- James C. Hu
- BioBio / Room 443A
- Undergraduate Education
- B.S. Stanford University (1975)
- Graduate Education
- Ph.D. University of Wisconson (1987)
Microbial Genomics and Annotation
The value of society’s investment in science is strongly dependent on the ability of future scientists to build on the results of previous results. As the pace of scientific productivity has accelerated through genomics and other Big Data technologies, the ability of scientist to master the literature is increasingly dependent on computational tools. One important aspect of making data more reusable is the association of data with annotations that can be used in computer-based data mining and analyses.
My group works on the development and use of biological ontologies, which are sets of standardized controlled vocabularies for annotation. Our current focus is on the Ontology for Microbial Phenotypes, which is being constructed to facilitate the reuse and analysis of data from the awesome power of microbial genetics. We also work with the Gene Ontology Consortium on the annotation of gene functions, an have developed systems for integrating annotation with education in the Community Assessment of Community Annotation with Ontologies (CACAO)
We have also worked on developing systems for building model organism databases for community annotation, including EcoliWiki, which reuses and modifies the open source software built for Wikipedia to provide more specialized scientific data resources.
Siegele, DA, LaBonte, SA, Wu, PI, Chibucos, MC, Nandendla, S, Giglio, MG et al.. Phenotype annotation with the ontology of microbial phenotypes (OMP). J Biomed Semantics. 2019;10 (1):13.
Xia, J, Chiu, LY, Nehring, RB, Bravo Núñez, MA, Mei, Q, Perez, M et al.. Bacteria-to-Human Protein Networks Reveal Origins of Endogenous DNA Damage. Cell. 2019;176 (1-2):127-143.e24.
Giglio, M, Tauber, R, Nadendla, S, Munro, J, Olley, D, Ball, S et al.. ECO, the Evidence & Conclusion Ontology: community standard for evidence information. Nucleic Acids Res. 2019;47 (D1):D1186-D1194.
Chibucos, MC, Siegele, DA, Hu, JC, Giglio, M. The Evidence and Conclusion Ontology (ECO): Supporting GO Annotations. Methods Mol. Biol. 2017;1446 :245-259.
Gaudet, P, Škunca, N, Hu, JC, Dessimoz, C. Primer on the Gene Ontology. Methods Mol. Biol. 2017;1446 :25-37.
Nehring, RB, Gu, F, Lin, HY, Gibson, JL, Blythe, MJ, Wilson, R et al.. An ultra-dense library resource for rapid deconvolution of mutations that cause phenotypes in Escherichia coli. Nucleic Acids Res. 2016;44 (5):e41.
Chibucos, MC, Zweifel, AE, Herrera, JC, Meza, W, Eslamfam, S, Uetz, P et al.. An ontology for microbial phenotypes. BMC Microbiol. 2014;14 :294.
Hu, JC, Sherlock, G, Siegele, DA, Aleksander, SA, Ball, CA, Demeter, J et al.. PortEco: a resource for exploring bacterial biology through high-throughput data and analysis tools. Nucleic Acids Res. 2014;42 (Database issue):D677-84.
Brister, JR, Le Mercier, P, Hu, JC. Microbial virus genome annotation-mustering the troops to fight the sequence onslaught. Virology. 2012;434 (2):175-80.
Renfro, DP, McIntosh, BK, Venkatraman, A, Siegele, DA, Hu, JC. GONUTS: the Gene Ontology Normal Usage Tracking System. Nucleic Acids Res. 2012;40 (Database issue):D1262-9.