Bayesian Models and Markov Chain Monte Carlo Methods for Protein Motifs with the Secondary Characteristics-Reference-Cited by-同舟云学术

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Bayesian Models and Markov Chain Monte Carlo Methods for Protein Motifs with the Secondary Characteristics

Published:2005-09 Issue:7 Volume:12 Page:952-970
ISSN:1066-5277
Container-title:Journal of Computational Biology
language:en
Short-container-title:Journal of Computational Biology

Author:

Xie Jun¹,Kim Nak-Kyeong¹

Affiliation:

1. Department of Statistics, Purdue University, 150 N. University Street, West Lafayette, IN 47907-2067.

Publisher

Mary Ann Liebert Inc

Subject

Computational Theory and Mathematics,Computational Mathematics,Genetics,Molecular Biology,Modelling and Simulation

Link

http://www.liebertpub.com/doi/pdf/10.1089/cmb.2005.12.952

Reference14 articles.

1. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs

2. Prosite: a dictionary of sites and patterns in proteins

3. The Pfam protein families database

4. Profile hidden Markov models

5. Probabilistic alignment of motifs with sequences

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. AI-assisted food enzymes design and engineering: a critical review;Systems Microbiology and Biomanufacturing;2022-10-01

2. An analysis of single amino acid repeats as use case for application specific background models;BMC Bioinformatics;2011-05-19

3. Protein Multiple Alignment Incorporating Primary and Secondary Structure Information;Journal of Computational Biology;2006-12

4. Protein Multiple Alignment Incorporating Primary and Secondary Structure Information;Journal of Computational Biology;2006-11

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