The document discusses how scientific research papers have a narrative structure similar to fairy tales. It describes how research papers follow a story grammar with an introduction to establish the research space, methods and results sections that follow the "cycle of scientific investigation" through fact, goal, method, result, and implication clauses, and a discussion section. It also discusses how understanding a paper's metadiscourse by representing it as a set of claims and evidence linked together can help with comprehension. However, the paper discussed has been retracted due to figure preparation issues that compromised the accuracy and integrity of the published results.
Presentation of the Semantic Knowledge Graph research paper at the 2016 IEEE 3rd International Conference on Data Science and Advanced Analytics (Montreal, Canada - October 18th, 2016)
Abstract—This paper describes a new kind of knowledge representation and mining system which we are calling the Semantic Knowledge Graph. At its heart, the Semantic Knowledge Graph leverages an inverted index, along with a complementary uninverted index, to represent nodes (terms) and edges (the documents within intersecting postings lists for multiple terms/nodes). This provides a layer of indirection between each pair of nodes and their corresponding edge, enabling edges to materialize dynamically from underlying corpus statistics. As a result, any combination of nodes can have edges to any other nodes materialize and be scored to reveal latent relationships between the nodes. This provides numerous benefits: the knowledge graph can be built automatically from a real-world corpus of data, new nodes - along with their combined edges - can be instantly materialized from any arbitrary combination of preexisting nodes (using set operations), and a full model of the semantic relationships between all entities within a domain can be represented and dynamically traversed using a highly compact representation of the graph. Such a system has widespread applications in areas as diverse as knowledge modeling and reasoning, natural language processing, anomaly detection, data cleansing, semantic search, analytics, data classification, root cause analysis, and recommendations systems. The main contribution of this paper is the introduction of a novel system - the Semantic Knowledge Graph - which is able to dynamically discover and score interesting relationships between any arbitrary combination of entities (words, phrases, or extracted concepts) through dynamically materializing nodes and edges from a compact graphical representation built automatically from a corpus of data representative of a knowledge domain.
Searching on Intent: Knowledge Graphs, Personalization, and Contextual Disamb...Trey Grainger
Search engines frequently miss the mark when it comes to understanding user intent. This talk will walk through some of the key building blocks necessary to turn a search engine into a dynamically-learning "intent engine", able to interpret and search on meaning, not just keywords. We will walk through CareerBuilder's semantic search architecture, including semantic autocomplete, query and document interpretation, probabilistic query parsing, automatic taxonomy discovery, keyword disambiguation, and personalization based upon user context/behavior. We will also see how to leverage an inverted index (Lucene/Solr) as a knowledge graph that can be used as a dynamic ontology to extract phrases, understand and weight the semantic relationships between those phrases and known entities, and expand the query to include those additional conceptual relationships.
As an example, most search engines completely miss the mark at parsing a query like (Senior Java Developer Portland, OR Hadoop). We will show how to dynamically understand that "senior" designates an experience level, that "java developer" is a job title related to "software engineering", that "portland, or" is a city with a specific geographical boundary (as opposed to a keyword followed by a boolean operator), and that "hadoop" is the skill "Apache Hadoop", which is also related to other terms like "hbase", "hive", and "map/reduce". We will discuss how to train the search engine to parse the query into this intended understanding and how to reflect this understanding to the end user to provide an insightful, augmented search experience.
