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BioInform s Funding Update: Some Recent NIH Awards in Bioinformatics: May 12, 2003

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Core: Bioinformatics and Microarray. Start date: April 2003, Expires: March 2008. Principal investigator: Clayton Naeve. Institution: St. Jude Children’s Hospital. NIH Institute: NCI.

Funding for a core facility to support the production and use of cDNA and oligonucleotide microarrays, along with bioinformatic support for data storage and analysis. Current bioinformatics resources include InforMax’s Vector NTI and GenoMax, an Affymetrix LIMS system, Spotfire DecisionSite, and other applications for sequence and gene expression analysis.

 

Ab Initio Geometry Optimization of Large Molecules. Start date: April 2003. Expires: September 2003. Principal investigator: Jing Kong. Institution: Q-Chem. NIH Institute: NIGMS.

Supports development of a new cost-effective algorithm for density-functional geometry optimizers for biomolecules, an approach that is currently limited to relatively small molecules containing no more than 30 atoms.

 

Bioinformatics for Immune Response Biosignature Analyses. Start date: May 2003. Expires: October 2003. Principal investigator: Kenneth Drake. Institution: Seralogix. NIH Institute: NIAID.

Phase I SBIR grant to develop a prototype of a bioinformatics framework for immune response biosignature analyses of infectious diseases, including biowarfare agents. The framework combines dynamic Bayesian network learning and modeling techniques with intelligent software agent technology.

 

Beowulf Cluster for Computer-Intensive Research. Start Date: May 2003. Expires: April 2004. Principal Investigator: Michael King. Institution: University of Massachusetts Medical School, Worcester. NIH Institute: NCRR.

Grant to support the purchase of a Beowulf cluster for NIH-funded researchers at the University of Massachusetts Medical School, particularly new recruits who are expected to conduct research in the areas of bioinformatics, structural biology, molecular biophysics, and imaging.

 

Computational Analysis of Cancer Cytogenetic Data. Start date: April 2003. Expires: March 2005. Principal investigator: Ping Liang. Institution: Roswell Park Cancer Institute. NIH Institute: NCI.

Supports a project to analyze cancer etiologic/cytogenetic data deposited in the Mitelman Database of Chromosomal Aberrations in Cancers using computational approaches. The researchers plan to develop an algorithm that will analyze karyotype data to reveal all cytogenetic changes based on information in the database.

 

Algorithms to Map Disease & Genetic Effects on the Brain. Start date: May 2003. Expires: Feb. 2006. Principal investigator: Paul Thompson. Institution: University of California, Los Angeles. NIH Institute: NIBIB.

Project aims to develop a computational framework to map disease and genetic effects on the brain by blending neuroimaging and genetics techniques. A pilot project will first develop the mathematics and software necessary to link large-scale brain imaging and genetic studies of the brain. These algorithms will detect, map, and help understand patterns of abnormality in subjects at genetic risk for disease. Additional algorithms will chart how the brain changes dynamically in childhood, with age, according to gender, and in health and disease. Patterns will be stored in a computational/statis- tical brain atlas, and be linked with cognitive, clinical, and therapeutic parameters.

 

Functional Genomic Screen using RNAi in Drosophila. Start date: May 2003. Expires: April 2007. Principal investigator: Norbert Perrimon. Institution: Harvard Medical School. NIH Institute: NIGMS.

Supports the creation of an “RNAi facility” within the Institute of Chemistry and Cell Biology at Harvard Medical School where visiting scientists can conduct high-throughput RNAi screens with the help of experienced staff. The facility will provide bioinformatics support to help investigators conduct the screens and interpret the primary data. In addition, a central, publicly available database will be established that keeps records of all RNAi screens.

 

Improve Predictions of Structure/Function by PredictProtein. Start date: May 2003. Expires: April 2007. Principal investigator: Burkhard Rost. Institution: Columbia University Health Sciences. NIH Institute: NLM.

Supports improvements to PredictProtein, an internet server for protein structure prediction. Technical improvements will address job and data handling, database updates, user interface, web page layout, presentation of results, and will directly link original resources. The researchers will focus on improving predictions for membrane helical proteins, developing methods to predict beta-membrane proteins, and on using structure predictions to accurately infer functional information.

 

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