One of the goals the post-genomic era is to use protein sequence and structure data to learn about the function of these proteins in normal and disease states. In the ¿omics¿ era, computational methods constitute a valuable tool, because they can easily process large amounts of data and provide useful and instant information relevant in biomedical research. This book described using computational approaches to study the effects of genetic mutations in proteins, with the general aim of correlating protein sequence, structure, and function. Our works focus on identifying whether genotype/phenotype relationship can be learned from protein sequence and structural information, whether protein structure prediction methods are accurate enough to provide useful information when the experimental structures are not available, and finally to combine this information to predict and understand the effect of mutations on clinical phenotype and drug responses. The approaches developed in this work enable a systematic, comprehensive, and quantitative analysis of disease-related mutations and establish a paradigm to study genotype/phenotype correlations.
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One of the goals the post-genomic era is to use protein sequence and structure data to learn about the function of these proteins in normal and disease states. In the ¿omics¿ era, computational methods constitute a valuable tool, because they can easily process large amounts of data and provide useful and instant information relevant in biomedical research. This book described using computational approaches to study the effects of genetic mutations in proteins, with the general aim of correlating protein sequence, structure, and function. Our works focus on identifying whether genotype/phenotype relationship can be learned from protein sequence and structural information, whether protein structure prediction methods are accurate enough to provide useful information when the experimental structures are not available, and finally to combine this information to predict and understand the effect of mutations on clinical phenotype and drug responses. The approaches developed in this work enable a systematic, comprehensive, and quantitative analysis of disease-related mutations and establish a paradigm to study genotype/phenotype correlations.
Zhiyan FU, Ph.D. in Computational Biology at Mount Sinai School of Medicine of New York University, New York. M.S. in Bioinformatics at Zhongshan (Sun Yat-sen) University, Guangzhou. Research Scientist, Signal Patterns Inc., Pleasantville, NY. Biostatistics Consultant, Mount Sinai Medical Center, New York, NY.
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Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. One of the goals the post-genomic era is to useprotein sequence and structure data to learn aboutthe function of these proteins in normal and diseasestates. In the omics era, computational methodsconstitute a valuable tool, because. Nº de ref. del artículo: 4958610
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - One of the goals the post-genomic era is to useprotein sequence and structure data to learn aboutthe function of these proteins in normal and diseasestates. In the omics era, computational methodsconstitute a valuable tool, because they can easilyprocess large amounts of data and provide useful andinstant information relevant in biomedical research.This book described using computational approaches tostudy the effects of genetic mutations in proteins,with the general aim of correlating protein sequence,structure, and function. Our works focus onidentifying whether genotype/phenotype relationshipcan be learned from protein sequence and structuralinformation, whether protein structure predictionmethods are accurate enough to provide usefulinformation when the experimental structures are notavailable, and finally to combine this information topredict and understand the effect of mutations onclinical phenotype and drug responses. The approachesdeveloped in this work enable a systematic,comprehensive, and quantitative analysis ofdisease-related mutations and establish a paradigm tostudy genotype/phenotype correlations. Nº de ref. del artículo: 9783639113167
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