Topics: Semantic Search, Apache Solr, Finite State Transducers, Probabilistic Query Parsing, Bayes Theorem, Augmented Search, Recommendations, Query Disambiguation, NLP, Knowledge Graphs
Presentation of the Semantic Knowledge Graph research paper at the 2016 IEEE 3rd International Conference on Data Science and Advanced Analytics (Montreal, Canada - October 18th, 2016)
Abstract—This paper describes a new kind of knowledge representation and mining system which we are calling the Semantic Knowledge Graph. At its heart, the Semantic Knowledge Graph leverages an inverted index, along with a complementary uninverted index, to represent nodes (terms) and edges (the documents within intersecting postings lists for multiple terms/nodes). This provides a layer of indirection between each pair of nodes and their corresponding edge, enabling edges to materialize dynamically from underlying corpus statistics. As a result, any combination of nodes can have edges to any other nodes materialize and be scored to reveal latent relationships between the nodes. This provides numerous benefits: the knowledge graph can be built automatically from a real-world corpus of data, new nodes - along with their combined edges - can be instantly materialized from any arbitrary combination of preexisting nodes (using set operations), and a full model of the semantic relationships between all entities within a domain can be represented and dynamically traversed using a highly compact representation of the graph. Such a system has widespread applications in areas as diverse as knowledge modeling and reasoning, natural language processing, anomaly detection, data cleansing, semantic search, analytics, data classification, root cause analysis, and recommendations systems. The main contribution of this paper is the introduction of a novel system - the Semantic Knowledge Graph - which is able to dynamically discover and score interesting relationships between any arbitrary combination of entities (words, phrases, or extracted concepts) through dynamically materializing nodes and edges from a compact graphical representation built automatically from a corpus of data representative of a knowledge domain.
Searching on Intent: Knowledge Graphs, Personalization, and Contextual Disamb...Trey Grainger
Search engines frequently miss the mark when it comes to understanding user intent. This talk will walk through some of the key building blocks necessary to turn a search engine into a dynamically-learning "intent engine", able to interpret and search on meaning, not just keywords. We will walk through CareerBuilder's semantic search architecture, including semantic autocomplete, query and document interpretation, probabilistic query parsing, automatic taxonomy discovery, keyword disambiguation, and personalization based upon user context/behavior. We will also see how to leverage an inverted index (Lucene/Solr) as a knowledge graph that can be used as a dynamic ontology to extract phrases, understand and weight the semantic relationships between those phrases and known entities, and expand the query to include those additional conceptual relationships.
As an example, most search engines completely miss the mark at parsing a query like (Senior Java Developer Portland, OR Hadoop). We will show how to dynamically understand that "senior" designates an experience level, that "java developer" is a job title related to "software engineering", that "portland, or" is a city with a specific geographical boundary (as opposed to a keyword followed by a boolean operator), and that "hadoop" is the skill "Apache Hadoop", which is also related to other terms like "hbase", "hive", and "map/reduce". We will discuss how to train the search engine to parse the query into this intended understanding and how to reflect this understanding to the end user to provide an insightful, augmented search experience.
Topics: Semantic Search, Apache Solr, Finite State Transducers, Probabilistic Query Parsing, Bayes Theorem, Augmented Search, Recommendations, Query Disambiguation, NLP, Knowledge Graphs
Zoology Second Year Important Question | Exam Tips and TricksPreethyKs
Zoology Kerala State Syllabus Higher Secondary Plus Two Exam Important Questions and DIscusions. Watch the video for detailed discussions https://www.youtube.com/playlist?list=PL8qkmi2Zm8Y349meFKzVi4-QofB4bpTyc
Zoology Second Year Important Question | Exam Tips and TricksPreethyKs
Zoology Kerala State Syllabus Higher Secondary Plus Two Exam Important Questions and DIscusions. Watch the video for detailed discussions https://www.youtube.com/playlist?list=PL8qkmi2Zm8Y349meFKzVi4-QofB4bpTyc
Talk at the World Science Festival at Columbia, June 2, 2017: session on Big Data and Physics: http://www.worldsciencefestival.com/programs/big-data-future-physics/
Data Repositories: Recommendation, Certification and Models for Cost RecoveryAnita de Waard
Talk at NITRD Workshop "Measuring the Impact of Digital Repositories" February 28 – March 1, 2017 https://www.nitrd.gov/nitrdgroups/index.php?title=DigitalRepositories
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Nutraceutical market, scope and growth: Herbal drug technology
The Narrative Structure of Research Articles, or, Why Science is Like a Fairy Tale
1. The Narrative Structure of Research Articles,
or, Why Science is Like a Fairy Tale
Anita de Waard, VP Research Data Collaborations
Research Data Management Services, Elsevier
3. Discourse Comprehension 101
• Letter < syllable < word < clause < sentence < discourse:
This is how linguistics is structured.
