Neurological Evaluation of Acute Ischemic stroke in Emergency Room
NRNB Annual Report 2013
1. Annual Progress Report - Research Progress 2013
National Resource for Network Biology
P41 GM103504
05/01/2012 - 04/30/2013
WANG,
JIGUANG
ZHANG, CHAO
CHRISTAKIS,
NICHOLAS
XU, DONG
KWOK, PUI-YAN
TANG, LING
FUNG
DUTKOWSKI,
JANUSZ
WAAGMEESTER,
ANDRA
LI, JIANFENG
DHRUVA, NEIL
ZHOU, YIGANG
SOBOL,
ROBERT W
SINHA,
SRAVANTHI
RANI
FRIED, JAKE
LAUNGANI,
RITISHA
WRENSCH,
MARGARET
LUNA,
AUGUSTIN
YUMOTO,
FUMIAKI
CONKLIN,
BRUCE
HANNUM, GREG
JONES, LEANNE
HANCOCK,
WILLIAM S
FLETTERICK,
ROBERT J
FIJTEN, RIANNE
LOTIA,
SAMAD
VAN IERSEL,
MARTIJN
KUMAR,
PRAVEEN
KIPPS, THOMAS ZHANG, KANG
GREGG,
CHRISTOPHER
KUTMON,
MARTINA
WILLIGHAGEN,
EGON
RATH,
CHRISTOPHER
M
DORRESTEIN,
PIETER
ASTAKHOV,
VADIM
FOWLER,
JAMES
DUTTA,
ANWESHA
BANDEIRA,
NUNO
DAWSON, TED
KAMBUROV,
ATANAS
SUBRAMANI,
SURESH
PENTCHEV,
KONSTANTIN
PICO,
ALEXANDER
DUVVURI,
VIKAS
NORMAN,
MICHAEL L
GUO, YURONG
VAN ATTIKUM,
HAICO
FERRIN,
THOMAS
MAERE, STEVEN
IDEKER, TREY
SHIH, DAVID
DEMCHAK,
BARRY
MORRIS,
JOHN
"SCOOTER"
PFISTER,
SABINA
BANDYOPADYAY,
SOURAV
ECKMANN,
LARS
KIRBY, MICHEAL
MONTOJO,
JASON
PEARSON, BRET
ALMAN,
BENJAMIN A
VOISIN,
VERONIQUE
GILSON,
MICHAEL
RODCHENKOV,
IGOR
GRAMOLINI,
ANTHONY
HU, ZHENJUN
KAY, STEVEN
MCCONNELL,
MIKE
SHARMA,
KUMAR
BEMIS,
DEBRA
EMILI, ANDREW
SCHWIKOWSKI,
BENNO
WOLF, DIETER A
GINSBERG,
MARK
GUITHART,
ORIOL
CHANG, JOHN T
NALDI,
AURâLIEN
LOPES,
CHRISTIAN
BADER, GARY
NOIROT,
PHILIPPE
TAYLOR,
MICHAEL
ISSERLIN, RUTH
ANDREWS,
BRENDA
SANDER,
CHRIS
DICK, JOHN
SIMINOVITCH,
KATHERINE
AKSOY,
BúLENT
ARMAN
GAIEVER, GURI
SINGH, SHEILA
ZACKSENHAUS,
ELDAD
BOONE,
CHARLES
JURISICA, IGOR
STEIN, LINCOLN
SANSONETTI,
PHILIPPE
VARMUS,
HAROLD
JIAO, DAZHI
SAKUNTABHAI,
ANAVAJ
LIU, JEFF
ZANDSTRA,
PEER
WALLACE, IAIN
BRUN,
CHRISTINE
CERAMI,
ETHAN
FRANZ, MAX
KUCHERLAPATI,
RAJU
DOGRUSOZ,
UGUR
RUGHEIMER,
FRANK
COLLOMBET,
SAMUEL
THIEFFRY,
DENIS
SONLU, SINAN
The 2013 NRNB Network. On the left is a network representation of all NRNB personnel and
collaborators (blue circles), all TRD, DPB, Collaboration, and Service projects (orange
diamonds), and associated publications (green triangles). Node size is proportional to the
number of connections. Thick red borders indicate personnel, projects and publications directly
funded by the NRNB P41 grant. On the right is a zoomed inset, inclusive of all NRNB-funded
personnel making up the vital core of the NRNB network. There are 276 nodes and 365
connections in the network. NRNB funds 46 (17%) of these nodes, which make 211 (58%)
of the connections. As a Cytoscape network [1], we can interactively explore this
representation with our External Advisory Committee, offering dynamic views of our projects,
collaborations and budgets. Also see Appendix A for a full-page view of the entire network.
HERMJAKOB,
HENNING ARANDA,
BRUNO
GAO,
JIANJIONG
BAHCECI,
ISTEMI
LEVINE,
DOUGLAS A
MESIROV, JILL P
WEBSTER, NICK
TILL, ANDREAS
DONG, YUE
FIUME, MARC
CHACHCHA,
KHUSHI
SMOOT, MIKE
MORRIS, QUAID
GUIDOS,
CYNTHIA
BRUDNO,
MICHAEL
BARK, STEVEN
J
SAITO,
RINTARO
ONO,
KEIICHIRO
KUCHINSKY,
ALLAN
DANSKA, JAYNE
MERICO,
DANIELE
HOOK, VIVIAN
HANSPERS,
KRISTINA
BROWN, JOHN
MEYERSON,
MATHEW L
LADANYI, MARC
SAWYERS,
CHARLES
PEROU,
CHARLES M
1. Smoot ME, Ono K, Ruscheinski J, Wang PL, Ideker T (2011) Cytoscape 2.8: New features for data
integration and network visualization. Bioinformatics 27:431–432.
BARBER, DIANE
L
CHANDA,
SUMIT K
2. Annual Progress Report - Advisory Committee 2013
National Resource for Network Biology
P41 GM103504
05/01/2012 - 04/30/2013
We held our second External Advisory Committee (EAC), on December 12, 2012, in
coordination with the annual Cytoscape Workshops and Network Biology Symposium
hosted by NRNB this year at the Gladstone Institutes in San Francisco. In addition to
the EAC members listed below, we also had our Program Officer, Doug Healy in
attendance. The following report was issued by our EAC.
Participating External Advisory Committee Members:
•
•
•
•
•
Stephen Friend, Sage Bionetworks
David Hill, Dana-Farber Cancer Institute
Tamara Munzner, University of British Columbia
Anya Tsalenko, Agilent Technologies
Marian Walhout, University of Massachusetts Medical School
Overall Perspectives of the NRNB External Advisory Board
All of the members of the advisory Committee found this meeting to provide evidence of
very strong progress and appreciated the increased clarity as to how to convey it to
outsiders. In the past 18 months all of the major suggestions have been effectively
addressed. The supplementary material has allowed a very powerful engagement by
Alex Pico and the delivery of an entirely new focus to build out the cytoscape tools
within a “cytoscape App store”: http://apps.cytoscape.org This has been matched by a
comprehensive evolution of functionalities within the new version of Cytoscape 3.0 and
a coherent maturation of all the Technology Research and Development Projects TRDs
and associated Driving Biological Projects DBPs. The three major suggestions this
cycle involve: 1) reviewing both the existing TRDs and DBPs to determine how midcourse optimization of these projects might allow maximal creation of “shining
examples” around the strengths of the NRNB, especially by searching for new distal
DBPs, 2) resolving the question of how to best measure success for the NRNB with a
transition away from paper/citation based metrics to metrics of community enablement
and integration, and 3) the importance of preparing for the extension by completing the
draft proposal in time to engage the EAC six weeks before it is due to be submitted. In
summary, the NRNB has continued to make excellent progress through the first half of
this funding period and the committee is strongly supportive of the overall progress and
direction. The comments below, albeit pointedly critical, are designed to help the NRNB
position itself for the strongest possible competitive renewal in 18 mos. Please see the
following descriptions of the specific programs for more detailed comments:
3. Specific Project Summary Statements
1) TRDs and DBPs (separate one for TRD3 and Cytoscape)
All of the NRNB labs continue to do exciting and cutting edge work developing new
approaches to develop network-based solutions to address important questions in
biological and social sciences. The “network extracted gene ontology” is one example of
integrating a novel way to better use ontologies while providing a visual output that
offers a clearer and better representation of functional modules. Integrating statistical
and scripting tools into Cytoscape is a decided plus, initially done in the context of social
networks, that should have broad applicability. Ongoing work is proposing potential
paradigm- shifting ways to answer questions and gain insight beyond traditional
approaches – using link clustering and network ontology, for example.
The recent set of publications across the entire spectrum of NRNB activities shows that
good progress is being made in developing new network-based tools and demonstrating
the value of studying networks. At the approximately halfway point of this grant, the
NRNB has provided clear examples of identifying problems or critical biological
questions that require novel approaches, proposing and developing solutions based on
integrating information into networks, and implemented potentially useful tools for
addressing similar questions. Each of the TRDs was individually successful in that
regard. The challenge going forward is to clearly demonstrate that these tools and
approaches have applicability beyond the questions/problem(s) that the individual TRDs
tackled in the first place. One thing to consider is now how to better integrate across
multiple TRDs. For example, can the tools being developed in TRD A, C, & D
be used in TRD B – this could be taken on as a collaboration or via a new DBP. Can the
tools in TRD D be used to add further insight in developing network as biomarkers or
network ontologies efforts?
TRD C has made significant and impressive progress in the past year, with flagship
projects in Mosaic (ontology-partitioned mosaics) and NeXO (network extracted
ontologies). The Mosaic work has already been released as a Cytoscape plugin. The
NeXO work is particularly exciting as a path to data-driven ontologies rather than a
single monolithic solution that is not sensitive to context.
Several possible avenues for moving forward with the NeXO work were discussed,
including the possibility of partnering with the existing GO project via supplemental
funding.
In terms of communicating the overall value of the NRNB to the broader scientific
community, there are four distinct elements that need to be clearly articulated in terms
of what the TRDs are doing and what the NRNB as a whole has accomplished: NRNB
to date has clearly shown 1) an ability to Identify a problem/driving biological question
that can not be done without a network approach; 2) an ability to develop new tools and
technology for network analysis and visualization; 3) an ability to implement usable tools
4. and demonstrate proof of concept; and, the most challenging, 4) an ability to
demonstrate that the tools are getting into wide use (e.g. via Cytoscape). This will
require additional tracking and curation efforts that will be challenging because
Cytoscape is now viewed as a “standard tool” and therefore less likely to be cited.
