Gene Annotation Using Evidence Integration and Propagation. Start date: Sept. 12, 2005. Expires: Aug. 31, 2008. Amount: $350,000. Principal investigator: Simon Kasif. Institution: Boston University, Charles River Campus. NIH institute: NHGRI.
Funds development of a "systematic methodology" for integration of multiple sources of gene function evidence based on probabilistic inference methods. The grantees will use a functional linkage graph representation of evidence, together with controlled vocabularies of function descriptors such as the GO ontology, and develop methods to integrate and propagate function classifications through evidence networks to generate predicted functions for proteins of unknown function, with probabilities to indicate the confidence of the prediction.
Database for Glycan Structures. Start date: Sept. 15, 2005. Expires: March 11, 2006. Amount: $158,812. Principal investigator: Ram Sasisekharan. Institution: Parivid. NIH institute: NIGMS.
Funds development of a glycan database that includes data from the NIGMS-funded Consortium for Functional Glycomics, as well as from other resources.
Developing Software for Protein-Based Gene Finding. Start date: Sept. 16, 2005. Expires: June 30, 2008. Amount: $400,000. Principal investigator: Morgan Giddings. Institution: University of North Carolina, Chapel Hill. NIH institute: NHGRI.
Supports development of gene-finding software that will use mass spectrometry measurements of proteins to reveal the location and structure of the genes encoding those proteins within the genome. The investigators will modify and combine the TWINSCAN and GFS programs, developed for genomic and proteomic analysis, respectively.
A General Bayesian Polymorphism Discovery Tool. Start date: Sept. 16, 2005. Expires: July 31, 2010. Amount: $369,355. Principal investigator: Gabor Marth. Institution: Boston College. NIH institute: NHGRI.
Proposal to build on the existing software, POLYBAYES, to develop an improved general polymorphism discovery tool. The software will organize fragmentary sequences by layering them upon the genome reference sequence; discard paralogous sequences from similar, duplicated genome regions; and use base quality values in a rigorous, Bayesian scheme to compare sequences of arbitrary quality standards.
General Data-Analysis Tools to Relate Chemical Diversity. Start date: Sept. 23, 2005. Expires: July 31, 2007. Amount: $388,977. Principal investigator: Paul Clemons. Institution: Massachusetts Institute of Technology. NIH institute: NHGRI.
Supports development of a software environment for quantitative chemical biology research. One goal of this environment will be to aid chemists in synthetic planning, and biologists in interpreting screening results and selecting molecules. Another goal will be to integrate new tools for chemistry and chemical biology with existing analysis tools for genomic medicine.
Chemical Informatics Cyberinfrastructure. Start date: Sept. 23, 2005. Expires: July 31, 2007. Amount: $363,300. Principal investigator: Geoffrey Fox. Institution: Indiana University, Bloomington. NIH institute: NHGRI.
Funds development of an integrated Chemical Informatics Cyberinfrastructure that will "make the best use of high-throughput screening data from public databases, especially that flowing into PubChem," according to the grant's abstract.
MACE — Michigan Alliance for Cheminformatic Exploration. Start date: Sept. 23, 2005. Expires: July 31, 2007. Amount: $306,000. Principal investigator: Kerby Shedden. Institution: University of Michigan, Ann Arbor. NIH institute: NHGRI.
Funds the Michigan Alliance for Cheminformatic Exploration (MACE), which "aims to play a leading role in developing tools and analysis methods for discovering biologically significant and therapeutically relevant compounds in the National Library of Medicine's PubChem database," according to the grant abstract. As an NIH-designated Exploratory Center for Cheminformatics Research (ECCR), MACE will "deliver an integrated analysis toolset constructed from components that have already been developed in the co-investigators' laboratories."
Comparative and Web-Enabled Virtual Screening. Start date: Sept. 23, 2005. Expires: July 31, 2007. Amount: $385,126. Principal investigator: Jacqueline Hughes-Oliver. Institution: North Carolina State University, Raleigh. NIH institute: NHGRI.
Project to develop computational algorithms and software to gain theoretical and empirical insights in the use of chemical diversity for determining quantitative structure-activity relationships (QSARs).
ASTRAL: Foundation for Structure and Evolution Studies. Start date: Sept. 23, 2005. Expires: Aug. 31, 2009. Amount: $228,000. Principal investigator: Steven Brenner. Institution: University of California, Berkeley. NIH institute: NIGMS.
Supports continued development of the ASTRAL collection of software and database for the study of protein structure and evolution. Aims include automating the software used to build ASTRAL, documenting all tools used to build ASTRAL, and making them available as open source, producing new releases of ASTRAL, extending its utility to more of the biomedical research community, and developing resources to facilitate extension of ASTRAL by the bioinformatics community.
Surface Shape Based Screening of Large Protein Databases. Start date: Sept. 23, 2005. Expires: Aug. 31, 2010. Amount: $295,444. Principal investigator: Daisuke Kihara. Institution: Purdue University, West Lafayette. NIH institute: NIGMS
Funds development of algorithms for identifying, representing, comparing, clustering, and docking local surface shape signatures of proteins. To identify binding sites, a visibility based algorithm will be used, which can identify both cavity and protrusion regions. In addition, three hierarchical levels of representation are proposed to represent identified binding sites.
A Systems Approach to Mapping the DNA Damage Response. Start date: Sept. 26, 2005. Expires: July 30, 2010. Amount: $600,688. Principal investigator: Trey Ideker. Institution: University of California, San Diego. NIH institute: NIEHS.
Proposal to elucidate the eukaryotic DNA damage response through an integrated experimental/computational approach that will lead to in silico models of signaling and regulatory networks. According to the investigators, "comparative modeling of the networks induced by different damaging agents is likely to reveal rich new insights into cellular toxicity and, ultimately, cancer progression."
CloNET: Modeling Genetic Networks from Clonal Analysis. Start date: Sept. 30, 2005. Expires: Sept. 29, 2007. Amount: $71,000. Principal investigator: Radhakrishnan Nagarajan. Institution: University of Arkansas, Little Rock. NIH institute: NLM.
Proposal to develop an interactive and mathematically rigorous toolbox called CloNET for modeling the dependencies and network structure from gene expression data obtained from clonal analysis. The toolbox will be developed in the language R.
Integrated Bioinformatic Analysis of Genomic Datasets. Start date: Sept. 30, 2005. Expires: Sept. 29, 2008. Amount: $162,000. Principal investigator: Rakesh Nagarajan. Institution: Washington University. NIH institute: NLM.
Project to software applications that will perform integrated analyses of functional genomic datasets with clinical data and gene annotation. The application will concurrently analyze and visualize functional genomic datasets with clinicopathology patient data and gene annotation using statistical algorithms.
Mixed Effects Modeling of Microarrays Using the S-score. Start date: Aug. 1, 2005. Expires: July 31, 2008. Amount: $65,944. Principal investigator: Richard Kennedy. Institution: Virginia Commonwealth University. NIH institute: NLM.
Proposal to design, implement, and validate a mixed effects model extension of the S-score algorithm for oligonucleotide microarrays. The S-score was originally developed to provide alternatives to existing software for measuring differential gene expression. It is based on an error model in which the detected signal is proportional to the probe pair signal for highly expressed genes, but approaches a background level (rather than 0) for low levels of expression. According to the grantees, improvements on the S-score may be realized by extending it to a more general model capable of handling more than two samples and mixed effects in the predictor variables.