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NSF Bioinformatics Grants Awarded April 4 — May 28, 2008

Gold Standard Set for Functional Annotation of Microbial Hypothetical Proteins. Start date: May 15, 2008. Expires: April 30, 2009. Awarded amount to date: $179,752. Principal investigator: Eugene Kolker. Sponsor: Children's Hospital and Regional Medical Center.
Supports a project to create a “gold standard” reference set of annotated genes that were previously designated as hypothetical. This set will serve as a baseline for validating new approaches to functional annotation of uncharacterized genes, according to the grant abstract. The investigators note that hypothetical genes comprise around one-third of all predicted genes, “and their number is expanding rapidly with each new genome sequencing project.” The goal of the project is to build a reference set of 200 previously hypothetical genes with high quality functional annotation.

Exploring Timescale Parallelization for Long-timescale Molecular Dynamics. Start date: May 15, 2008. Expires: April 30, 2009. Awarded amount to date: $103,063. Principal investigator: Srinivas Aluru. Sponsor: Iowa State University.
Supports development of timescale parallelization methods that will extend the timescales for molecular dynamics by orders of magnitude while retaining atomic level details, according to the grant abstract. The investigators will make the methods available as part of a new version of the LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) software package.

Identifying Selection Pressures on Viral Genomes. Start date: June 1, 2008. Expires: May 31, 2009. Awarded amount to date: $188,803. Principal investigator: Simon Frost. Sponsor: University of California-San Diego.
Supports development of likelihood-based statistical models of molecular evolution to study evolutionary patterns from alignments of coding sequences. The proposed models will allow the pattern of substitution to vary across the phylogenetic tree, across sites in the alignment, and to depend on the residues involved, according to the grant abstract. The models also account for recombination by permitting phylogenetic histories to change between regions of an alignment. “These evolutionary patterns will be derived from the data, rather than from a priori assumptions, through the innovative use of genetic algorithms to search for good-fitting models,” the investigators state in the abstract.

Complex Biological Systems Across Multiple Space and Time Scales. Start date: June 1, 2008. Expires: May 31, 2011. Awarded amount to date: $1,446,022. Principal investigator: Beatrice Riviere. Sponsor: University of Pittsburgh.
Supports the development of algorithms for solving complex spatio-temporal problems that arise in biology and the application of these and other methods to neuroscience and inflammation research. In particular, the project will develop “effective discretizations of coupled biological processes, iterative solvers, and coupling/decoupling strategies,” according to the grant abstract.

Statistical Methodology and Applications to Genetics, Engineering and Economics. Start date: July 1, 2008. Expires: June 30, 2011. Awarded amount to date: $587,375. Principal investigator: Tze Lai. Sponsor: Stanford University.
Supports development of an improved method for searching a parameter set for the location of one or more signals in a noisy background — a problem that occurs in gene mapping, bioinformatics, and other applications, according to the grant abstract. This problem arises in gene mapping, brain mapping, bioinformatics, and astronomy. The project plans to use parallel recursive algorithms, new ideas in change-point detection, and empirical Bayes methodology to develop asymptotically efficient estimation and prediction schemes with “manageable complexity.” One goal of the proposed research is to develop a comprehensive theory of efficient parameter estimation, filtering, and smoothing in hidden Markov models on general state spaces, the abstract states.

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The Scan

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In PLOS this week: functional potential of the cervicovaginal microbiome, glycosylation patterns in model archaea, and more.