The NRNB is poised to be more than a collection of already successful TRDs. There
should be some consideration for a major paper that involves ALL TRDs and many of
DBPs to show how the new suite of Cytoscape tools can help answer a major question
in elucidating genotype-to-phenotype relationships. Cytoscape has become a great
collection of tools and NRNB has done great science developing some new tools and
using them on a specific question – but the NRNB needs to move beyond being just a
developer of Cytoscape tools and should look towards becoming an entity that is more
of a “whole is greater than the sum of the parts”.
While the entire spectrum of projects involving all TRDs and DBPs is quite exciting, now
is the time to begin considering restructuring the DBPs – potentially eliminating some –
as plans are developed for the competitive renewal in 18 months.
One area to consider is whether or not the NRNB should begin to branch out with
respect to other disease models – much of the recent success has been focused on
cancer – as there is more and more evidence for many genes to be involved in diseases
very distinct from the initial disease associated with any given gene.
As previously, Hill’s lab is willing to serve as an alpha or beta test site for data
integration and novel visualizations as well as testing plug-ins for statistical analysis
coupled to visualizations.
In Summary, it is clear that some TRDs are progressing well and are on track to roll out
tools for network biology that will be widely used. In other cases, it is not clear the right
audience is being reached. With this in mind, we recommend that the NRNB perform a
comprehensive review of all TRD projects and strive to align them with a set of DBPs
that represent the most active user communities in network biology with the following
goals:
● Reach out to key/hub user bases for each technology
● Pursue opportunities for cross pollination/integration/pipelines across NRNB
technology projects, which are currently being developed in isolation
● Identify other important resources and tools that NRNB TRDs could integrate with
Cytoscape Progress:
The team has made great progress towards Cytoscape 3.0: the beta release has been
available for many months, and the full release is coming very soon. Many suggestions
from the last meeting have already been incorporated, including identifying which
previous plugins are high impact and devoting resources to make sure that these are
5. ported to the new version.
The issue of backwards compatibility was raised again, since Cytoscape 3.0 introduces
major API changes that prevents old plugins from working without code updates. The
verbal answer made it clear that choices had been carefully considered in consultation
with the developer community. In particular, the assurance was made that API
compatibility is a guaranteed contract for all 3.x versions with no changes made before
version 4.0, thanks to the use of semantic versioning. The suggestion was made once
again to ensure that keeping the API stable is a very high priority, because as the user
community grows in size the costs of breaking backwards compatibility increase
accordingly.
The consensus was that the process taken as described verbally was sound; it was just
poorly documented in the written report. The suggestion for next time is to more
explicitly document several things:
-
process taken (to show that care was in fact taken)
-
lessons learned: what worked, what didn't
-
plans for the future
The team has made great progress in better documenting the use of Cytoscape by the
biology community, with compelling statistics about the amount of use (including the
impressive number of 1400 NIH grants). The changes made to the cytoscape.org front
page with the tumblr feed showing images and the explicit encouragement that people
should cite its use are great. The use of resources to also manually track the divergence
between citation rates and use is entirely appropriate (with the interesting result that use
is at least 2x the citations).
There are many new exciting technical directions. The new AppStore will benefit many
constituencies: developers, end-users, and the PIs themselves in documenting usage of
its efforts by the community. The set of new features chosen also reflects the needs of
many constituencies, for example scaffolding new users with the new welcome/startup
screen, and supporting developers with the new API. It's also heartening to see
technology transfer from the visualization community with the incorporation of edge
bundling.
The report mentioned new support for 3D rendering. Concerns were raised about
whether devoting resources to this effort is appropriate given the empirical work from
visualization community that has found many drawbacks to 3D layout of node-link
graphs. The verbal answer was the new modular architecture allows alternate
renderers, and 3D was simply one of several, and it was developed by a community
member rather than the core developers.
2) Outreach and Impact
At the last advisory board meting it was suggested to “distribute open source network
6. technologies to the greater scientific community”. This meeting Alex Pico presented the
NRNB execution on that suggested deliverable. Simply stated there has been awesome
progress and much of this stems from the direct leadership of Alex in his new role as an
Executive Director of the NRNB. Whether measured by the recently published article in
Nature Methods “A travel guide to Cytoscape plugins, or through a visit to the cytoscape
app store you can get to by googling “cytoscape apps” http://apps.cytoscape.org or by
looking at how often they are used, this stands out as a remarkable success. It is now
possible to extend this powerful start and consider annotating it with sections for open
source and non-open source apps. There is a possibility to begin a dialog between
those that desire new apps with those willing to build them. It might even be possible to
now have funding listed and contests to encourage the building out of the most
requested apps.
3) Moving forward: Ideas and Topics for Discussion
A lot of discussion about moving forward to NRNB effort was centered on increasing
outreach to potential users of NRNM resources including Cytoscape, as well as tracking
the use of these resources. Big progress has been made already through
http://www.nrnb.org website, Cytoscape app store, but more could be done.
Some suggestions for increasing outreach to users included targeted communications
to potential users either subscribed to Cytoscape mailing list, or authors of papers using
Cytoscape. Connections to various social media resources like twitter or facebook could
be increased. Quantitatively this outreach could be measured by the number of groups
using NRNB resources, not in number of papers citing these resources or Cytoscape.
Some of the papers may not cite Cytoscape directly, but have it buried in the
Supplementary information that is not being searched or not cited at all.
Impact of Cytoscape and NRNB tools in general could be increased by connecting to
other public resources for molecular and computational biology. One example is
connection with GenomeSpace (www.genomespace.org) which is a platform that
connects different bioinformatics tools, making it possible to move data smoothly
between these tools and leveraging available analysis and visualizations. Other public
resources that could benefit from connection to Cytoscape include Galaxy,
KnowledgeBase, and IGV. Sharing between users could be increased by enabling
smooth sharing Cytoscape networks on Google Drive or Amazon Cloud, as well as the
use of Cytoscape web.
One area of applications of network biology tools that could be significantly expanded
going forward is social network research, especially analysis of social and molecular
networks, and interactions between different groups.
NRNB group made an impressive progress with tens of successful Google Summer of
Code projects. Going forward it would be great to track careers of these students and
students from NRNB mentorship program as another way to measure impact on
community and science.
7. 4) Suggestions For Next EAC Meeting and Report:
1. Next Report
This year's report was much better than last year's; however, there is still room for
improvement.
As suggested, the emphasis shifted from the science results of the DBPs to the more
appropriate new developments created through the TRDs; that's a major improvement.
However, the problem of documenting to what extent the output of this and previous
funding -- new tools or methods -- are used in biological discovery could be even more
clearly addressed.
For example, in the group's own research papers that are not directly about the
development of Cytoscape itself, to what extent was the use of Cytoscape instrumental
in achieving the research results? We suggest that this story should be told very
explicitly.
Another suggestion for the next round is to provide a full list of results or subprojects at
a fine-grained level, for example a specific new Cytoscape plugin or new analysis
method proposed in a research papers. For each result, identify progress according to a
four key milestones:
1. Identify problems
2. propose solutions (for example, new methods in published paper)
3. build generally available tool
4. get other people to use it
The goal should not be to reach the final milestone for every idea, but to document
progress in terms of moving from earlier ones to later ones. Subprojects may enter at
any stage, they don't have to be seeded only through the DBPs in the original grant.
Subprojects may also exit at any stage, for example when the decision is made to
propose alternate new solutions rather than following up with tool building in every case.
It was clear from the verbal discussion that the center should be able produce some
very satisfying answers of its achievements along these lines, and that these proofs of
accomplishment will be a compelling and convincing part of a renewal proposal. This
type of reporting will also help with the argument that the impact of Cytoscape and the
NBRB goes beyond simple publication counts and citation counts. The deeper goal of
the center is to introduce and encourage network methods in the biology community, so
documenting the adoption of methods and tools shows progress towards that goal.
A second suggestion is to more clearly explain the boundary between this P41 and the
other sources of funding: the related R01, and the grants supporting the DBPs. Ideker
articulated a clear story in response to EAC questions: the $300K/yr R01 funds
maintenance, while new technology springs from the $700K/yr P41. The committee
approves of this story; it just needs to be told clearly and concisely in the written
8. materials. In particular, document what efforts are funded through the R01 and what are
through the P41. Although the NRNB has broader scope than Cytoscape alone, since it
is partially funding core Cytoscape work the best way to address this boundary is to at
least briefly present the full picture of what work on Cytoscape has been done, and then
to explain what parts were funded by the P41. The current report gives the full picture of
Cytoscape development, but does not adequately explain the boundary.
The administrative information section is very well done. The budget is clearly
explained, with crosscutting breakdowns between categories (staff vs. TRDs vs. PI
salaries) and PI groups. The breakdown of expenses according to both FTEs and
money was also helpful. The discussion of the importance of actively cultivating an open
development community is articulate.
2. Next Meeting
First, the EAC should be sent the relevant written materials to read in advance of the
actual meeting. This year, the report was provided on paper to committee members at
the start of the meeting, with an electronic version following a few hours into the
meeting. This timing is too late, because it's hard to assimilate the written report in
parallel with attending to the presentations. The report should be provided to committee
members in advance, ideally one week before the meeting, and at bare minimum at
least two days before the meeting. The late timing this year was particularly frustrating
given that this report was created many months ago, but through an oversight hadn't
been forwarded to us.
Second, the EAC agreed that we would best serve the interests of the NBRB by
scheduling our next meeting shortly before the renewal proposal is due in what we think
will be June 2014. Our intent is to act as pre-reviewers, where we will read a full draft of
the proposal in detail before the meeting and then devote the meeting to an in-depth
discussion of ways to strengthen and improve it. We propose roughly six weeks before
the proposal is due: early enough that our feedback can be responded to, but late
enough that the draft proposal is nearly complete rather than preliminary. This meeting
would be roughly 1.5 years from now, the same amount of time that has elapsed
between our first and second meetings.
Third, a suggestion for the renewal proposal is to have a large set of short testimonials
from users, rather than (or in addition to) the more usual approach of full formal letters
of support from a small number of people. The testimonials would be a few sentences
or a paragraph about how Cytoscape has been valuable in their own work; having
dozens or even hundreds of these compiled together in one document might have
enormous impact on reviewers.
5) Collaborations and service projects
A major goal of NRNB is to support collaborations with a broad variety of researchers in
Biomedical science. Different types of collaborations have been initiated from very small
support-style collaborations to larger collaborations that require active participation by
NRNB. The EAC was very impressed with the overall number of collaborations. At the
9. time of the previous SAB meeting, there were 36 active research collaborations with
NIH-supported researchers. In the last 1.5 year or so, another 60 were added, making a
total of 96. One issue is that the majority of collaborations are internal Better
advertisement of NRNB and its collaborative goals at relevant scientific conferences
may help to acquire more external collaborations.