But it is not how we understand text!
4. • Letter < syllable < word < clause < sentence < discourse:
This is how linguistics is structured.
But it is not how we understand text!
Discourse Comprehension 101
5. • Letter < syllable < word < clause < sentence < discourse:
This is how linguistics is structured.
But it is not how we understand text!
Discourse Comprehension 101
6. • Letter < syllable < word < clause < sentence < discourse:
This is how linguistics is structured.
But it is not how we understand text!
Discourse Comprehension 101
7. • Letter < syllable < word < clause < sentence < discourse:
This is how linguistics is structured.
But it is not how we understand text!
Discourse Comprehension 101
8. • Letter < syllable < word < clause < sentence < discourse:
This is how linguistics is structured.
But it is not how we understand text!
Discourse Comprehension 101
9. • Letter < syllable < word < clause < sentence < discourse:
This is how linguistics is structured.
But it is not how we understand text!
• Kintsch and Van Dijk, ‘93: we read a text at three levels:
– surface code: literal text, exact words/syntax
– text base: preserves meaning, but not exact wording
– situation model: ‘microworld’ that the text is about:
constructed inferentially through interaction between the
text and background knowledge
• We use knowledge about text genre to activate a schema:
this allows creation of the text base and situation model
Discourse Comprehension 101
11. The structure of a research paper:
Discussion:
• Statement of principal findings
• Strengths and weaknesses of the study
• Relation to other studies
• Unanswered questions and future research
Introduction: “Create a Research Space”
• Establish a research territory
• Establish a niche
• Occupy the niche
Methods and Results:
“Cycles of Scientific Investigation”
(see below)
12. THORNDYKE, P.W. (1977), Cognitive Structures in Comprehension and Memory of
Narrative Discourse, COGNITIVE PSYCHOLOGY 9, 77- 110 (1977)
A Story Grammar:
13. Story Grammar The Story of Goldilocks and
the Three Bears
Setting Time Once upon a time
Character a little girl named Goldilocks
Location She went for a walk in the forest.
Pretty soon, she came upon a
house.
Theme Goal She knocked and, when no one
answered,
Attempt she walked right in.
Episode Name At the table in the kitchen, there
were three bowls of porridge.
Subgoal Goldilocks was hungry.
Attempt She tasted the porridge from the
first bowl.
Outcome This porridge is too hot! she
exclaimed.
Attempt So, she tasted the porridge from
the second bowl.
Outcome This porridge is too cold, she
said
Attempt So, she tasted the last bowl of
porridge.
Paper
Grammar
The AXH Domain of Ataxin-1 Mediates Neurodegeneration
through Its Interaction with Gfi-1/Senseless Proteins
Background The mechanisms mediating SCA1 pathogenesis are still not fully
understood, but some general principles have emerged.
Objects of
study
the Drosophila Atx-1 homolog (dAtx-1) which lacks a polyQ tract,
Experimental
setup
studied and compared in vivo effects and interactions to those of
the human protein
Research
goal
Gain insight into how Atx-1's function contributes to SCA1
pathogenesis. How these interactions might contribute to the
disease process and how they might cause toxicity in only a
subset of neurons in SCA1 is not fully understood.
Hypothesis Atx-1 may play a role in the regulation of gene expression
Name dAtX-1 and hAtx-1 Induce Similar Phenotypes When
Overexpressed in Files
Subgoal test the function of the AXH domain
Method overexpressed dAtx-1 in flies using the GAL4/UAS system
(Brand and Perrimon, 1993) and compared its effects to those
of hAtx-1.
