Bioinformatics : Advanced Topics

Gretchen Kenney

ISBN 10: 1632390973 / ISBN 13: 9781632390974

Published by ML Books International - IPS, 2015

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - The science of compiling and studying complex biological data, such as genetic codes, is referred to as bioinformatics. This book extensively covers topics related to bioinformatics. It includes a wide variety of topics such as unraveling genetic determinants of complex disorders, functional characterization of inherently unfolded proteins/regions and database resources for protein allergens. It also elaborates topics like protein interaction networks, flexible protein-protein docking and classification and prediction of regulatory motifs. There has also been emphasis on computational means for determining best classifiers and key disease genes in large-scale transcriptomic and proteomic experiments. Computational algorithms have been explained in an easy-to-grasp manner for graduate and undergraduate students apart from researchers studying molecular biology and genetics. The book aims to assist biostatisticians, computational scientists and mathematicians in their academic and research activities in the field of bioinformatics.

Seller Inventory # 9781632390974

Bibliographic Details

• Title: Bioinformatics : Advanced Topics
• Publisher: ML Books International - IPS
• Publication Date: 2015
• Language: English
• ISBN 10: 1632390973
• ISBN 13: 9781632390974
• Binding: Buch
• Condition: Neu
• Dimensions: 235W x 157H x 15D millimeters 235 millimeters width by 157 millimeters height by 15 millimeters depth
• Weight: 434 grams

About this title

Synopsis

The science of compiling and studying complex biological data, such as genetic codes, is referred to as bioinformatics. This book extensively covers topics related to bioinformatics. It includes a wide variety of topics such as unraveling genetic determinants of complex disorders, functional characterization of inherently unfolded proteins/regions and database resources for protein allergens. It also elaborates topics like protein interaction networks, flexible protein-protein docking and classification and prediction of regulatory motifs. There has also been emphasis on computational means for determining best classifiers and key disease genes in large-scale transcriptomic and proteomic experiments. Computational algorithms have been explained in an easy-to-grasp manner for graduate and undergraduate students apart from researchers studying molecular biology and genetics. The book aims to assist biostatisticians, computational scientists and mathematicians in their academic and research activities in the field of bioinformatics.