The goal of the proposed research is to develop accurate algorithms for annotating the human genome by combining the rigor of probabilistic modeling with the power of Comparative genomics. The approach will be to use orthologous human and murine genomic sequences within a probabilistic framework that simultaneously models both the structure of genes (eg. exons, introns, untranslated regions, etc.), and the expected conservation in the each of the components. Supporting algorithms that enable the use of draft sequence and whole-genome shotgun sequences are also proposed in order for researchers to immediately take advantage of this expected improvement in gene prediction technology. The research will be conducted by Dr. Ian Korf, under the supervision of Dr. Warren Gish at the Genome Sequencing Center, in the Department of Genetics, and Dr. Michael Brent, in the Department of Computer Science, at Washington University, St. Louis. From his mentors, Dr. Korf, a molecular biologist by training, will learn the techniques of probabilistic modeling and improve his computer programming skills, in order to attain the stated goals of the project, and to lay a foundation for his career as an independent researcher in the field of computational molecular biology.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Career Transition Award (K22)
Project #
5K22HG000064-02
Application #
6499136
Study Section
Ethical, Legal, Social Implications Review Committee (GNOM)
Program Officer
Good, Peter J
Project Start
2001-02-15
Project End
2004-01-31
Budget Start
2002-02-01
Budget End
2004-01-31
Support Year
2
Fiscal Year
2002
Total Cost
$146,062
Indirect Cost
Name
Washington University
Department
Biostatistics & Other Math Sci
Type
Schools of Engineering
DUNS #
062761671
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Rose, Alan B; Elfersi, Tali; Parra, Genis et al. (2008) Promoter-proximal introns in Arabidopsis thaliana are enriched in dispersed signals that elevate gene expression. Plant Cell 20:543-51
Cantarel, Brandi L; Korf, Ian; Robb, Sofia M C et al. (2008) MAKER: an easy-to-use annotation pipeline designed for emerging model organism genomes. Genome Res 18:188-96
Flicek, Paul; Keibler, Evan; Hu, Ping et al. (2003) Leveraging the mouse genome for gene prediction in human: from whole-genome shotgun reads to a global synteny map. Genome Res 13:46-54
Stajich, Jason E; Block, David; Boulez, Kris et al. (2002) The Bioperl toolkit: Perl modules for the life sciences. Genome Res 12:1611-8
Korf, I; Flicek, P; Duan, D et al. (2001) Integrating genomic homology into gene structure prediction. Bioinformatics 17 Suppl 1:S140-8