Gene Prediction Based On a Generalized Hidden Markov Model and Some Statistical Models of Related States: a Review

DOI

10.2991/bst-16.2016.8How to use a DOI?

Keywords

GHMM, WMM, WAM, WWAM, MC, IMM, MDD.

Abstract

In recent years, the methods with a generalized hidden Markov model have gained significant application and development in gene prediction, which is predicting the location and structure of genes in genomic sequences, and produced an army of remarkable programs, such as Genie, GENSCAN, AUGUSTUS, etc. In spite of some limitations, the favorable performance and accuracy these programs still show have withstood the test of practice and time. Here, we provide a comprehensive review of the method of gene prediction with a novel hidden Markov model and some statistical models of related states included, just to share this knowledge with individuals interested in it.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Rui Guo
AU  - Jian Zhang
AU  - Ke Yan
AU  - Tian-Qi Wang
PY  - 2016/01
DA  - 2016/01
TI  - Gene Prediction Based On a Generalized Hidden Markov Model and Some Statistical Models of Related States: a Review
BT  - Proceedings of the 2016 International Conference on Biological Sciences and Technology
PB  - Atlantis Press
SP  - 36
EP  - 46
SN  - 2468-5747
UR  - https://doi.org/10.2991/bst-16.2016.8
DO  - 10.2991/bst-16.2016.8
ID  - Guo2016/01
ER  -