Joint classification and pairing of human chromosomes

Author

Biyani, Pravesh ; Wu, Xiaolin ; Sinha, Abhijit

Author_Institution

Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, Ont., Canada

Volume

2

Issue

2

fYear

2005

Firstpage

102

Lastpage

109

Abstract

We reexamine the problems of computer-aided classification and pairing of human chromosomes, and propose to jointly optimize the solutions of these two related problems. The combined problem is formulated into one of optimal three-dimensional assignment with an objective function of maximum likelihood. This formulation poses two technical challenges: 1) estimation of the posterior probability that two chromosomes form a pair and the pair belongs to a class and 2) good heuristic algorithms to solve the three-dimensional assignment problem which is NP-hard. We present various techniques to solve these problems. We also generalize our algorithms to cases where the cell data are incomplete as often encountered in practice.

Keywords

biology computing; cellular biophysics; computational complexity; maximum likelihood estimation; optimisation; probability; NP-hard; cell data; computer-aided classification; heuristic algorithms; human chromosome pairing; maximum likelihood; posterior probability; three-dimensional assignment problem; Biological cells; Cells (biology); Genetics; Heuristic algorithms; Humans; Linear programming; Maximum likelihood estimation; Neural networks; Testing; Transportation; Chromosome classification; homologue pairing; maximum likelihood estimation; optimization.; three-dimensional assignment; Algorithms; Artificial Intelligence; Chromosomes, Human; Humans; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Karyotyping; Likelihood Functions; Pattern Recognition, Automated;

fLanguage

English

Journal_Title

Computational Biology and Bioinformatics, IEEE/ACM Transactions on

Publisher

ieee

ISSN

1545-5963

Type

jour

DOI

10.1109/TCBB.2005.26

Filename

1438347