Empirical Inference

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

2006

Article

ei


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).

Author(s): Danziger, SA. and Swamidass, SJ. and Zeng, J. and Dearth, LR. and Lu, Q. and Cheng, JH. and Cheng, JL. and Hoang, VP. and Saigo, H. and Luo, R. and Baldi, P. and Brachmann, RK. and Lathrop, RH.
Journal: IEEE Transactions on Computational Biology and Bioinformatics
Volume: 3
Number (issue): 2
Pages: 114-125
Year: 2006
Month: April
Day: 0

Department(s): Empirical Inference
Bibtex Type: Article (article)

Digital: 0
DOI: 10.1109/TCBB.2006.22
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: PDF

BibTex

@article{4106,
  title = {Functional census of mutation sequence spaces: The example of p53 cancer rescue mutants},
  author = {Danziger, SA. and Swamidass, SJ. and Zeng, J. and Dearth, LR. and Lu, Q. and Cheng, JH. and Cheng, JL. and Hoang, VP. and Saigo, H. and Luo, R. and Baldi, P. and Brachmann, RK. and Lathrop, RH.},
  journal = {IEEE Transactions on Computational Biology and Bioinformatics},
  volume = {3},
  number = {2},
  pages = {114-125},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = apr,
  year = {2006},
  doi = {10.1109/TCBB.2006.22},
  month_numeric = {4}
}