In the three years since the original proposal was submitted, the claims we made about the impending readiness of knowledge-based approaches and natural language processing to address pressing problems of information overload in molecular biology have been resoundingly confirmed, and such methods have become increasingly accepted within the computational bioscience and systems biology communities. We are now well into the era of broad use of semantic representation technology to support biomedical research, and at the cusp of the use of biomedical natural language processing software to create the enormous number of necessary formal representations automatically from biomedical texts. The results of the work during the last funding period have not only contributed innovative and significant new methods, but have helped us identify a set of specific research issues we claim are now the rate-limiting factors in building an extensive, high-quality computational knowledge-base of molecular biology.
The aims of this competitive renewal are to address those factors, making it possible to scale our impressive results on intentionally narrow applications to much larger (and more significant) tasks, specifically: (1) to create an enriched, relationally decomposed set of conceptual frames, hewing closely to multiple, community curated ontologies;(2) develop language processing tools capable of recognizing and populating instances of those conceptual frames, and (3) develop systems for integrating and using diverse knowledge from multiple sources to generate scientific insights, focusing on the analysis of sets of dozens to hundreds of genes produced by diverse high-throughput methodologies. An innovative aspect of this proposal is the creation and application of novel, insight-based extrinsic evaluation techniques for such systems.

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
Research Project (R01)
Project #
5R01LM008111-07
Application #
8117587
Study Section
Special Emphasis Panel (ZLM1-ZH-C (J2))
Program Officer
Ye, Jane
Project Start
2003-12-01
Project End
2013-07-31
Budget Start
2011-08-01
Budget End
2012-07-31
Support Year
7
Fiscal Year
2011
Total Cost
$597,135
Indirect Cost
Name
University of Colorado Denver
Department
Pharmacology
Type
Schools of Medicine
DUNS #
041096314
City
Aurora
State
CO
Country
United States
Zip Code
80045
Boguslav, Mayla; Cohen, K Bretonnel; Baumgartner, William A et al. (2018) Improving precision in concept normalization. Pac Symp Biocomput 23:566-577
Cohen, K Bretonnel; Xia, Jingbo; Zweigenbaum, Pierre et al. (2018) Three Dimensions of Reproducibility in Natural Language Processing. LREC Int Conf Lang Resour Eval 2018:156-165
Callahan, Tiffany J; Baumgartner, William A; Bada, Michael et al. (2018) OWL-NETS: Transforming OWL Representations for Improved Network Inference. Pac Symp Biocomput 23:133-144
Cohen, K Bretonnel; Lanfranchi, Arrick; Choi, Miji Joo-Young et al. (2017) Coreference annotation and resolution in the Colorado Richly Annotated Full Text (CRAFT) corpus of biomedical journal articles. BMC Bioinformatics 18:372
Kao, David P; Stevens, Laura M; Hinterberg, Michael A et al. (2017) Phenotype-Specific Association of Single-Nucleotide Polymorphisms with Heart Failure and Preserved Ejection Fraction: a Genome-Wide Association Analysis of the Cardiovascular Health Study. J Cardiovasc Transl Res 10:285-294
Hunter, Lawrence E (2017) Knowledge-based biomedical Data Science. EPJ Data Sci 1:19-25
Greene, Casey S; Garmire, Lana X; Gilbert, Jack A et al. (2017) Celebrating parasites. Nat Genet 49:483-484
Hooper, Joan E; Feng, Weiguo; Li, Hong et al. (2017) Systems biology of facial development: contributions of ectoderm and mesenchyme. Dev Biol 426:97-114
Oellrich, Anika; Collier, Nigel; Groza, Tudor et al. (2016) The digital revolution in phenotyping. Brief Bioinform 17:819-30
Cohen, K Bretonnel; Fort, Karën; Adda, Gilles et al. (2016) Ethical Issues in Corpus Linguistics And Annotation: Pay Per Hit Does Not Affect Effective Hourly Rate For Linguistic Resource Development On Amazon Mechanical Turk. LREC Int Conf Lang Resour Eval 2016:8-12

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