Opportunities for combinatorial optimization in computational biology

被引:68
|
作者
Greenberg, HJ
Hart, WE
Lancia, G
机构
[1] Univ Colorado, Dept Math, Denver, CO 80217 USA
[2] Sandia Natl Labs, Discrete Algorithms & Math, Albuquerque, NM 87185 USA
[3] Univ Udine, Dept Matemat & Informat, I-33100 Udine, Italy
关键词
computational biology; combinatorial optimization; global optimization; integer programming; minimum energy; bioinformatics; molecular structure prediction; protein folding; protein alignment; rearrangements; assembly; sequence alignment; SNP; sorting by reversals;
D O I
10.1287/ijoc.1040.0073
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This is a survey designed for mathematical programming people who do not know molecular biology and want to learn the kinds of combinatorial optimization problems that arise. After a brief introduction to the biology, we present optimization models pertaining to sequencing, evolutionary explanations, structure prediction, and recognition. Additional biology is given in the context of the problems, including some motivation for disease diagnosis and drug discovery. Open problems are cited with an extensive bibliography, and we offer a guide to getting started in this exciting frontier.
引用
收藏
页码:211 / 231
页数:21
相关论文
共 50 条