Results Overexpression of dAtx-1 by Rhodopsin1(Rh1)-GAL4, which
drives expression in the differentiated R1-R6 photoreceptor cells
(Mollereau et al., 2000 and O'Tousa et al., 1985), results in
neurodegeneration in the eye, as does overexpression of hAtx-
1[82Q]. Although at 2 days after eclosion, overexpression of
either Atx-1 does not show obvious morphological changes in
the photoreceptor cells
Data (data not shown),
Results both genotypes show many large holes and loss of cell integrity
Story Grammar For A Science Paper:
16. In defense of the clause
as the unit of thought:
1. Importantly, our results so far indicate that the expression of miR-
372&3 did not reduce the activity of RASV12, as these cells were still
growing faster than normal cells and were tumorigenic, for which RAS
activity is indispensable (Hahn et al, 1999 and Kolfschoten et al, 2005).
2. To shed more light on this aspect, we examined the effect of miR-
372&3 expression on p53 activation in response to oncogenic
stimulation.
3. We used for this experiment BJ/ET cells containing p14ARFkd because,
following RASV12 treatment, in those cells p53 is still activated but
more clearly stabilized than in parental BJ/ET cells (Voorhoeve and
Agami, 2003), resulting in a sensitized system for slight alterations in
p53 in response to RASV12.
4. Figure 4A shows that following RASV12 stimulation, p53 was stabilized
and activated, and its target gene, p21cip1, was induced in all cases,
indicating an intact p53 pathway in these cells.
Regulatory
clause
Fact Goal Method Result Implication
17. Both seminomas and the EC component of
nonseminomas share features with ES cells. To
exclude that the detection of miR-371-3 merely
reflects its expression pattern in ES cells, we tested
by RPA miR-302a-d, another ES cells-specific
miRNA cluster (Suh et al, 2004). In many of the
miR-371-3 expressing seminomas and
nonseminomas, miR-302a-d was undetectable (Figs
S7 and S8), suggesting that miR-371-3 expression is
a selective event during tumorigenesis.
Both seminomas and the EC component of
nonseminomas share features with ES cells.
To exclude that
the detection of miR-371-3 merely reflects its
expression pattern in ES cells,
we tested by RPA miR-302a-d, another ES cells-
specific miRNA cluster (Suh et al, 2004).
In many of the miR-371-3 expressing seminomas
and nonseminomas, miR-302a-d was undetectable
(Figs S7 and S8),
suggesting that
miR-371-3 expression is a selective event during
tumorigenesis.
Fact
Hypothesis
Method
Result
Implication
Goal
Reg-Implication
Conceptual
knowledge
Experimental
Evidence
Clause, realm and tense:
18. Facts in the
eternal present
Endogenous small RNAs (miRNAs) regulate
gene expression by mechanisms conserved
across metazoans.
I sing of golden-throned Hera whom Rhea bare.
Queen of the immortals is she, surpassing all in
beauty: she is the sister and the wife of loud-
thundering Zeus, --the glorious one whom all the
blessed throughout high Olympus reverence and
honor.
Events in the
simple past
Vehicle-treated animals spent equivalent
time investigating a juvenile in the first and
second sessions in experiments conducted in
the NAC and the striatum: T1 values were
122 ± 6 s and 114 ± 5 s.
Now the wooers turned to the dance and to
gladsome song, and made them merry, and waited
till evening should come; and as they made merry
dark evening came upon them.
Events with
embedded
facts
We also generated BJ/ET cells expressing the
RASV12-ERTAM chimera gene, which is only
active when tamoxifen is added (De Vita et al,
2005).
And she took her mighty spear, tipped with sharp
bronze, heavy and huge and strong, wherewith she
vanquishes the ranks of men-of warriors, with
whom she is wroth, she, the daughter of the
mighty sire.
Attribution in
the present
perfect
miRNAs have emerged as important
regulators of development and control
processes such as cell fate determination and
cell death (Abrahante et al., 2003, Brennecke
et al., 2003, Chang et al., 2004, Chen et al.,
2004, Johnston and Hobert, 2003, Lee et al.,
1993]
In this book I have had old stories written down, as
I have heard them told by intelligent people,
concerning chiefs who have held dominion in the
northern countries, and who spoke the Danish
tongue; and also concerning some of their family
branches, according to what has been told me.