Collaborations are only a small part of the NRNB budget with an estimated cost of
~$100,000, but are highly effective at leveraging the NRNB expertise to expand the
overall impact and reach of Cytoscape.
The term ‘collaboration’ is used in a way that is somewhat ambiguous: within the CSP
umbrella is included tiny-scope efforts called ‘support’ (33%), small-scope efforts called
‘consulting’, and medium- scope efforts called ‘collaboration’. However, the DBPs are
what we might consider true collaboration, and the hope is that some of the mediumscope efforts would evolve into new DBPs over the time, even as some previous DBPs
might be scaled back into a smaller role. However, since the term ‘CSP’ is the standard
vocabulary defined by the grant, perhaps it is not realistic to rename these mediumscope efforts. It would be useful to see these numbers proportioned for internal versus
external collaborations.
These collaborations are currently tracked in a publicly available and transparent way
on the NBRB web site with titles, investigators, and NRNB contact. It would be useful if
their status could also be tracked.
For the renewal, it will be very important to obtain letters or a filled out survey from
collaborators regarding the utility of Cytoscape and how it changed their research.
6) Promising ideas for potential supplemental funding
The first supplemental effort provided to the NRNB enabling the Cytoscape App Store
project has turned out to be a remarkable return on investment, demonstrating a
capacity for greater creativity and productivity. We highly recommend additional
supplemental grants to maintain, or even increase, this level of activity. During the
advisory meeting, we explored a number of proposals worth considering:
1. Moving NeXO forward (see TRD A) by partnering with existing GO projects
2. Enable Cytoscape users to record/reuse/host/share workflows and sessions to
promote network biology use cases, enriched publications, reproducibility and
collaboration.
3. Interface with a specific key technology that targets a strategic community ripe for
network biology perspective/tools (e.g., MIDAS, UCSC Genome Browser, NCBO
BioPortal, Galaxy, GenomeSpace, Sage Bionetworks/Synapse, DREAM)
10. Annual Progress Report - Administrative Information 2013
National Resource for Network Biology
P41 GM103504
05/01/2012 - 04/30/2013
Administrative Structure
During the first year, we defined the administrative structure of the resource, including some
unique new roles within the organization. The roles of Principal Investigator (PI), Co-PI, External
Advisory Committee (EAC), Resource Administrator and Chief Software Architect were defined
as in the original grant. We defined a new role of Executive Director (ED) to oversee some of
the new resource functions that NRNB provides, including Training & Outreach,
Communications and Infrastructure. The ED (Alex Pico, Gladstone Institutes) is responsible for
coordinating these efforts as well as conducting all of the necessary tracking and due diligence
for the annual reporting to NIH. During the second year, we defined the new role of
Collaboration Coordinator to screen and process collaboration requests to our resource. This
has been a vital role in supporting the 80+ ongoing collaborations during the past two years.
During the third year, we defined a proper position for the Roving Engineer who is vital
for outreach to new users, app developers and strategic partnerships. Our Roving
Engineer is also a major contributor to Cytoscape core design and implementation,
embodying the full cycle from users to developers to implementation to release. Finally,
we are very pleased to have maintained an active dialog with our EAC members, including Dr.
Stephen Friend as chair of the committee.
Budget changes have been minimal over the three years, with the exception of the new
Collaboration Coordinator and TRD increases for Pico, Ideker and Sander in Year 2, and the
new Roving Engineer and subsequent TRD cuts to Pico and Ideker in Year 3. The trend over
time has been toward supporting more Outreach initiatives to fulfill our P41 goals.
A
B
Outreach
Ideker
TRDs
Pico
Sander
Bader
Admin
Schwikowski
Co-PIs
Fowler
11. Figure 1. Budget graphs. Area charts showing the distribution of funds for years 1-3 (x-axis)
per category (A) and per group (B). Y-axis is in units of $1,000s of US dollars. Each stripe
typically corresponds to an individual with a specific role in NRNB, totaling 6.5 FTEs. Note that
groups are sorted by degree of change, which is critical in this style of visualization to minimize
misperception of change when slopes are actually parallel.
As the basis for the graphs above, here are itemized tables of FTEs and funding for all three
years (Table 1). Highlighted in red are the significant changes in Year 3 to FTEs and total
dollars.
Roles and Groups
Collaboration (Ideker)
Admin-Asst. (Ideker)
Core Tech. (Ideker)
TRD-A (Ideker)
Admin-PI (Ideker)
Communication (Pico)
Admin-ED (Pico)
Roving Engineer (Pico)
TRD-C (Pico)
Co-PI (Pico)
TRD-A (Sander)
Co-PI (Sander)
TRD-C (Bader)
Co-PI (Bader)
TRD-D (Schwikowski)
Co-PI (Schwikowski)
TRD-B (Fowler)
Co-PI (Fowler)
SUBTOTAL
Supplement (Ideker)
Supplement (Pico)
Supplement (Bader)
SUBTOTAL
GRAND TOTAL
Year 1
0.00
1.00
0.40
0.50
0.30
0.30
0.50
0.00
0.20
0.02
0.65
0.02
1.00
0.10
1.00
0.08
1.00
0.10
7.17
FTEs
Year 2
0.50
0.56
0.40
0.50
0.30
0.30
0.50
0.00
0.48
0.02
0.65
0.02
1.00
0.10
1.08
0.08
0.72
0.10
7.32
Year 3
0.63
0.56
0.40
0.50
0.29
0.25
0.50
0.12
0.13
0.02
0.62
0.02
0.91
0.10
1.08
0.08
0.20
0.10
6.51
Year 1
0
52
47
40
74
29
56
0
21
5
90
5
90
0
81
0
58
21
669
$1,000s
Year 2
50
38
51
45
78
29
56
0
39
5
97
5
93
0
83
0
54
26
750
Year 3
50
41
53
36
77
25
57
16
17
0
98
5
90
0
83
0
53
27
728
0.00
0.00
0.00
0.00
7.17
0.40
1.00
0.40
1.80
9.12
0.40
1.00
0.40
1.80
8.31
0
0
0
0
669
45
85
45
175
925
45
85
45
175
903
Table 1. NRNB effort and budget. Annual budgeting of FTEs and $1,000s itemized by roles
(per group). Major changes are highlighted in red. Subtotals are provided separately for the
main grant and supplemental funding (bold) and Grand Total is in the last row.
Allocation of Resource Access
Beyond the active distribution and support of Cytoscape, which is covered in later sections,
NRNB resource allocation can be categorized in the following way:
1. On-site training events: NRNB staff participated in 13 training events during the
reporting period. These events include tutorials, workshops and courses.
12. 2. Requests for collaboration and mentorship: For the second consecutive year, we
have maintained a high number of active collaborations. Many of these collaborations
are coming through our participation in Google Summer of Code (GSoC) and our own
NRNB Academy efforts (see #3).
3. Google Summer of Code and NRNB Academy: In addition to receiving requests from
potential students through these programs, we also receive requests from a number of
groups to join our organization as mentors. This brings new technology and ideas to our
effort. GSoC has been our most successful outreach program by far. It’s responsible for
a quarter of all our NRNB collaborations. It is the most active period for NRNB.org,
granting broad exposure for NRNB in the open source community. Building on the
success of this model, we launch NRNB Academy last year. Our Academy follows the
same approach as GSoC, organizing around available mentors, ideas and interested
students. However, we are not restricted to supporting university students in our
program as it is independent of GSoC and 100% volunteer based. The Research
Progress and Highlights provide more details.
4. Requests for training material support: We receive requests for tutorial materials
throughout the year from inside and outside the Cytoscape core development team. Our
homegrown Open Tutorials system makes it easy to accommodate all such requests.
Open Tutorials is an easy-to-use wiki system that provides content formatted to be used
as online sessions, slide shows and printed handouts. This year we are seeing more
content from more contributors, in addition to a steady rise in visitors (see details in the
Training section below).
5. Providing software community support: Our goal is to develop a generic template of
services based on the support we provide the Cytoscape community of users and
developers. So far we have extended support to Cytoscape, WikiPathways, Cytoscape
Web and the cBio Cancer Genomics Portal. These proven resources demonstrate the
broader scope of the NRNB mission. We are providing distribution links, showcases,
tutorial support, news and event tracking, and GSoC and NRNB Academy participation
to these projects. New this year, is a gallery page with screenshot for all of these tools.
Awards and Honors
None
Dissemination
Overall
Cytoscape Version 3.0 (v3.0) was released for unrestricted public use on February 1, 2013. It
represents an evolution of v2.x resulting from a two-year collaboration of a multinational, multiinstitution team of programmers and biologists. This report describes the Cytoscape software,
the infrastructure that supports it, and the activities of the community it serves.
Background
The overall mission of Cytoscape is to be a freely available worldwide asset supporting network
analysis and visualization for systems biology science. The major focus of v3.0 is the
modularization and rationalization of code to solve stability issues in v2.x encountered as
multiple developers pursued multiple agendas. Under v2.x, internal programmatic interfaces
evolved from one release to the next, leading to the failure of working plugins over time and
13. negative interactions between otherwise working plugins. Ultimately, this resulted in loss of
programmer and user productivity, and undermined community confidence in Cytoscape.
v3.0 addresses these issues by adopting modular coding practices promoted by the OSGi1
architectural framework. This enables both the Cytoscape core and externally developed apps
(formerly called plugins) to evolve independently without compromising unrelated functionality.
At the logical level, Cytoscape leverages OSGi precepts to produce v3.0 APIs having cleaner
and clearer demarcations between functional areas. At the deployment level, OSGi enables onthe-fly substitution of one processing element for another (e.g., apps) in order to tailor
Cytoscape to meet user requirements at runtime without reinstalling or reconfiguring Cytoscape.
v3.0 represents a strong investment toward reducing future development and support costs, and
increasing reliability and evolvability. We expect to leverage v3.0 as a platform to satisfy the
evolving needs of multiple stakeholder groups, and as a platform enabling research on leading
edge analysis and visualization techniques. v3.0 is the intended successor to v2.8, with
development and support of v2.8 expected to diminish and disappear over time in favor of v3.0
and its successors. v3.0 is upward compatible with v2.8, but not downward compatible.
While v3.0 is a substantial reorganization of v2.8, its launch marks an evolution in the
Cytoscape team’s approach to community engagement, where different community
demographics are engaged in different, demographic-sensitive ways. The team identified four
major groups: new users, casual (but not new) users, power users, and app developers. Initial
v3.0 release was promoted towards power users and app developers as a way of delivering
v3.0’s advanced capabilities to groups most able to leverage them, give qualitative and remedial
feedback, and promote v3.0 adoption to other Cytoscape users. This strategy dovetails with
v3.0 features (described below) that lower barriers to entry for new and casual users while
enabling efficiency and productivity for power users and app developers.
