NSF D0241160 (PI Zhao)
1/1/03 - 12/31/06
NSF
Statistical and Computational Methods in Genomics and Proteomics and their Applications to Modeling the G11 Transition during Yeast Cell Cycle
Role: co-PI

In this project a team of researchers with expertise in statistics, genomics, proteomics, bioinformatics and computer science will develop an integrative approach to constructing biological pathways. The Gerstein lab contribution is to do data-mining to build biological networks.

Whole Project Website: http://bioinformatics.med.yale.edu/transcriptionalmodeling.htm


Year 1 report [ html ]
Year 2 report [ html ]
Year 3 report [ html ]

URL: https://www.fastlane.nsf.gov/servlet/showaward?award=0241160

Articles funded by this grant:
A high productivity/low maintenance approach to high-performance computation for biomedicine: four case studies.
N Carriero, MV Osier, KH Cheung, PL Miller, M Gerstein, H Zhao, B Wu, S Rifkin, J Chang, H Zhang, K White, K Williams, M Schultz (2005). J Am Med Inform Assoc 12: 90-8.

Genomic analysis of regulatory network dynamics reveals large topological changes.
NM Luscombe, MM Babu, H Yu, M Snyder, SA Teichmann, M Gerstein (2004). Nature 431: 308-12.

Genomic analysis of gene expression relationships in transcriptional regulatory networks.
H Yu, NM Luscombe, J Qian, M Gerstein (2003). Trends Genet 19: 422-7.

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