Implications
are hedged,
and in the
present tense
These results indicate that although miR-
372&3 confer complete protection to
oncogene-induced senescence in a manner
similar to p53 inactivation, the cellular
response to DNA damage remains intact
Now it is said that ever since then whenever the
camel sees a place where ashes have been
scattered, he wants to get revenge with his enemy
the rat and stomps and rolls in the ashes hoping to
get the rat
Tense use in science and mythology:
19. Summing up:
1. Discourse Comprehension 101:
– We read gobs of text and integrate these with our
knowledge networks
– We understand through schema’s
2. Story grammars and the Cycle of Scientific Investigation
– Papers are like fairytales
– Within Results, Cycles of Scientific Investigation connect
data to claims
– Tense helps identify the realm of the claim (like in
mythology)
3. How can we use this to help scientists read?
20. So how can this understanding
help us help scientists read papers?
• Why do we read?
To learn, i.e.: obtain the knowledge contained within the
text and integrate it with what we already know.
• What do we read?
Things that are ‘interesting’ :
– Pertinent
– Possibly/probably true
– Novel, but in agreement with what I know
• How do we read?
21. human breast cancer
noninvasive MCF7-Ras
antisense oligonucleotides
high-grade malignancy
cell viability
retroviral vector
miR-31
cloned
transiently expressed miRNA sponges
Is it pertinent? -> Possibly…
Is it true? -> ?
Is it new, but in agreement with what I know? -> -?
Represent a paper as
Collections of Noun Phrases?
22. miR-31 PREVENT acquisition of aggressive traits
miR-31 INHIBIT noninvasive MCF7-Ras cells
miR-31 ENHANCE invasion
cell viability AFFECT inhibitor
miR-31 expression DEPRIVE metastatic cells
Is it pertinent? -> Possibly…
Is it true? -> ?
Is it new, but in agreement with what I know? ->?
Represent a paper as Triples
(Two Nouns and a Verb):
23. The preceding observations demonstrated that X expression deprives Y cells of
attributes associated with Z.
We next asked whether X also prevents the acquisition of A traits by B cells.
To do so, we transiently inhibited X in C cells with either D or E.
Both approaches inhibited X function by > 4.5-fold (Figure S7A).
Suppression of X enhanced invasion by 20-fold and motility by 5-fold, but F was
unaffected by either inhibitor (Figure 3A; Figure S7B).
The E sponge reduced X function by 2.5-fold, but did not affect the activity of other
known Js (Figures S8A and S8B).
Collectively, these data indicated that sustained X activity is necessary to prevent the
acquisition of Z traits by both K and untransformed B cells.
Is it pertinent? -> Need content
Is it true? -> Sounds likely! I know this stuff!
Is it new, but in agreement with what I know? -> Need content
Represent a paper’s Metadiscourse:
24. Claim:
• sustained miR-31 activity is necessary to prevent the acquisition of aggressive
traits by both tumor cells and untransformed breast epithelial
Evidence: Method:
• We transiently inhibited miR-31 in noninvasive MCF7-Ras cells with either
antisense oligonucleotides or miRNA sponges.
Evidence: Result:
• Both approaches inhibited miR-31 function by >4.5-fold (Figure S7A).
• Suppression of miR-31 enhanced invasion by 20-fold and motility by 5-fold,
but cell viability was unaffected by either inhibitor (Figure 3A; Figure S7B).
• The miR-31 sponge reduced miR-31 function by 2.5-fold, but did not affect
the activity of other known antimetastatic miRNAs (Figures S8A and S8B).
Is it pertinent? -> Probably
Is it true? -> Sounds likely!
Is it new, but in agreement with what I know? -> Check/know
Represent a Paper as a
Set of Claims and Evidence:
25. Is it pertinent? -> Possibly
Is it true?
