Computing Reviews
Today's Issue Hot Topics Search Browse Recommended My Account Log In
Review Help
Search
Joint classification and pairing of human chromosomes
Biyani P., Wu X., Sinha A.  IEEE/ACM Transactions on Computational Biology and Bioinformatics 2 (2): 102-109, 2005. Type: Article
Date Reviewed: Mar 22 2006

There are 46 chromosomes in a normal human cell. Each chromosome is composed of a long, single strand of DNA. At the right stage of cell division, the chromosomes condense and are observable by light microscopy. Certain genetic abnormalities can be observed in this manner and used to diagnose rare genetic diseases such as Down syndrome. It is often the case that the pattern of human chromosomes (that is, the karyotype) is compiled by hand.

There is some interest in automating this process using computational algorithms. Previous work in this area has focused almost exclusively on neural network approaches. Biyani and others argue that neural networks are suboptimal for this problem. This paper presents a maximum likelihood approach to the chromosome classification problem. The authors propose a three-dimensional assignment approach that uses a Lagrangian-type relaxation method for optimization. The authors were able to show that their method performed better than other methods in this domain.

It would be nice to eventually see this algorithm included in an open source software package that could be routinely used in cytogenetic laboratories that generate karyotypes from human cells for the purpose of genetic analysis and disease diagnosis. Integration of this algorithm into clinical practice will be the ultimate test of its validity and usefulness.

Reviewer:  Jason Moore Review #: CR132587 (0701-0088)
Bookmark and Share
  Featured Reviewer  
 
Biology And Genetics (J.3 ... )
 
 
Classifier Design And Evaluation (I.5.2 ... )
 
 
Design Methodology (I.5.2 )
 
 
Heuristic Methods (I.2.8 ... )
 
 
Problem Solving, Control Methods, And Search (I.2.8 )
 
Would you recommend this review?
yes
no
Other reviews under "Biology And Genetics": Date
Computational botany: methods for automated species identification
Remagnino P., Mayo S., Wilkin P., Cope J., Kirkup D.,  Springer International Publishing, New York, NY, 2016. 114 pp. Type: Book (978-3-662537-43-5)
Sep 20 2017
Reconstruction of gene regulatory networks based on repairing sparse low-rank matrices
Chang Y., Dobbe R., Bhushan P., Gray J., Tomlin C.  IEEE/ACM Transactions on Computational Biology and Bioinformatics 13(4): 767-777, 2016. Type: Article
Feb 1 2017
Multiple kernel fuzzy SVM-based data fusion for improving peptide identification
Jian L., Xia Z., Niu X., Liang X., Samir P., Link A.  IEEE/ACM Transactions on Computational Biology and Bioinformatics 13(4): 804-809, 2016. Type: Article
Jan 19 2017
more...

E-Mail This Printer-Friendly
Send Your Comments
Contact Us
Reproduction in whole or in part without permission is prohibited.   Copyright © 2000-2017 ThinkLoud, Inc.
Terms of Use
| Privacy Policy