The second release (v3.0.1) is imminent – it incorporates various critical fixes and numerous
feature requests made by early v3.0 adopters. As such, it will be promoted to the entire
Cytoscape community, including new and casual users. v3.0.1 will become the default
Cytoscape download, replacing v2.8 as the default.
As compared to v2.8, Cytoscape users will benefit most directly from the v3.0 in the long run by:
• experiencing
fewer
core
and
app
bugs
from
one
release
to
the
next
• the
availability
of
more
and
richer
apps
(due
to
developers
spending
less
time
tracking
and
fixing
bugs)
• more
core
features
with
higher
biological
and
logistical
value
(due
to
improved
flexibility
provided
by
interface-‐driven
development)
The v3.0 Release
Throughout 2012, Cytoscape developers made a number of beta versions available to early
adopters. Issues were tracked in RedMine, and were contributed by both developers and early
adopters. The final release was made on February 1, 2013, accompanied by updated user
documentation, user tutorials, JavaDoc programmer documentation, app developer tutorials, a
new App Developer Cookbook (containing useful code snippets), and release notes.
1
www.osgi.org
–
also
used
as
the
basic
framework
for
Eclipse
and
numerous
commercial
products
14. Additionally, a new and comprehensive user-focused Welcome Letter was created to
differentiate between different user demographics and engage them appropriately.
Principle v3.0 development was carried on by staff and researchers worldwide, including the
following institutes: UC San Diego, Pasteur Institute, University of Toronto, Gladstone Institute
(UC San Francisco), University of Amsterdam.
v3.0 included the following major features:
• Upward
compatibility
with
Cytoscape
2.x
networks,
attributes,
analysis,
layout,
and
display
• App
Store
(for
centralized
app
availability)
• Friendly
Welcome
dialog
(to
engage
new
and
casual
users)
• Import
network
• Edge
bend
visual
property
• Edge
bundling
• Grouping
(for
hierarchical
networks)
• Enhanced
search
• Show
All
in
Table
Browser
• Multiple
network
management
• Major
refactoring
to
rationalize/regularize
inter-‐module
interfaces
(to
aid
app
developers
in
creating
reliable
apps)
Major issues remaining after the v3.0 release included:
• Slower
startup
than
v2.x
• Fewer
apps
(plugins)
than
v2.x
• Numerous
undiscovered
or
unaddressed
bugs
(due
to
major
refactoring)
• Smaller
network
capacity
on
32
bit
processors
There are 145 apps (plugins) available in v2.x, though many have gone unmaintained and have
fallen out of use. Of the v2.x plugins, 8 were delivered in v3.0 as core functionality:
EnhancedSearch
MetanodePlugin2
PSICQUICUniversalClient
GraphMLReader
NCBIEntrezgeneUserInterface ScriptEngineManager
JavaScriptEngine
NetworkAnalyzer
Additionally, the App Store contained another 13 apps (corresponding to many of the most
popular v2.x plugins):
AgilentLiteratureSearch
Cy3PerformanceReporter
jActiveModules
CentiScaPe
Cyni Toolbox
MCODE
ClueGO
CyPath2
PathExplorer
CluePedia
DynNetwork
Venn and Euler Diagram
ClusterOne
GeneMANIA
Bug Bounty
To foster early investment and engagement in v3.0 by the user community, we created the
Cytoscape Bug Bounty program, which paid out small prizes to users identifying high value
bugs in the month of February 2013.
15. The program produced 35 bugs by 17 qualified reporters: 8 crash/data loss, 19 user interface,
and 7 cosmetic. Gift cards were given to the top 9 reporters.
It
was
great
fun
to
participate
in
the
February
Bug
Bounty.
Thank
you
for
organizing
it,
and,
in
general,
thank
you
for
making
the
development
of
Cytoscape
an
open
process.
It’s
really
appreciated,
from
the
point
of
view
of
the
users,
when
a
software
is
developed
this
way.
In
general,
I’ve
found
that
the
new
Cytoscape
3.0
version
is
a
great
improvement
over
the
previous.
The
new
“Welcome
screen”,
together
with
many
little
improvements
to
the
menus
and
the
interface,
gave
me
a
feeling
of
very
user
friendly
software.
The
ability
of
downloading
whole
species
for
networks
with
a
click,
or
to
import
them
from
many
sources,
is
attractive
to
many
people,
and
I
know
some
persons
who
will
use
it
for
their
work.
The
App
store
is
also
a
nice
addition,
as
it
is
much
better
to
have
a
common
web
page
for
all
the
plugins
instead
of
having
to
look
for
documentation
dispersed
into
many
little
websites.2
The v3.0.1 Release
The v3.0.1 Release is scheduled for April 18, 2013. Its main purpose is to eliminate bugs
leading to data loss, program crashes, misleading displays, and small user interface issues.
Given this, we expect that it will be suitable for use by the entire Cytoscape community
(including new and casual users) in preference to v2.8, and we expect v3.0.1 to become the
default download on the Cytoscape web site.
The first v3.0.1 release candidate (RC) will become available for download by April 4. It will
include fixes or resolutions for 98 reported bugs and other issues, including 30 of 35 reported
under the Bug Bounty program.
Notably, the v3.0.1 release:
• Substantially
increases
the
size
of
network
manageable
on
32-‐bit
systems
• Migrates
source
from
SVN
to
GitHub
(to
expand
collaboration
opportunities)
At release time, we expect there to be slightly under 200 bugs or unresolved issues remaining
on our backlog, including feature requests and issues requiring substantial development or
rework. Additionally, app developers have asked for improved documentation to enable quick
and reliable app development.
Currently, UC San Diego is upgrading three v2.8 plugins to become v3.0 apps, and expects
completion in Q3 2013:
• GenomeSpace
• MiMI
• BiNGO
Additionally, the NRNB has offered Amazon gift certificates as rewards to app developers for
the first 20 apps independently developed and submitted.
2
Giovanni
Marco
Dall’Olio,
March
8,
2013
via
e-‐mail
16. Bug and Issue Tracking
Since early 2011, the Cytoscape team has tracked bugs and issues using the RedMine cloud
service. As of v3.0, users can inject reports of bugs and issues into RedMine directly from
Cytoscape. A CDF plot of bugs and issues logged over time shows aggressive tracking:
The following CDF shows that the Cytoscape team has responded to logged reports (by
addressing them as bug fixes or scheduling them to be addressed in the future).
“Created” means that a ticket was opened, and “Updated” means that a Cytoscape team
member has acknowledged it, and has prioritized it for solving or has already solved it.
Measured Results
Cytoscape Downloads and Web Site Visits
Through 2013, the overall number of Cytoscape downloads (including v2.8 and v3.0) continues
to rise. The chart below shows the monthly download counts, with data dropouts in November,
17. 2007 and March, 2009. In February 2013, the download count was 6,685, and the count for
March was 7,323.
Since 2012, weekly visits (outside of holidays) have increased. The Cytoscape v3.0 web page
was first put up in October 2012. The trends since the February, 2013 release are too new to
yield conclusions, though it seems that visits have measurably increased. Visits to the
Cytoscape download page have remained somewhat constant over time, though seem to have
increased since v3.0’s February 2013 release.
18. In examining year over year visit patterns, 2013 visits have increased by about 30%, with an
uptick corresponding to the v3.0 release timeframe. This pattern is reflected in visits to the
download page, too. Note that visits to the v3.0 page are associated with about 25% of page
visits. (Note that visits to the v3.0 page are prerequisite to downloading v3.0, and therefore
bounds the count of v3.0 downloads. Visiting the v3.0 page can have many purposes, only one
of which is downloading v3.0.)
Between January 1, 2012, and the end of March, 2013, the Cytoscape web site received
393,903 distinct visits. Web site visitors were geographically dispersed worldwide:
19. Cytoscape visitors arrived most often after performing a Google search, but also arrived from
direct links and from links within Cytoscape web pages:
20. App Store
The App Store opened for business on June 1, 2012. Since then, it has received over 33,000
visits from users worldwide:
Most visits originate from a link within the Cytoscape web site but a significant number of visits
launch from search engines and direct links:
21. Except for during the holiday season, the traffic to the App Store has consistently grown. By
March, 2013, weekly visitors numbered between 1,100 and 1,300. Through March, 2013, a total
of 33,596 visits were received:
Interest was evenly distributed across a number of app categories:
The most frequently downloaded apps (as of March, 2013) were:
App
ClueGo
GeneMANIA
jActiveModules
MCODE
Count
1,394
1,230
1,196
980
22. Cytoscape Citations
The count of Cytoscape-citing papers continues to accelerate year-over-year, with the count for
2013 being incomplete (as of March, 2013).
Year-over-year growth has been historically sporadic, and may be showing signs of slowing:
Year-over-year
Growth
2004-2005
64%
2005-2006
72%
2006-2007
126%
2007-2008
94%
2008-2009
80%
2009-2010
8%
2010-2011
32%
2011-2012
19%
2012-2013
incomplete
Community Outreach
The Cytoscape community consists of core developers, app developers, and users.
Communication and outreach is multimodal: Google Groups for contemporaneous discussion,
Google video and Hackathons for core developer meetings, papers, web site and social media,
and public meetings and symposia.
Google Groups and Video
The Cytoscape team has maintained Google Groups since April, 2011. As of March, 2013, there
were 4 groups:
23. Group
cytoscape-discuss
cytoscape-helpdesk
cytoscape-announce
cytostaff
Membership
1,531
1,148
918
49
Topic Count
2,570
1,413
194
2,643
The discuss and helpdesk groups facilitate self help (through search), peer assistance, and
assistance directly by Cytoscape core developers. The announce group is used by Cytoscape
core developers to announce new Cytoscape releases, and by app developers to announce
new apps.
The cytostaff group enables communication between Cytoscape core developers to coordinate
activities and exchange technical information. Cytoscape core developers also meet on video
chat weekly to plan agendas, triage issues, and conduct infrastructure activities.
Hackathons
The Cytoscape team conducted a Hackathon at the Gladstone Institute in San Francisco on
December 12, 2013, concurrently with the annual general Cytoscape symposium. Participants
laid out the following roadmap for short and medium term development:
• Table
loading
performance
• Network
panel
update
• Command
language
support
• Search/Filter
API
• Property
Sheets
• Separation
of
ViewModel
• Advanced
Label
Rendering
(Zoom/multi-‐scale)
• JSON
package
to
support
external
processes
• SBGN
symbols
• Table
merge
• Vizmapper
documentation
• Developer
requests
o Integration
to
R/scripting
o XMLRPC/REST
access
o Headless/daemon
mode
Web Site and Social Media
The main Cytoscape web site (cytoscape.org) was augmented to include a branch for v3.0,
which includes user and developer documentation, links to the Welcome Document and release
notes, and links to presentations and social media sites. Notably, videos of app presentations at
the December 13-14 general Cytoscape symposium were posted at:
http://nrnb.org/presentations.html
24. Future Risks
The primary objective of the architectural refactoring that transformed Cytoscape v2.8 to v3.0
was to normalize relationships amongst subsystems so that changes could be made in one
subsystem without detriment to another. While this evolution has been accomplished, much
code was changed, and bugs continue to be discovered and reported by the user community.