Is it new, but in agreement with what I know? -> Need background
-> Probably!
Show who wrote it, and where:
26. So we probably need all of these:
• Surface code provides noun phrases and triples that offer
pointers re. topical relevance
• Text base and and situation model are created through specific
metadiscourse conventions (e.g. refs at the end) that create a
biological reasoning model:
• This can be expressed as a set of claims, linked to evidence, that
can help represent key points in the paper
• Journal name and author’s affiliation help define schema and
provide ‘willingness to be convinced’ socially/interpersonally.
We next asked whether …
To do so, we transiently inhibited…
Suppression of X enhanced invasion …
but F was unaffected …(Figure 3A). …
Collectively, these data indicated that … .
Hypothesis
Goal/Method
Result
Results
Implication
27. But wait: there’s a wolf in the woods!
This article has been retracted: please see Elsevier Policy on Article Withdrawal
(http://www.elsevier.com/locate/withdrawalpolicy). This article has been retracted
at the request of the authors.
Our study reported that miR-31 is a regulator of multiple mRNAs important for
different aspects of breast cancer metastasis. We recently identified concerns with
several figure panels in which original data were compiled from different replicate
experiments in order to assemble the presented figure. The scope of the figure
preparation issues includes compiling data from independent experiments to
present them as one internally controlled experiment, statistical analyses based
on technical replicates that are not reflective of the biological replicates, and
comparisons of selectively chosen data points from multiple experiments. As
many of the published figures are therefore not appropriate or accurate
representations of the original data, we believe that the responsible course of
action is to retract the paper. We apologize for any inconvenience we have caused.
28. In Summary:
1. Discourse Comprehension 101
2. Story grammars and the Cycle of Scientific
Investigation
3. How can we help scientists read?
– Tools that ‘read’ papers and allow easy access to claims
and evidence
– Tools and practices that record data (=evidence)
throughout the practice of creating it
– Tools that help us make sense out of all of this
networked knowledge
– Cultural habits to support these practices.
29. For Change to Occur,
We Need Networks of Collaboration:
Force11:
– Multi-stakeholder, member-driven organisation
– Unites scholars, tool developers, librarians, publishers, funding agencies etc. etc.
– E.g.: RRID initiative just got implemented in Cell: “STAR Methods: Structured,
Transparent, Accessible Reporting.”
National Data Service:
– Multi-stakeholder group, based around supercomputing centres
– Aims to be a ‘connective tissue’ between data creation, curation, storage etc projects.
– Inviting Pilots: two or more partners who have not worked together, interested in
collaborating on a data-centric project to solve a real-world needs
– E.g. Datasearch, Data Linking systems
RDA:
– Coleading Data publishing, linking group
– Colead Cost Recovery group, part of RDA US Sustainability effort
– Active in Chemistry, Earth Science groups, starting IG on Data Search
– SciDataCon, Sept 11-16, Denver, CO
The National
DATA SERVICE
30. Anita de Waard
VP Research Data Collaborations Research Data
Management Services, Elsevier
a.dewaard@elsevier.com
And we all live happily
ever after….
33. Noun Phrases: some progress
• Despite these difficulties, noun phrase recall/precision is
quite high, e.g. I2B22011 [1], [2], others: 90%-98%
• Many tools, see [3] for a list; e.g. GoPubMed:
34. Triples: some issues:
• Contingent on good NP & VP detection
• Hard to parse text! E.g. a commercial tool gave:
insulin maintaining glucose homeostasis
When insulin secretion cannot be increased adequately (type I
diabetes defect) to overcome insulin resistance in maintaining
glucose homeostasis, hyperglycemia and glucose intolerance
ensues.
insulin may be involved glucose homeostasis
Because PANDER is expressed by pancreatic beta-cells and in
response to glucose in a similar way to those of insulin, PANDER
may be involved in glucose homeostasis.
