Functional census of mutation sequence spaces: The example of p53 cancer rescue mutants

Samuel A. Danziger, S. Joshua Swamidass, Jue Zeng, Lawrence R. Dearth, Qiang Lu, Jonathan H. Chen, Jianlin Cheng, Vinh P. Hoang, Hiroto Saigo, Ray Luo, Pierre Baldi, Rainer K. Brachmann, Richard H. Lathrop

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)

Abstract

Many biomedical problems relate to mutant functional properties across a sequence space of interest, e.g., flu, cancer, and HIV. Detailed knowledge of mutant properties and function improves medical treatment and prevention. A functional census of p53 cancer rescue mutants would aid the search for cancer treatments from p53 mutant rescue. We devised a general methodology for conducting a functional census of a mutation sequence space by choosing informative mutants early. The methodology was tested in a double-blind predictive test on the functional rescue property of 71 novel putative p53 cancer rescue mutants iteratively predicted in sets of three (24 iterations). The first double-blind 15-point moving accuracy was 47 percent and the last was 86 percent; r = 0.01 before an epiphanic 16th iteration and r = 0.92 afterward. Useful mutants were chosen early (overall r = 0.80). Code and data are freely available (http://www.igb.uci.edu/research/research.html, corresponding authors: R.H.L. for computation and R.K.B. for biology).

Original languageEnglish
Pages (from-to)114-124
Number of pages11
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume3
Issue number2
DOIs
Publication statusPublished - Apr 2006
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Genetics
  • Applied Mathematics

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