Genome Clustering From Linguistic Models to Classification of Genetic Texts /
The study of language texts at the level of formal non-semantic models has a long history. Suffice it to say that the well-known Markov chains were first introduced as one of such models. The representation of biological data as text and, consequently, applications of text-analysis models in the fie...
| Main Authors: | , , , |
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| Corporate Author: | |
| Format: | Electronic |
| Language: | English |
| Published: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2010.
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| Series: | Studies in Computational Intelligence,
286 |
| Subjects: | |
| Online Access: | https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-12952-0 |
Table of Contents:
- Part 1 Biological Background
- Part 2 Biological Classification
- Part 3 Mathematical Models for the Analysis of Natural-Language Documents
- Part 4 DNA Texts
- Part 5 N-gram Spectra of the DNA Text
- Part 6 Application of Compositional Spectra to DNA Sequences
- Part 7 Marker-Function Profile-Based Clustering
- Part 8 Genome as a Bag of Genes the Whole-Genome Phylogenetics
- Part 9 Appendix A. Clustering Methods
- Part 10 Appendix B. Sequence Complexity
- Part 11 Appendix C. DNA curvature.