Post-Structural Genomics: Correlate Protein Sequence, Structure, and Function - Couverture souple

Fu, Zhiyan

 
9783639113167: Post-Structural Genomics: Correlate Protein Sequence, Structure, and Function
Couverture souple
ISBN 10 : 3639113160 ISBN 13 : 9783639113167
Editeur : VDM Verlag Dr. Müller, 2008

Synopsis

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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Présentation de l'éditeur

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.

Biographie de l'auteur

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.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
VDM Verlag Dr. Müller
Date d'édition
2008
Langue
anglais
ISBN 10 
3639113160
ISBN 13 
9783639113167
Reliure
Broché
Nombre de pages
132
Coordonnées du fabricant
non disponible
Personne responsable
non disponible