Researches genome informatics with a focus on gene ontology.
My research focuses on functional and comparative genome informatics. I work on the development of systems to integrate and interrogate genetic, genomic and phenotypic information. I am one of the leaders of the Gene Ontology (GO) project, and I have been deeply involved with the work of the GO Consortium since its inception. The Gene Ontology project is an international effort to provide controlled structured vocabularies for molecular biology that serve as terminologies, classifications and ontologies to further data integration, analysis and reasoning. My interest in bio-ontologies stems as well from the work I do as a principal investigator with the Mouse Genome Informatics (MGI) project at The Jackson Laboratory. The MGI system is a model organism community database resource that provides integrated information about the genetics, genomics and phenotypes of the laboratory mouse. My current research projects combine bio-ontologies and database knowledge systems to represent disease processes with the objective of discovering molecular elements that contribute to particular pathologies such as respiratory diseases.
Widespread use of the GO system for functional annotation of genomes enables comparative analysis of genome-size data sets. Understanding and supporting the GO annotation process and bringing new groups into the GO community is essential to the continued development of a broad, integrated network of biological information that can be transparently shared to enable and advance knowledge discovery. The GO Consortium group now consists of 19 model organism databases and genome-annotation groups who work cooperatively to construct the GO bio-ontologies, to provide functional annotations for a wide variety of organisms, and to support a GO information resource. GO participants located at The Jackson Laboratory lead ontology development projects, develop new software applications for the GO project, and provide GO annotations for mouse gene products. Other core groups of the GO project include an ontology development group based at the European Bioinformatics Institute in the United Kingdom, a software and resource development group based at Lawrence Berkeley National Laboratory, and a production database group based at Stanford University.
MGI supports scientific research that uses the laboratory mouse as a model for the study of human biology and disease. MGI data are curated both from the biomedical literature and from co-curated data loads from other major bioinformatics resources. My research group is responsible for the functional and comparative annotation of mouse genes in the MGI resource. This work includes defining the mouse gene set (in co-curation with other informatics resource providers), indexing the biomedical literature for functional annotation, providing official gene nomenclature along with a robust set of synonyms, and extending the representation of relationships between mouse, human and rat genes and genomes. We work closely with the MGI Sequences and Sequence Maps group to resolve sequence-based inconsistencies in the representations of the mouse genome and the sequence and mapping data integrated in MGI and between MGI and other informatics resource centers such as the NCBI, Ensembl and the UniProt groups. We also work closely with the MGI Phenotypes group to support the development of standards for the representation of phenotype/genotype data in MGI.
MGI-GO scientific curators are using a combination of algorithmic and manual approaches to update annotations of mouse gene products to the GO vocabularies. Currently, more than 17,500 mouse genes have at least preliminary GO annotations and over 9,700 have annotations based on experimental assays in mouse. We use data-mining and other strategies to semi-automate gene annotation to the GO. The highest quality annotations, however, depend on skilled scientific curators who review published literature for information that provides experimental verification for the GO attributions.