Proceedings of the 2016 International Conference on Biological Sciences and Technology

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

Authors
Rui Guo, Jian Zhang, Ke Yan, Tian-Qi Wang
Corresponding Author
Rui Guo
Available Online January 2016.
DOI
https://doi.org/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.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
The International Conference on Biological Sciences and Technology
Part of series
Advances in Biological Sciences Research
Publication Date
January 2016
ISBN
978-94-6252-161-2
ISSN
2468-5747
DOI
https://doi.org/10.2991/bst-16.2016.8How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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  - The International Conference on Biological Sciences and Technology
PB  - Atlantis Press
SN  - 2468-5747
UR  - https://doi.org/10.2991/bst-16.2016.8
DO  - https://doi.org/10.2991/bst-16.2016.8
ID  - Guo2016/01
ER  -