For now, the community remains forgiving and indulgent, mainly because Cytoscape’s basic
functionality appears sound. However, the community perspective may change when v3.0
becomes the default download. While bugs can be fixed on point releases, slow startup times
and the slow conversion rate of v2.x plugins into v3.0 apps remain a threat for several quarters.
Mitigating strategies include continuing the excellent and diligent support offered by the
Cytoscape team and community, which serves to help prioritize release features and to keep
user frustration from growing. Additionally, software reliability can be improved by incrementally
developing automatic test suites beyond what exists today.
While Cytoscape’s semantic versioning provides app developers with important guarantees of
interface- and semantic-consistency as Cytoscape evolves, it’s possible that semantic
versioning itself may threaten to retard plugin authorship, rendering Cytoscape unresponsive to
scientific requirements in meaningful timeframes. The interfaces defined in Cytoscape 3.0 have
been shown to be insufficient for the needs of new apps in some cases. While new interfaces
can be added, doing so requires incrementing the minor version number (e.g., from 3.0 to 3.1),
which is intended to occur only rarely. Furthermore, the operational complexity and overhead of
making new Cytoscape releases virtually guarantee the slow evolution of Cytoscape interfaces.
Mitigating strategies include deliberately hastening the pace of interface-augmenting releases
and engaging app developers to aggressively feed interface requests to the team – possibly at
the expense of core development.
Notwithstanding the enormous benefits of the architectural refactoring, critical Cytoscape
subsystems (e.g., user interface and apps) remain tightly coupled. This coupling threatens (at
best) to recapitulate the tangled relationships that triggered the refactoring or (at worst) make
the replacement, scaling, or reuse of these subsystems problematic. Eventually, this threatens
the evolvability of Cytoscape to serve scientific interests in relevant timeframes. Mitigating
strategies include focused refactoring of key subsystems along SOA (service oriented
architecture) or COA (component oriented architecture) principles to expose and separate
distinct concerns. This type of refactoring can occur while implementing a given use case, and
then leveraged to benefit subsequent, related use cases.
Patents, Licenses, Inventions, and Copyrights
None. We are committed to an Open-Source dissemination policy.
Training and Outreach
Annual Cytoscape Retreat
The annual Cytoscape Workshops and Symposium was hosted by the National Resource for
Network Biology (NRNB) at the Gladstone Institutes on the UCSF Mission Bay campus in San
Francisco during this reporting period. In addition to developer meetings, the event included
user and new developer tutorials, a Plugin/App Expo, a special Network Biology symposium,
25. and our EAC meeting. The meeting was a huge successful with capacity attendance for the
user tutorial and very positive survey responses from attendees.
Workshops
For the reporting period, NRNB has participated a total of 13 training events in multiple
countries. These events include tutorials, workshops and courses. Cytoscape is taught in many
classroom and workshop settings. We try to track all of these on our website and Event Tracker.
We’ve identified 37 courses offered in the 2012-2013 calendar year! And these are just the ones
affiliated with NRNB staff.
Open Tutorials
Our tutorial management system, Open Tutorials, is still the main source for tutorial materials for
the Cytoscape project, and is being used both internally by presenters, and by researchers and
developers. Visits to Open Tutorials have continued to increase over the last year, with an
average of 3750 visits/month, as compared to 2700 visits/month for the previous reporting
period. More than half of all visits (57%) are from new visitors. We estimate that the increase in
traffic is mainly from users, as we have had only two new editors in the same period.
Tutorial development during the past year was focused on a set of user tutorials for Cytoscape
3.0, covering the most common use cases and describing the user interface and new welcome
screen. We plan to add several additional user tutorials over the next 6 months. Overall, Open
Tutorials has allowed NRNB to reach our goal of providing tutorial support to a broad and
diverse community.
Social Media
We have initiated a social media effort for Cytoscape through a number of different tools
(http://www.cytoscape.org/community.html). For example, a Twitter account is used for quick
announcements (http://twitter.com/cytoscape) and YouTube is utilized for video tutorials
(http://www.youtube.com/results?search_query=cytoscape). During this reporting period we
continued the popular Tumblr site to capture published figures using Cytoscape. Pairs of figures
are posted on a weekly basis on the front page of cytoscape.org based on this Tumblr feed. We
now regularly get authors submitting their recent publications to us, asking to feature them via
our Tumblr site. This is directly helping to promote the use and citation of Cytoscape.
Google AdWords
We were awarded a non-profit account in the Google AdWords program. We are managing 8
Ad Group campaigns consisting of over 880 keywords and phrases. Last month alone we
received over 7,000 clicks on these ads to our NRNB sites. These activities are worth over
$8,800 a month (a 550% increase over last year), which we are getting free-of-charge. We have
a spending limit of $329 per day through this program, a potential value of $120,000 per year,
so we will continue to identify new ads and relevant resources.
Google Summer of Code and NRNB Academy
In addition to the outreach effort described above, we also leverage a Google-sponsored
program called Google Summer of Code to attract new developers. This year we are
coordinating 30 mentors, leveraging the effort of developers from open source communities
surrounding NRNB-related tools. Last summer through the GSoC program we received over 60
26. student applications. From these we selected 16 students to mentor on Cytoscape and NRNBrelated projects. All 16 projects passed and completed the summer successfully! Google paid
$5,000 per student, making their investment $80,000 in NRNB for 3 months of work.
Inspired by this very successful model for recruiting new code contributors, we designed and
launched NRNB Academy last year. Through NRNB Academy, we offer anybody the
opportunity to work with our open source development team on network biology related tools
and resources. The program offers a framework for training by providing project ideas and by
pairing participants with mentors. It is completely volunteer-based and offers participants flexible
project terms. Since its launch in January 2011, we have had 14 requests from participants,
and we currently have 4 students enrolled. The first graduate completed their project in
September 2012.
In addition to ongoing student projects, the program has also resulted in one collaboration and
continues to be a source for project ideas and mentors for our GSoC effort. Based on our
experience so far, this program is not only effective in producing useful tools and resources, but
it also serves as a mechanism to increase long-term development collaborations. Our first
graduating student continues to be involved as a contributor, and two of the ongoing students
are involved in longer-term ongoing projects as well.
27. Annual Progress Report - Research Highlights 2013
National Resource for Network Biology
P41 GM103504
05/01/2012 - 04/30/2013
Contents
●
●
●
Network Approach to Building Gene Ontologies
First Release of Cytoscape 3.0 and the Cytoscape App Store
NRNB Google Summer of Code Program Reaches New Levels
Network Approach to Building Gene Ontologies
Ontologies are of key importance to many domains of biological research. The Gene Ontology
(GO), in particular, has been instrumental in unifying knowledge about biological processes,
cellular components, and molecular functions through a hierarchy of concepts and their
interrelationships. However, given only partial biological knowledge and inconsistency in how
this knowledge is curated, it has been difficult to construct, extend and validate GO in an
unbiased manner. We have recently showed that the existing collection of high-throughput
network maps, as are now becoming available, can be analyzed to automatically assemble an
ontology of gene function that rivals manually curated efforts [1]. Our systematic computational
approach combines evidence from physical, genetic and transcriptional networks to produce an
ontology comprised of 4,123 biological concepts and 5,766 hierarchical concept relations. Using
a new ontology alignment procedure, we found that the network-based ontology captures the
majority of known cellular components and identifies approximately 600 new cellular
components and component relations – many of which we were able to validate either
experimentally or bioinformatically. By working closely with the GO curators, we were able to
incorporate selected new components and relations into the Gene Ontology, thus providing
proof-of-principle for how to systematically update and revise the GO structure based on largescale data
1. Dutkowski, J., Kramer, M., Surma, M.A., Balakrishnan, R., Cherry, J.M., Krogan, N.J., and Ideker, T., A
gene ontology inferred from molecular networks. Nat Biotechnol, 2013. 31(1): p. 38-45.
First Release of Cytoscape 3.0 and the Cytoscape App Store
The overall mission of Cytoscape is to be a freely available worldwide asset supporting network
analysis and visualization for systems biology science. Cytoscape Version 3.0 (v3.0) was
released for unrestricted public use on February 1, 2013. It represents an evolution of v2.x
resulting from a two-year collaboration of a multinational, multi-institution team of programmers
and biologists. The major focus of v3.0 is the modularization and rationalization of code to solve
stability issues in v2.x encountered as multiple developers pursued multiple agendas. Version
3.0 addresses these issues by adopting modular coding practices promoted by the OSGi
28. architectural framework. This enables both the Cytoscape core and externally developed apps
(formerly called plugins) to evolve independently without compromising unrelated functionality.
Since 2012, weekly visits (outside of holidays) have increased. The Cytoscape v3.0 web page
was first put up in October 2012. The trends since the February, 2013 release are too new to
yield conclusions, though it seems that visits have measurably increased. Visits to the
Cytoscape download page have remained somewhat constant over time, though seem to have
increased since v3.0’s February 2013 release.
To help address the needs of users, we launched the Cytoscape App Store
(http://apps.cytoscape.org) to coincide with the release of Cytoscape 3.0, a major rearchitecturing of Cytoscape for improved stability, performance, and versatility. The overarching
goals of the Cytoscape App Store are to highlight the important features apps add to Cytoscape,
to enable researchers to find apps they need, and for developers to promote their apps. For
each Cytoscape 3.0 app, the App Store supports unique features like one-click install and
comprehensive download statistics. The App Store opened for business on June 1, 2012. Since
then, it has received over 33,000 visits from users worldwide. Except for during the holiday
season, the traffic to the App Store has consistently grown. By March, 2013, weekly visitors
numbered between 1,100 and 1,300. Through March, 2013, a total of 33,596 visits were
received.
The App Store is already playing a broader role in the Cytoscape community than just a place
for browsing and submitting apps. For instance, we held a competition for the best Cytoscape
3.0 apps in December 2012. The first prize was shared by ClueGO, which visualizes the
relationship between gene ontology terms; and DynNetwork, which visualizes networks with
time-based movement. We plan to host more competitions in the future to encourage Cytoscape
3.0 app development. Apps and the app developer community play a critical role in success of
Cytoscape, ensuring its continued relevance and reach as the field of network biology evolves.
