Constrained Markov networks for automated analysis of G-banded chromosomes
✍ Scribed by C. Guthrie; J. Gregor; M.G. Thomason
- Publisher
- Elsevier Science
- Year
- 1993
- Tongue
- English
- Weight
- 909 KB
- Volume
- 23
- Category
- Article
- ISSN
- 0010-4825
No coin nor oath required. For personal study only.
✦ Synopsis
Automated analysis of chromosome band patterns using probabilistic Markov networks has been reported in previous work. Band patterns are represented as strings of symbols. Inferred from a set of learning strings, a Markov network is a model of intraband and interband relations in these strings. The inference is entirely data-driven and is accomplished using dynamic programming. This paper presents a new model of chromosome band patterns, the constrained Markov network, which is a special case of its predecessor. Substantial experimental evidence of the superiority of the new model over the old is given in terms of equal results in centromere finding and improved results in classification for the 22 autosomes. Furthermore, a method for simplification of constrained Markov networks is shown to be of considerable importance with respect to computational complexity. Banded chromosome Centromere finding Chromosome classification Constrained Markov network Dynamic programming Pattern recognition * Author to whom correspondence should be addressed. CWt 2322-C * Cell-wise length normalization might yield a more appropriate range per specific cell, but classification of isolated chromosomes is computed here and cell-context is not taken into account.
* Note that UMNs cannot be pruned by this simple method because they are not constrained to the form of concatenated stages.