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Multiple Sequence Alignment of the M Protein in SARS-Associated and Other Known Coronaviruses 被引量:1
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作者 史定华 周晖杰 +2 位作者 王斌宾 顾燕红 王翼飞 《Journal of Shanghai University(English Edition)》 CAS 2003年第2期118-123,共6页
In this paper, we report a multiple sequence alignment result on the basis of 10 amino acid sequences of the M protein, which come from different coronaviruses (4 SARS associated and 6 others known). The alignment mo... In this paper, we report a multiple sequence alignment result on the basis of 10 amino acid sequences of the M protein, which come from different coronaviruses (4 SARS associated and 6 others known). The alignment model was based on the profile HMM (Hidden Markov Model), and the model training was implemented through the SAHMM (Self Adapting Hidden Markov Model) software developed by the authors. 展开更多
关键词 SARS (Severe Acute Respiratory Syndrome) CORONAVIRUS M (Membrane or Matrix) protein multiple sequence alignment profile hmm.
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Brief Introduction to Self-Adapting Hidden Markov Model Program for Multiple Sequences Alignment
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作者 GuYan-hong SHIDing-hua 《Journal of Shanghai University(English Edition)》 CAS 2001年第2期93-95,共3页
In this letter, we briefly describe a program of self adapting hidden Markov model (SA HMM) and its application in multiple sequences alignment. Program consists of two stage optimisation algorithm.
关键词 hidden Markov model (hmm) profile hmm multiple sequences alignment BIOINFORMATICS
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Hidden Markov Models Incorporating Fuzzy Measures and Integrals for Protein Sequence Identification and Alignment 被引量:6
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作者 Niranjan P. Bidargaddi Madhu Chetty Joarder Kamruzzaman 《Genomics, Proteomics & Bioinformatics》 SCIE CAS CSCD 2008年第2期98-110,共13页
Profile hidden Markov models (HMMs) based on classical HMMs have been widely applied for protein sequence identification. The formulation of the forward and backward variables in profile HMMs is made under statistic... Profile hidden Markov models (HMMs) based on classical HMMs have been widely applied for protein sequence identification. The formulation of the forward and backward variables in profile HMMs is made under statistical independence assumption of the probability theory. We propose a fuzzy profile HMM to overcome the limitations of that assumption and to achieve an improved alignment for protein sequences belonging to a given family. The proposed model fuzzifies the forward and backward variables by incorporating Sugeno fuzzy measures and Choquet integrals, thus further extends the generalized HMM. Based on the fuzzified forward and backward variables, we propose a fuzzy Baum-Welch parameter estimation algorithm for profiles. The strong correlations and the sequence preference involved in the protein structures make this fuzzy architecture based model as a suitable candidate for building profiles of a given family, since the fuzzy set can handle uncertainties better than classical methods. 展开更多
关键词 fuzzy profile hmm sequence alignment fuzzy measure fuzzy integral
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