35. Triples: some progress:
Biological Expression Language [4]:
We provide evidence that these miRNAs are potential novel oncogenes participating in the development
of human testicular germ cell tumors by numbing the p53 pathway, thus allowing tumorigenic growth in
the presence of wild-type p53.
Increased abundance of miR-372 decreases activity of TP53
r(MIR:miR-372) -| tscript(p(HUGO:Trp53))
Context: cancer
SET Disease = “Cancer”
Activity of TP53 decreases cell growth
tscript(p(HUGO:Trp53)) -| bp(GO:”Cell Growth”
36. Metadiscourse: why it matters
• Voorhoeve et al., 2006: “These miRNAs neutralize p53- mediated CDK
inhibition, possibly through direct inhibition of the expression of the tumor
suppressor LATS2.”
• Kloosterman and Plasterk, 2006: “In a genetic screen, miR-372 and miR-373
were found to allow proliferation of primary human cells that express
oncogenic RAS and active p53, possibly by inhibiting the tumor suppressor
LATS2 (Voorhoeve et al., 2006).”
• Yabuta et al., 2007: “[On the other hand,] two miRNAs, miRNA-372 and-373,
function as potential novel oncogenes in testicular germ cell tumors by
inhibition of LATS2 expression, which suggests that Lats2 is an important tumo
suppressor (Voorhoeve et al., 2006).”
• Okada et al., 2011: “Two oncogenic miRNAs, miR-372 and miR-373, directly
inhibit the expression of Lats2, thereby allowing tumorigenic growth in the
presence of p53 (Voorhoeve et al., 2006).”
“[Y]ou can transform .. fiction into fact just by adding or
subtracting references”, Bruno Latour [5]
37. Adding Metadiscourse To Triples
Claim ORCA Value
Together, Lats2 and ASPP1 shunt p53 to proapoptotic
promoters and promote the death of polyploid cells [1]. (…)
Value = 3
Source = N
Basis = 0
Further biochemical characterization of hMOBs showed that
only hMOB1A and hMOB1B interact with both LATS1 and LATS2
in vitro and in vivo [39]. (…)
Value = 3
Source = N
Basis = Data
Our findings reveal that miR-373 would be a potential
oncogene and it participates in the carcinogenesis of human
esophageal cancer by suppressing LATS2 expression.
Value = 1 or 2 ?
Source = Author
Basis = Data
Furthermore, we demonstrated that the direct inhibition of
LATS2 protein was mediated by miR-373 and manipulated the
expression of miR-373 to affect esophageal cancer cells growth.
Value = 2 (or 3?)
Source = Author
Basis = Data
38. Claims and Evidence: some issues:
• Data2Semantics [11]: linking clinical guidelines to evidence.
Inconsistency within guideline and guidelines v. evidence:
• Studies have demonstrated inconsistent results regarding the use of such
markers of inflammation as C-reactive protein (CRP), interleukins- 6 (IL-6) and
-8, and procalcitonin (PCT) in neutropenic patients with cancer [55–57].
• [55]: PCT and IL-6 are more reliable markers than CRP for predicting
bacteremia in patients with febrile neutropenia
• [56] In conclusion, daily measurement of PCT or IL-6 could help identify
neutropenic patients with a stable course when the fever lasts >3 d. …,
it would reduce adverse events and treatment costs.
• [57] Our study supports the value of PCT as a reliable tool to predict
clinical outcome in febrile neutropenia.
• Drug Interaction Knowledgebase [12]: how to identify evidence?
• R-citalopram_is_not_substrate_of_cyp2c19:
• At 10uM R- or S-CT, ketoconazole reduced reaction velocity to 55 -60% of
control, quinidine to 80%, and omeprazole to 80-85% of control (Fig. 6).
39. Claims and Evidence: some progress
• Defining ‘salient knowledge components’ in text:
– Argumentative zones, CoreSC can both be found
– Blake, Claim networks (more soon!)
– Claimed Knowledge Updates (Sandor/de Waard, [13]):