Gene Prediction Based On a Generalized Hidden Markov Model and Some Statistical Models of Related States: a Review
Rui Guo, Jian Zhang, Ke Yan, Tian-Qi Wang
Available Online January 2016.
- https://doi.org/10.2991/bst-16.2016.8How to use a DOI?
- GHMM, WMM, WAM, WWAM, MC, IMM, MDD.
- 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.
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 SP - 36 EP - 46 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 -