Scholarly Communication for Bioinformatics Students

The Changing Face of Scholarly Communication and the Opportunities it Affords the Bioinformatics/Systems Biology Student
Philip E. Bourne
University of California San Diego
pbourne@ucsd.edu
http://www.sdsc.edu/pb
Third UCSD Bioinformatics and Systems Biology Expo – 2/28/2011

Observation 1: Everyone in this Room is Driven by One Thing Above All Else

Observation 2: We Are a Field That Uses/Produces Public On-Line Data Like No Other

Observation 3: We Have Shaped the Way Data Are Shared – We Have Had Very Little Impact on Publications

Perhaps it is Time We Though Less About a Publication as a Reward and More About How it Can be Presented to Maximize its Use

So What Needs to Happen
We need data and knowledge about that data to interoperate i.e. we need new kinds of fast, versatile publications and data archives
We need to be more open with both
We need to think more about the tools that analyze, visualize and annotate data to maximize knowledge discovery
Reward systems need to change
We need scientist management tools
We need to be less fixated on the big data problems
We need to unleash the full power of the Internet
Hard
Easy

One Personal Example of Why This Needs to Happen Now

Josh Sommer – A Remarkable Young ManCo-founder & Executive Director the Chordoma Foundation
http://sagecongress.org/Presentations/Sommer.pdf

Chordoma
A rare form of brain cancer
No known drugs
Treatment – surgical resection followed by intense radiation therapy
http://upload.wikimedia.org/wikipedia/commons/2/2b/Chordoma.JPG

If I have seen further it is only by
standing on the shoulders of giants
Isaac
Isaac Newton
From Josh’s point of view the climb
up just takes too long
> 15 years and > $850M to be
more precise
Adapted: http://sagecongress.org/Presentations/Sommer.pdf

http://fora.tv/2010/04/23/Sage_Commons_Josh_Sommer_Chordoma_Foundation

So We Have Seem What Needs the Change and Why. What about the How?

We Need Data and Knowledge About That Data to Interoperate
The Knowledge and Data Cycle
0. Full text of PLoS papers stored
in a database
4. The composite view has
links to pertinent blocks
of literature text and back to the PDB
User clicks on content
Metadata and webservices to data provide an interactiveview that can be annotated
Selecting features provides a data/knowledge mashup
Analysis leads to new content I can share
4.
1.
3. A composite view of
journal and database
content results
1. A link brings up figures
from the paper
3.
2.
2. Clicking the paper figure retrieves
data from the PDB which is
analyzed
PLoS Comp. Biol. 2005 1(3) e34

We Need Data and Knowledge About That Data to Interoperate – What is Stopping US?
Open Access
Governance – publishers vs. database providers
Reward
Metadata standards for provenance, privacy etc.
Exemplars
….

A Small Example - The World Wide Protein Data Bank
The single worldwide repository for data on the structure of biological macromolecules
Vital for drug discovery and the life sciences
39 years old
Free to all
http://www.wwpdb.org
We need data and knowledge about that data to interoperate

The World Wide Protein Data Bank – The Best Case Scenario
Paper not published unless data are deposited – strong data to literature correspondence
Highly structured data conforming to an extensive ontology
DOI’s assigned to every structure
http://www.wwpdb.org

Example Interoperability: The Database View
www.rcsb.org/pdb/explore/literature.do?structureId=1TIM
BMC Bioinformatics 2010 11:220

Example Interoperability: The Literature Viewhttp://biolit.ucsd.edu
Nucleic Acids Research 2008 36(S2) W385-389

ICTP Trieste, December 10, 2007

Semantic Tagging & Widgets are a Powerful Tool to Integrate Data and Knowledge of that Data, But as Yet Not Used Much
Will Widgets and Semantic Tagging Change Computational Biology?
PLoS Comp. Biol. 6(2) e1000673

Semantic Tagging of Database Content in The Literature or Elsewhere
http://www.rcsb.org/pdb/static.do?p=widgets/widgetShowcase.jsp
PLoS Comp. Biol. 6(2) e1000673
Semantic Tagging

The Publishers are Starting to Do It
From Anita de Waard, Elsevier

This is Literature Post-processingBetter to Get the Authors Involved
Authors are the absolute experts on the content
More effective distribution of labor
Add metadata before the article enters the publishing process

Word 2007 Add-in for authors
Allows authors to add metadata as they write, before they submit the manuscript
Authors are assisted by automated term recognition
OBO ontologies
Database IDs
Metadata are embedded directly into the manuscript document via XML tags, OOXML format
Open
Machine-readable
Open source, Microsoft Public License
http://www.codeplex.com/ucsdbiolit

Challenges
Authors
Carrot IF one or more publishers fast tracked a paper that had semantic markup it might catch on
Publishers
Carrot Competitive advantage

The Promise – A Hypothetical Example
Cardiac Disease
Literature
Immunology Literature
Shared Function

High-throughput Biology Requires High-throughput Knowledge Discovery
Consider an Example from Our Own Work…
Roger Chang Will Give You Another Example

The TB-Drugome
Determine the TB structural proteome
Determine all known drug binding sites from the PDB
Determine which of the sites found in 2 exist in 1
Call the result the TB-drugome
Kinnings et al 2010 PLoS Comp Biol6(11): e1000976
High-throughput Data Requires High-throughput Knowledge

1. Determine the TB Structural Proteome
TB proteome
homology models
solved structures
2, 266
3, 996
284
1, 446
High quality homology models from ModBase (http://modbase.compbio.ucsf.edu) increase structural coverage from 7.1% to 43.3%
Kinnings et al 2010 PLoS Comp Biol 6(11): e1000976

2. Determine all Known Drug Binding Sites in the PDB
Searched the PDB for protein crystal structures bound with FDA-approved drugs
268 drugs bound in a total of 931 binding sites
No. of drugs
Acarbose
Darunavir
Alitretinoin
Conjugated estrogens
Chenodiol
Methotrexate
No. of drug binding sites

Map 2 onto 1 – The TB-Drugome
http://funsite.sdsc.edu/drugome/TB/
Similarities between the binding sites of M.tb proteins (blue),
and binding sites containing approved drugs (red).

From a Drug Repositioning Perspective
Similarities between drug binding sites and TB proteins are found for 61/268 drugs
41 of these drugs could potentially inhibit more than one TB protein
conjugated estrogens &
methotrexate
No. of drugs
chenodiol
levothyroxine
testosterone
raloxifene
alitretinoin
ritonavir
No. of potential TB targets

Top 5 Most Highly Connected Drugs

We Need Better Ways to Associate Data and Knowledge and its More than Just Text Mining of PubMed Abstracts – Its About Changing the System
Our Future is in Your Hands!

Acknowledgements
BioLit Team
Lynn Fink
Parker Williams
Marco Martinez
RahulChandran
Greg Quinn
Microsoft Scholarly Communications
Pablo Fernicola
Lee Dirks
SavasParastitidas
Alex Wade
Tony Hey
RCSB PDB team
Andreas Prilc
DimitrisDimitropoulos
TB Drugome Team
Lei Xie
Sarah Kinnings
Li Xie
http://funsite.sdsc.edu/drugome/TB/
http://biolit.ucsd.edu
http//www.pdb.org
http://www.codeplex.com/ucsdbiolit

pbourne@ucsd.edu
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Scholarly Communication for Bioinformatics Students

by Philip Bourne on Feb 28, 2011

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Scholarly Communication for Bioinformatics Students — Presentation Transcript