Modern Homology Search

Dynamic programming [1] has full sensitivity, but too slow for large scale homology search. FASTA / BLAST type of heuristics [2] trade sensitivity for speed. Can we have both sensitivity and speed? We present the mathematical theory of optimized spaced seeds which allows modern homology search to achieve high sensitivity and high speed simultaneously. The spaced seed methodology is implemented in our PatternHunter software [3, 4], as well as many other modern homology search software, serving thousands of queries daily. The theory is then extended and implemented in ZOOM [5] to do fast genome scale reads mapping for the second generation sequencers. Joint work with Bin Ma, John Tromp, D. Kisman, Hao Lin, and Zefeng Zhang. References[1] S.F. Altschul, W. Gish, W. Miller W, E.W. Myers, D.J. Lipman. Basic local alignmentsearch tool. J Mol Biol 215:3(1990), 403–410.[2] T.F. Smith, M.S. Waterman, Identification of Common Molecular Subsequences.Journal of Molecular Biology , 147(1981), 195–197.[3] B. Ma, J. Tromp, M. Li, PatternHunter: Faster and more sensitive homology search.Bioinformatics, 18:3(2002), 440–445.[4] M. Li, B. Ma, D. Kisman and J. Tromp. PatternHunter II: highly sensitive and fasthomology search. J. Bioinformatics and Computational Biology , 2:3(2004), 417–440.[5] H. Lin, Z. Zhang, M.Q. Zhang, B. Ma, M. Li. ZOOM! Zillions of oligos mapped.Bioinformatics. In press. 2008.