The new Cytoscape App Store aims to increase the visibility and accessibility of apps, providing
support to both Cytoscape users and app developers. We anticipate that traffic will continue to
increase as apps–and the App Store–become more prominent in the Cytoscape community.
NRNB Google Summer of Code Program Reaches New Levels
Last summer through the Google Summer of Code (GSoC) program we received over 60
student applications. From these we selected 16 students to mentor on Cytoscape and NRNBrelated projects. All 16 projects passed and completed the summer successfully! This is almost
double the number of students we mentor through GSoC in a typical year and puts NRNB
in the top 10 supported organizations out of 180 open source orgs accepted into the
Googel program. Google paid $5,000 per student, making their investment $80,000 in NRNB
for 3 months of work.
Inspired by this very successful model for recruiting new code contributors, we designed and
launched NRNB Academy last year. Through NRNB Academy, we offer anybody the
opportunity to work with our open source development team on network biology related tools
and resources. The program offers a framework for training by providing project ideas and by
pairing participants with mentors. It is completely volunteer-based and offers participants flexible
29. project terms. Since its launch in January 2011, we have had 14 requests from participants,
and we currently have 4 students enrolled. The first graduate completed their project in
September 2012.
In addition to ongoing student projects, the program has also resulted in one collaboration and
continues to be a source for project ideas and mentors for our GSoC effort. Based on our
experience so far, this program is not only effective in producing useful tools and resources, but
it also serves as a mechanism to increase long-term development collaborations.
30. Summary
Continued advances in high-throughput experimental technologies release enormous amounts
of interaction data into the public domain. Analysis of these interactions – and the networks they
form – relies in large part on robust bioinformatics technology. The mission of the NRNB
(nrnb.org) is to develop and support a suite of bioinformatics tools that broadly enable the study
of network biology. In our third year as a resource, we have significantly advanced our goals
through basic research, collaboration, dissemination of software tools, and community support.
Here, we describe our progress in research, both basic and collaborative. This progress
includes the use of network modules for patient diagnostics; tools that use ontologies to enable
new network analyses and visualizations; tools that generate ontologies from networks; novel
investigations at the interface of social networks and health; and major new releases of our
Cytoscape platform and App Store.
Each progress report below specifies the associated personnel and FTEs funded by the NRNB
grant. In terms of our own research, NRNB enables a stable effort from each of the resource
member sites, ranging from 0.20 to 1.08 FTEs. Many of these TRD projects leverage effort from
other grants and funding mechanisms as well in order to maximize the return on investment.
Nevertheless, without NRNB support, these projects would be significantly diminished, if not
discontinued, and would lack the cohesion and synergy provided by a network biology resource
(see reports #1-7 below).
In terms of the services, training and dissemination, the impact of the NRNB resource is clear.
Specifically, the extra effort needed to drive our mailing list response rate to over 90% is due to
this resource (see Administrative Information report); the Open Tutorials system for collecting,
maintaining and serving tutorial materials; the administration of NRNB’s participation in Google
Summer of Code and our own NRNB Academy (see report #9 below); the organization of the
annual Network Biology SIG and Cytoscape Workshops; the new Cytoscape App Store, which
has catalyzed Cytoscape user and developer communities (see report #10 below). These efforts
are maintained by the 0.5 FTE executive director and 0.25 FTE communications coordinator
roles defined and funded by NRNB.
And finally, NRNB has wide-ranging impact on biomedical research, both nationally and
internationally through its collaboration projects. NRNB member sites were collectively
maintaining an estimated two-dozen collaborations prior to the formation of this Resource.
During the first year, we established close to 40. And for the past two years, NRNB is now
maintaining 80-100 collaboration projects. These project range from the application of
Cytoscape as a research tool for network analysis and visualization, to the development of
Cytoscape plugins for custom data types and analyses, to the development and application of
other network and pathways tools and resources for network biology (see report #8 below). This
activity is a direct result of NRNB roles for executive director, communications coordinator and
collaboration coordinator (0.63 FTE).
We’ve come a long way in just three years, and NRNB is still maturing. With continued support,
we are committed to maintaining and growing these efforts as a Resource for the network
biology community.
31. Contents
I. Technology Research and Development: Progress and Applications
References and figures are provided for each project and numbered independently. This year,
per the direction of our EAC, we are using a 4-Stage model to provide a common context in
describing the wide variety of technologies being developed in both our TRD and Collaboration
projects. You will see references to "(Stage 2)", for example. The 4-Stage model is described
and illustrated at the beginning of the next section (II. Collaboration, Table 1.).
1.
2.
3.
4.
5.
A Gene Ontology Extracted from Molecular Networks (Ideker)
Network Analysis Tools for Cancer Genomics (Sander)
Network Analysis Methods for Inferring Causality in Signaling Networks (Sander)
Using Cytoscape for Social Network Research (Fowler)
Cytoscape 3.0 and CytoscapeWeb for the Visualization and Representation of
Biological Networks (Bader)
6. Analyzing Complex Networks Using Ontologies and Cytoscape 3.0 (Pico)
7. The CYNI Modular Network Inference Framework (Schwikowski)
II. Collaboration and Service Projects: Progress
In addition to the direct impact of our TRD projects on our research, NRNB also impacts new
science through our many CSPs. A description for each CSP is provided in the bulk of the
report. Here, we summarize the scope of our collaborations and provide a new 4-Stage model
and illustration to convey the range of our efforts as well as progress from year-to-year. Major
service projects are also described in this section.
8. Collaboration Landscape
9. Google Summer of Code and NRNB Academy
III. Progress on Supplemental Award, 2011-2013
We were awarded a two-year supplemental grant to work on the Cytoscape App Store. This is a
progress report on the second year.
10. The Cytoscape App Store (Pico, Bader)
Appendix A. The 2012 NRNB Network
A full-page view of this year’s network representation of NRNB.
32. I. Technology Research and Development: Progress and Applications
References and figures are provided for each project and numbered independently. This year,
per the direction of our EAC, we are using a 4-Stage model to provide a common context in
describing the wide variety of technologies being developed in both our TRD and Collaboration
projects. You will see references to "(Stage 2)", for example. The 4-Stage model is described
and illustrated at the beginning of the next section (II. Collaboration, Table 1).
1. A Gene Ontology Extracted from Molecular Networks (Ideker, 0.5 FTE: Janusz
Dutkowski)
Ontologies are of key importance to many domains of biological research. The Gene Ontology
(GO), in particular, has been instrumental in unifying knowledge about biological processes,
cellular components, and molecular functions through a hierarchy of concepts and their
interrelationships. However, given only partial biological knowledge and inconsistency in how
this knowledge is curated, it has been difficult to construct, extend and validate GO in an
unbiased manner. We have recently showed that the existing collection of high-throughput
network maps, as are now becoming available, can be analyzed to automatically assemble an
ontology of gene function that rivals manually curated efforts [1]. Our systematic computational
approach (Fig. 1) combines evidence from physical, genetic and transcriptional networks to
produce an ontology comprised of 4,123 biological concepts and 5,766 hierarchical concept
relations (Fig. 2). Using a new ontology alignment procedure (Fig. 1), we found that the networkbased ontology captures the majority of known cellular components and identifies approximately
600 new cellular components and component relations – many of which we were able to
validate either experimentally or bioinformatically. By working closely with the GO curators, we
were able to incorporate selected new components and relations into the Gene Ontology, thus
providing proof-of-principle for how to systematically update and revise the GO structure based
on large-scale data (Stages 1 & 2).
The network-extracted ontology is a new resource for systems and synthetic biology – i.e. a
data-driven catalogue of cellular machinery, from genes, to complexes, to pathways and higherorder processes. It provides a powerful tool for performing multi-scale analysis of biological
networks, including automatically identifying, annotating and visualizing the complete
hierarchical structure. We also show how integrating the ontology with additional highthroughput datasets leads to identification of new components and processes altered in human
disease. Based on our results, we suggest a new role for ontologies in bioinformatics: rather
than merely being used as a gold-standard for performing functional enrichment, ontologies
should serve as evolvable models that are validated, revised, and expanded based on new
genomic data.
Moving forward, it will be interesting to see how the network-extracted ontology can further be
extended. For instance while NeXO represents a rigorous approach to capture ontology terms
and term relations, the ability to systematically annotate the type of relation that occurs between
terms (e.g. “is a”, “part of”, “regulates”) poses a separate and very interesting challenge. An in-
33. depth investigation is needed to assess which network properties are best at separating the
different types of relations, and whether there are additional data sets that might be brought to
bear on this problem (Stage 3). Similarly, while NeXO identifies the majority of known cellular
components, it will be interesting to further investigate what types of network data could be used
to increase the coverage of biological processes and molecular functions. Finally, a key
question is whether enough high-quality data exist to build NeXO ontologies for other species,
particularly human, and, whether it is better to structure a common ontology for all species, as
has been done in GO, or to focus on individual species-specific ontologies.
Figure 1. Automated assembly and alignment of gene ontologies. (A) Probabilistic community
detection within the input networks yields a binary tree in which nodes correspond to ontology terms and
links correspond to parent-child term relations. Unsupported terms are replaced by multi-way joins, and
additional parent-child relations are added based on network data. The resulting ontology is aligned
against the Gene Ontology, in a way that (B) prohibits non-unique mappings and ancestor-descendant
criss-crossing.
34. Figure 2. The NeXO
ontology is shown as a
tree, with nodes indicating
terms and edges indicating hierarchical relations between terms, i.e.
that one term contains
another. Node sizes indicate the number of genes
assigned to a term. Node
colors
represent
the
degree of correspondence to a term in GO as
determined by ontology
alignment, with high-level
alignments labeled. Insets
show the hierarchy identified for the ribosome and
actin cytoskeleton.
References
1. Dutkowski, J., Kramer, M., Surma, M.A., Balakrishnan, R., Cherry, J.M., Krogan, N.J., and Ideker, T., A
gene ontology inferred from molecular networks. Nat Biotechnol, 2013. 31(1): p. 38-45.
2. Network Analysis Tools for Cancer Genomics (Sander, 0.62FTE: Ben Gross)
This project is focused on building network analysis tools for interpreting high-throughput cancer
genomic data sets to identify altered disease networks and enable the identification of networkbased biomarkers in cancer. Our primary focus is building user-friendly, open source tools for
visualizing and analyzing multidimensional cancer genomic data sets (including copy number,
mutation, and mRNA expression) in the context of known biological pathways and interaction
networks, and making these tools broadly available to clinical, experimental and computational
investigators within the cancer research community. Providing such tools to the cancer research
community is critical, as numerous large-scale projects, including the Cancer Genome Atlas
(TCGA) project and the International Cancer Genome Consortium (ICGC), are profiling dozens
of cancer types and subtypes. Identifying altered pathways and networks within each of these
cancer types remains a critical and open challenge.
