With the advent of high-throughput experimental and genome technologies, the amounts of produced biological data and the related literature have increased dramatically. A significant portion of the produced biological data has revealed genotypic features of many model organisms. An outstanding problem presently is to map the characterized genotypic features to their phenotypic properties with the ultimate goal of making high-impact scientific discoveries in areas including diagnosing/curing diseases, engineering genomes, and inventing drugs. To this end, three major challenges concerning the management and analysis of the available data are: high volume (e.g., thousands of genes, millions of publications), increasing diversity (e.g., genes, pathways, metabolic profiles), and high complexity (e.g., hierarchical organization of entities, graph structures). In this book, we discuss several biological data mining and analysis problems. The book addresses distinct keystones on the path from genotype (e.g., genes and functionality annotations) to phenotype (e.g., metabolite profile changes). This book is intended for all Bioinformatics and Data Mining researchers, as well as instructors.
Product Identifiers
Publisher
Vdm Verlag
ISBN-13
9783639229127
eBay Product ID (ePID)
11049031092
Product Key Features
Author
Ali Cakmak
Publication Name
Mining Metabolic Networks and Biomedical Literature
Format
Paperback
Language
English
Subject
Engineering & Technology
Publication Year
2010
Type
Textbook
Number of Pages
244 Pages
Dimensions
Item Height
229mm
Item Width
152mm
Item Weight
363g
Additional Product Features
Title_Author
Ali Cakmak
Country/Region of Manufacture
Germany
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