title: Joint classification and pairing of human chromosomes.
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.
authors.affiliation: Electrical and Computer Engineering Department, McMaster University, 1280 Main Street West, Hamilton, Ontario, Canada L8S 4K1. pravesh@grads.ece.mcmaster.ca
authors.forename: Pravesh
authors.initials: P
authors.lastname: Biyani
authors.forename: Xiaolin
authors.initials: X
authors.lastname: Wu
authors.forename: Abhijit
authors.initials: A
authors.lastname: Sinha
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D002877:Chromosomes, Human / Q000235:genetics* / Q000648:ultrastructure*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D007621:Karyotyping / Q000379:methods*; D016013:Likelihood Functions; D010363:Pattern Recognition, Automated / Q000379:methods*