During our first several years of NRNB funding, we completed a prototype project for displaying
multi-dimensional cancer genomic data in the context of molecular interaction networks. We
35. chose to implement the prototype in CytoscapeWeb [1], as CytoscapeWeb does not require any
additional software installation or require Java Web Start. It therefore significantly lowers the
barriers for usage, particularly for biologists and clinical researchers ----- two of our main target
user groups. We transitioned our tools from prototype to production mode (Stage 3), and have
made our software available to the entire cancer research community. Cancer researchers are
now using these tools to perform network analysis on up to 20 different cancer types,
including TCGA-funded projects, such as glioblastoma multiforme (GBM) [2] and serous ovarian
cancer [3] (Stage 4).
The cBioPortal for Cancer Genomics code base has recently reached a stable state where it
is now being considered as a general framework to build our other NRNB-related tools on. Our
recently finalized drug-target data support in the context of cBioPortal’s network analysis is one
such example. During the past year, we improved the network analysis capabilities of the
cBioPortal by providing query and visualization of aggregated drug data from multiple
resources. With this new feature, the portal currently contains gene-centric drug-target
information from the following resources: DrugBank [8], KEGG Drug [9], NCI Cancer Drugs
(http://www.cancer.gov/cancertopics/druginfo/alphalist), and Rask-Andersen et al. [10]. Within
the network analysis view, drugs are hidden by default, but can be added to the network via the
Genes & Drugs menu on the right side of the screen. Users now have the option of displaying
FDA-approved drugs, cancer drugs defined by NCI Cancer Drugs, or all drugs targeting the
query genes. For example, when the user queries for the gene EGFR in the portal, we not only
show the network context of this gene, but also provide information about the drugs targeting
the product of this gene: gefitinib and erlotinib are tyrosine kinase inhibitors that target the
catalytic domain of EGFR, and cetuximab and trastuzumab are monoclonal antibodies that
target the extracellular domain of EGFR and ERBB2, respectively (Fig. 1) [11].
36. Figure 1: Improved Network tab: Network analysis of epidermal growth factor receptor networks in
serous ovarian cancer. (A) Network view of the EGFR and ERBB2 neighborhood in serous ovarian
cancer (TCGA data set) rendered by Cytoscape Web. EGFR and ERBB2 are query genes (thick border),
and nearest neighbor genes are color coded by their alteration frequency in ovarian cancer. One can
display drugs that target EGFR or ERBB2 (hexagons, orange if FDA approved), as well as details about
genomic alterations and links to external resources (lower left panel, example MYC). (B) The portal
overlays multidimensional genomic data (copy number, mutation, and mRNA expression) onto all nodes
in the network. (C) Edges can represent different interaction types (color-coded, such as “reacts with”).
(D) Options for filtering, cropping and searching the network of interest.
Our new drug-target feature is now available as part of the open-access cBioPortal and is
helping cancer researchers in exploring the therapy options within the network context of genes
of interest (Stage 4).
Outreach Plans
Since its launch in mid-2010, the cBioPortal has been extensively used by cancer researchers
around the globe, particularly by The Cancer Genome Atlas (TCGA) network. The portal
currently attracts more than 1,500 unique visitors per week. In order to help researchers use
cBioPortal in their studies, we are actively communicating with various communities, such as
the TCGA network and publicizing the tool through different channels.
During the last year, we have adapted and are currently maintaining an e-mail list for users who
have questions regarding the use of the cBioPortal. This e-mail list and the questions answered
by
our
group
are
publicly
available
at
our
Google
Groups
page
(http://groups.google.com/group/cbioportal/). Furthermore we have recently completed a
manuscript that explains the use cases of cBioPortal and its network analysis feature in details
37. in order to encourage wider adaptation. We believe this publication (Science Signaling) will help
researchers interested in Cancer Research to use the portal in a more efficient way.
We have also participated in the last year’s Google Summer of Code (GSoC) Program for two
separate projects under the NRNB organization. The first project, a Cytoscape 3.0 Application to
facilitate downloading cancer genomics data through the cBioPortal Web API services, was
successfully lead by Dazhi Jiao under the advisement of two members from our group. This
Cytoscape 3.0 application allows users to download data from cBioPortal, visualize it in the
network context either in an overall or sample-specific manner, and analyze it with the help of
additional Cytoscape 3.0 applications (see Figure 2). The source code for this project is freely
available at our Google Code project web site (http://bit.ly/cbioportal). The software
implementation for this project is currently being finalized (Stage 3) and we are planning to
distribute this application through Cytoscape’s App Store interface in the next year (Stage 4).
Figure 2: A screenshot of the Mondrian application, an open-source project conducted as part of the
Google Summer of Code 2012 project. The image shows how genomics data, downloaded from the
cBioPortal through this application, is being overlaid onto the user’s network of interest. Once the data is
loaded from the cancer studies of interest through the cBioPortal’s Web Api, users have the option to
explore multi-dimensional cancer-related data within Cytoscape framework in a fashion that is similar to
cBioPortal’s network analysis feature.
Our second GSoC project was lead by the summer student, Istemi Bahceci under the coadvisement of one member of our group in conjunction with our NRNB-collaborator Ugur
Dogrusoz at Bilkent University. The aim of this project was to extend CytoscapeWeb to support
the Systems Biology Graphical Notation (SBGN) for more detailed biological pathway
visualization. This project was completed over the last summer and we are currently
38. integrating it into the cBioPortal’s to provide better network analysis options for users (Stage 4,
please see the following section).
New Driving Biological Projects
In the next year, we are anticipating improving the network analysis feature in two ways: 1)
detailed visualization of the pathways and reactions in the network view; 2) inference of
indirect drug targets, for potentially interesting therapy options, by using genomic alteration
and drug-target data.
Currently, interaction types that are shown in the network analysis view are derived from the
BioPAX to SIF inference rules [7]. For example: In Same Component indicates that Genes A
and B are involved in the same biological component, such as a complex; State Change
indicates that Gene A causes a state change, such as a phosphorylation change within Gene B.
This reduction from BioPAX to SIF was necessary as the Cytoscape Web framework, by then,
was not supporting visualization of more complex elements, such as compartments. With the
technology being developed as part of the CSP-100 project (Gary Bader), it recently become
feasible to visualize biological networks in a more detailed way, therefore enabling the use of
Systems Biology Graphical Notation (SBGN) for better representation of BioPAX. As part of our
NRNB collaboration with Ugur Dogrusoz (Bilkent University, Turkey), we are aiming to adopt
SBGN-complaint views to visualize multi-dimensional cancer genomics data with the network
context (see Figure 3). This project has recently been implemented as a proof-of-concept
prototype and is now being integrated into cBioPortal (Stage 3 -> 4). When complete, this new
feature will allow better presentation of proteomics data (e.g. Reverse Phase Protein Array data
provided as part of the TCGA network) by allowing users to optionally switch from a genecentric to protein-centric view.
Figure 3: Proposed additions to the current simple network view. On the left is the Simple Interaction
derived from BioPAX; on the right is an example visualization of a BioPAX network obtained from
Pathway Commons. The latter is utilizing the new visualization capabilities, Systems Biology Graphical
Notation (SBGN), of the CytoscapeWeb project. The SBGN view provides a more detailed representation
39. of the pathway and also provides protein-centric view with Proteomics data mapped to specific proteins or
phospho-proteins.
In the next year, we are also planning to utilize genomic alteration and pathway data to infer
clinically relevant uses of drug-target data. For this, we intend to use down- and up-stream
relationships between genes to suggest drugs of possible interest that can indirectly target a
particular genomic alteration event in cancer samples (see Figure 4). One historical example
for such cases is the use of AKT inhibitors in patients who bear a homozygous PTEN deletion.
Without the gene PTEN and its product, Akt proteins, which are down-stream of PTEN, cannot
be suppressed, and therefore are found to be upregulated in cancer samples that have the
homozygous PTEN deletion. In the presence of an AKT inhibitor, this up-regulation effect can
be counteracted. Another similar example of this concept is the use of CDK4/6 inhibitors when
CDKN2A is either mutated or homozygously deleted in cancer cells. Pathway resources, such
as Pathway Commons, already provide this type of relationships between genes; and we plan to
extract this information in a systematic way and combine it with the drug-target data in order to
infer such therapy options in an automatic manner within the cBioPortal framework. This method
and the prototype are currently under development (Stage 2).
Figure 4: Conceptual framework for inferring novel and drug-based therapy options based on specific
genomic alteration with the use of pathway context -- e.g. use of AKT inhibitors when PTEN is altered in
the tumor.
3. Network Analysis Methods for Inferring Causality in Signaling Networks
(Sander, 0.62FTE: Ben Gross)
The goal of our second TRD project is to develop network analysis tools that algorithmically
infer causality within signaling networks and make these tools available. High-throughput
screens conducted with libraries of small molecules or inhibitory RNAs have the ability to
identify compounds that induce tumor suppressive responses in cancer cells [12]. While the
effects of such perturbations can be easily linked to transcriptional changes, identifying the
causal mechanism is a main challenge. In collaboration with Somwar and colleagues [13], we
40. used a computational approach to predict the target of a small molecule inducing reduced
growth in lung adenocarcinoma cell lines. Interestingly, experimental follow up confirmed the
prediction.
Building on this concept, we have been working on computational approaches to model causal
signaling cascades inducing observed transcriptional changes within perturbed cancer cell
lines. We have been exploring the use of optimization algorithms adapted from statistical
physics to identify the minimal set of interactions able to connect genes that are differentially
expressed after a perturbation, with candidate targets of the same perturbation (Stage 2). This
initial approach relied on an algorithm that solves the Steiner-tree problem. Given a set of
“terminal” nodes, the Steiner-tree is defined as the tree of minimum weight connecting these
terminals, allowing the inclusion of additional nodes. Differentially expressed genes after a
perturbation and/or candidate targets of the same perturbation can be used as terminals. Our
prediction was that the resulting Steiner-tree could therefore contain both gene interactions able
to explain the observed transcriptional changes and the putative target of the perturbation.
Within this past year, we determined that this approach does not work as well as expected, and
are now in the process of exploring a new algorithmic framework that combines Gaussian
graphical models with maximum entropy methods.
New Driving Biological Projects
A new biological driver for deriving causality networks is inferring causal relationships within
data types and between data types, such as copy number changes and cancer genomics. For
example, we would like to investigate the relationship between mutations in the TP53 tumor
repressor and the complex copy number profile in ovarian cancer. Another example is the
exploration of causal relationships between gene mutations. For example, mutations in the
POLE gene lead to a characteristic spectrum of mutations in other proteins. We have
preliminary results and plan to develop a network analysis approach to identify causal
relationships.
