Multiple Alignments, Hidden Markov Models and SVMs - Abdullah, Mohamad Firdaus;Othman, Razib M
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Remote protein homology detection is a problem of detecting evolutionary relationship between proteins at low sequence similarity level. Among several problems in remote protein homology detection include the questions of determining which combination of multiple alignment and classification techniques is the best as well as the misalignment of protein sequences during the alignment process. Therefore, this study deals with remote protein homology detection via assessing the impact of using structural information on protein multiple alignments over sequence information. This study further…mehr

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Produktbeschreibung
Remote protein homology detection is a problem of detecting evolutionary relationship between proteins at low sequence similarity level. Among several problems in remote protein homology detection include the questions of determining which combination of multiple alignment and classification techniques is the best as well as the misalignment of protein sequences during the alignment process. Therefore, this study deals with remote protein homology detection via assessing the impact of using structural information on protein multiple alignments over sequence information. This study further presents the best combinations of multiple alignment and classification programs to be chosen. This study also improves the quality of the multiple alignments via integration of a refinement algorithm.
Autorenporträt
Mohamad Firdaus Abdullah has obtained his Masters Degree in Computer Science in 2010. Since then he has joined the industry and worked as internal software developer for a local based company in Malaysia.Dr. Razib M. Othman has obtained his PhD in Computer Science in 2008. Since then he has published numerous journal papers and book chapters.