We are also considering looking at interactions between microbial subpopulations, starting
with the gut microbiome, where a set of interacting bacterial populations change under
fluctuating constraints provided by the host and nutrient intake. Recent work has shown the
precise composition and evolution of this population is closely coupled to the state of health of
the host. Certain deviations from equilibrium present a significant risk of invasion by pathogenic
bacteria, as seen with some cancer patients receiving bone marrow transplantations [23]. A
more detailed understanding of the relationships between gut microbial subpopulations following
such aggressive treatments in the host could inform therapeutic development leading to
improved outcomes.
Our Related Publications
• Gao J, et al, Integrative Analysis of Complex Cancer Genomics Profiles using the cBioPortal. Science
Signaling Protocol (in Press).
41. • Molinelli* E, Korkut* A, Wang* W, MIller M, Gauthier N, Jing X, Kaushik P, et al. Perturbation Biology:
inferring signaling networks in cellular systems. PLoS Comp Bio (in Review).
• Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature.
2012; 490(7418):61-70.
• Cerami E, et al, The cBio Cancer Genomics Portal: An open platform for exploring multi-dimensional
cancer genomics data. Cancer Discovery. May 2012, 2:401.
• The Cancer Genome Atlas Network, Comprehensive Molecular Characterization of Human Colon and
Rectal Cancer. Nature 2012; 487(7407):330-337.
• The Cancer Genome Atlas Network, Comprehensive genomic characterization of squamous cell lung
cancers. Nature 2012; 489:519-525.
References
1. Lopes CT, Franz M, Kazi F, Donaldson SL, Morris Q, Bader GD: Cytoscape Web: an interactive webbased network browser. Bioinformatics, 26(18):2347-2348.
2. TCGA: Comprehensive genomic characterization defines human glioblastoma genes and core
pathways. Nature 2008, 455(7216):1061--1068.
3. Integrated genomic analyses of ovarian carcinoma. Nature 2011, 474(7353):609-615.
4. Keshava Prasad TS, Goel R, Kandasamy K, Keerthikumar S, Kumar S, Mathivanan S, Telikicherla D,
Raju R, Shafreen B, Venugopal A et al: Human Protein Reference Database--2009 update. Nucleic acids
research 2009, 37(Database issue):D767-772.
5. Matthews L, Gopinath G, Gillespie M, Caudy M, Croft D, de Bono B, Garapati P, Hemish J,
Hermjakob H, Jassal B et al: Reactome knowledgebase of human biological pathways and processes.
Nucleic acids research 2009, 37(Database issue):D619-622.
6. Schaefer CF, Anthony K, Krupa S, Buchoff J, Day M, Hannay T, Buetow KH: PID: the Pathway
Interaction Database. Nucleic acids research 2009, 37(Database issue):D674-679.
7. Cerami EG, Gross BE, Demir E, Rodchenkov I, Babur O, Anwar N, Schultz N, Bader GD, Sander C:
Pathway Commons, a web resource for biological pathway data. Nucleic acids research, 39(Database
issue):D685-690.
8. Knox C, Law V, Jewison T, Liu P, Ly S, Frolkis A, Pon A, Banco K, Mak C, Neveu V et al: DrugBank
3.0: a comprehensive resource for 'omics' research on drugs. Nucleic acids research 2011, 39(Database
issue):D1035-1041.
9. Ogata H, Goto S, Sato K, Fujibuchi W, Bono H, & Kanehisa M (1999). KEGG: Kyoto Encyclopedia of
Genes and Genomes. Nucleic acids research, 27(1), 29–34
10. Rask-Andersen M, Almen MS and Schioth HB: Trends in the exploitation of novel drug targets.
Nature Drug Discovery 2011; 10:579-590.
11. Raymond E., Faivre S, Armand JP: Epidermal growth factor receptor tyrosine kinase as a target for
anticancer therapy. Drugs 2000; 60:41-42.
12. Somwar R, Shum D, Djaballah H, Varmus H: Identification and preliminary characterization of novel
small molecules that inhibit growth of human lung adenocarcinoma cells. Journal of biomolecular
screening 2009, 14(10):1176-1184.
13. Somwar R, Erdjument-Bromage H, Larsson E, Shum D, Lockwood WW, Yang G, Sander C,
Ouerfelli O, Tempst PJ, Djaballah H et al: Superoxide dismutase 1 (SOD1) is a target for a small molecule
identified in a screen for inhibitors of the growth of lung adenocarcinoma cell lines. Proceedings of the
National Academy of Sciences of the United States of America 2011, 108(39):16375-16380.
14. Stratton MR, Campbell PJ, Futreal PA: The cancer genome. Nature 2009, 458(7239):719--724.
15. Hanahan D, Weinberg RA: The hallmarks of cancer. Cell 2000, 100(1):57--70.
16. Hanahan D, Weinberg RA: Hallmarks of cancer: the next generation. Cell 2011, 144(5):646-674.
42. 17. Ciriello G, Cerami E, Sander C, Schultz N: Mutual exclusivity analysis identifies oncogenic network
modules. Genome research 2012, 22(2):398-406.
18. Vaske CJ, Benz SC, Sanborn JZ, Earl D, Szeto C, Zhu J, Haussler D, Stuart JM: Inference of
patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM.
Bioinformatics 2010, 26(12):i237-245.
19. Vandin F, Upfal E, Raphael BJ: Algorithms for detecting significantly mutated pathways in cancer.
Journal of computational biology : a journal of computational molecular cell biology 2011, 18(3):507-522.
20. Turner N, Tutt A, Ashworth A: Hallmarks of 'BRCAness' in sporadic cancers. Nat Rev Cancer 2004,
4(10):814-819.
21. Storrs C: Combing the Cancer Genome. The Scientist 2012, Mar.
22. Taylor BS, Schultz N, Hieronymus H, Gopalan A, Xiao Y, Carver BS, Arora VK, Kaushik P, Cerami
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23. Jenq RR, Ubeda C, Taur Y, Menezes CC, Khanin R, Dudakov JA, Liu C, et al. Regulation of
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2012;209(5):903-911.
4. Using Cytoscape for Social Network Research (Fowler, 0.2FTE: James Fowler)
In addition to the Network Correlation plugin developed in collaboration with Alex Pico's group
last year, we have now also used Cytoscape to study the network of interactions in the Olfactory
system for a manuscript on “Friendship and Natural Selection” (in review) (Stage 1). A theory
paper predicting what we observe here was published last year [1]. The target audience for this
work is other social network scholars and people interested in applying these techniques to
social network data. In our friendship and natural selection paper we show that friends are more
genetically related than strangers, to the tune of about fourth cousins. So any project that takes
into account population structure might also consider structure induced by friendship. And if
there are gene characteristics available in Cytoscape, we could apply the Network Correlation
plugin to see how far in gene-gene interaction networks these characteristics tend to correlate
(Stage 2-4).
In terms of Cytoscape integration with our new work, it would be great to have a database of
natural selection scores available for each gene in human studies, so scholars could easily
visualize what parts of their network are under recent natural selection. I have Pardis Sabeti’s
Composite of Multiple Signals scores for about 3 million SNPs. It would also be nice to have
easily available within Cytoscape tools for translating from SNPs to genes. We will work with the
Cytoscape team to make natural selection data available and to implement methods for its
visualization. This work might relate to the visualization TRDs by Bader and Pico groups within
NRNB.
Social Networks and Health
We originally proposed using trend motifs as a new statistical method to investigate "Social
Networks and Disease". We are no longer working on this because we have come to believe
there are other methods that are more suitable. So we are now at Stage 1 in our work on
"Social Networks and Health", which has already led to a number of publications:
43. • Strully KW, Fowler JH, Murabito J, Benjamin EJ, Levy D, Christakis NA. Aspirin Use and
Cardiovascular Events in Social Networks, Social Science & Medicine 74 (7), 1125–1129 (March 2012)
• O'Malley J, Arbesman S, Steiger DM, Fowler JH, Christakis NA. Egocentric Social Network Structure,
Health, and Pro-Social Behaviors in a National Panel Study of Americans, PLoS ONE 7(5): e36250
(May 2012)
• Christakis NA, Fowler JH. Social Contagion Theory: Examining Dynamic Social Networks and Human
Behavior. Statistics in Medicine 32 (4): 556–577 (February 2013)
• Shakya HB, Christakis NA, Fowler JH. Parental Influence on Substance Use in Adolescent Social
Networks. Archives of Pediatrics & Adolescent Medicine 166 (12): 1132-1139 (December 2012)
• Rudolph AE, Crawford ND, Latkin C, Fowler JH, Fuller CM. Individual and Neighborhood Correlates of
Membership in Drug Using Networks with a Higher Prevalence of HIV in New York City (2006-2009),
Annals of Epidemiology, forthcoming
The target audience for this work includes scholars in public health. I will be teaching a class on
networks and we will use existing tools in Cytoscape there that contribute to Stage 4 (broad
adoption) for this approach. There are also some non-health-related projects that will be
precursors to a new project in which we will match death records to the Facebook data to
ascertain social network correlates of health:
• Jones JJ, Settle JE, Bond RM, Fariss CJ, Marlow C, Fowler JH. Inferring Tie Strength from Online
Directed Behavior. PLoS ONE 8 (2): e52168 (February 2013)
• Jones JJ, Bond RM, Fariss CJ, Settle JE, Kramer ADI, Marlow C, Fowler JH. Yahtzee: An Anonymized
Group Level Matching Procedure. PLoS ONE 8 (2): e55760 (February 2013)
• Bond RM, Fariss CJ, Jones JJ, Kramer ADI, Marlow C, Settle JE, Fowler JH. A 61-Million-Person
Experiment in Social Influence and Political Mobilization. Nature 489: 295–298 (13 September 2012)
This work might be ideally suited for a supplement grant. We would use the Facebook and
death data to predict longevity and health factors that influence it (like MI). Next, we would
develop and disseminate a Facebook App that anyone can download that will give them health
stats based on their data. We could then use Cytoscape to show people their networks and the
health risks of their friends and friends’ friends (Stage 4).
References
1. Fu F, Nowak MA, Christakis NA, Fowler JH. The Evolution of Homophily. Scientific Reports 2: 845
(13 November 2012)
5. Cytoscape 3.0 and CytoscapeWeb for the Visualization and Representation of
Biological Networks (Bader, 0.91FTE: Christian Lopes, Jason Montojo, Igor
Rodchenhov)
Technologies developed with NRNB funds
Our goal is to develop new technologies for visualization and representation of biological
networks. Our grant aims are:
Aim 1. Simplifying network views by hierarchically organizing networks and their modules.