Band 1
Biomolecular Networks Methods and Applications in Systems Biology
Aus der Reihe
Wiley Series in Bioinformatics
121,99 €
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
Kopierschutz
Ja
Family Sharing
Nein
Text-to-Speech
Nein
Erscheinungsdatum
29.06.2009
Herausgeber
Luonan Chen + weitereVerlag
John Wiley & SonsSeitenzahl
416 (Printausgabe)
Dateigröße
9493 KB
Auflage
1. Auflage
Sprache
Englisch
EAN
9780470488058
Alternative techniques and tools for analyzing biomolecular
networks
With the recent rapid advances in molecular biology,
high-throughput experimental methods have resulted in enormous
amounts of data that can be used to study biomolecular networks in
living organisms. With this development has come recognition of the
fact that a complicated living organism cannot be fully understood
by merely analyzing individual components. Rather, it is the
interactions of components or biomolecular networks that are
ultimately responsible for an organism's form and function. This
book addresses the important need for a new set of computational
tools to reveal essential biological mechanisms from a systems
biology approach.
Readers will get comprehensive coverage of analyzing
biomolecular networks in cellular systems based on available
experimental data with an emphasis on the aspects of network,
system, integration, and engineering. Each topic is treated in
depth with specific biological problems and novel computational
methods:
* GENE NETWORKS--Transcriptional regulation; reconstruction
of gene regulatory networks; and inference of transcriptional
regulatory networks
* PROTEIN INTERACTION NETWORKS--Prediction of protein-protein
interactions; topological structure of biomolecular networks;
alignment of biomolecular networks; and network-based prediction of
protein function
* METABOLIC NETWORKS AND SIGNALING NETWORKS--Analysis,
reconstruction, and applications of metabolic networks; modeling
and inference of signaling networks; and other topics and new
trends
In addition to theoretical results and methods, many
computational software tools are referenced and available from the
authors' Web sites. Biomolecular Networks is an indispensable
reference for researchers and graduate students in bioinformatics,
computational biology, systems biology, computer science, and
applied mathematics.
networks
With the recent rapid advances in molecular biology,
high-throughput experimental methods have resulted in enormous
amounts of data that can be used to study biomolecular networks in
living organisms. With this development has come recognition of the
fact that a complicated living organism cannot be fully understood
by merely analyzing individual components. Rather, it is the
interactions of components or biomolecular networks that are
ultimately responsible for an organism's form and function. This
book addresses the important need for a new set of computational
tools to reveal essential biological mechanisms from a systems
biology approach.
Readers will get comprehensive coverage of analyzing
biomolecular networks in cellular systems based on available
experimental data with an emphasis on the aspects of network,
system, integration, and engineering. Each topic is treated in
depth with specific biological problems and novel computational
methods:
* GENE NETWORKS--Transcriptional regulation; reconstruction
of gene regulatory networks; and inference of transcriptional
regulatory networks
* PROTEIN INTERACTION NETWORKS--Prediction of protein-protein
interactions; topological structure of biomolecular networks;
alignment of biomolecular networks; and network-based prediction of
protein function
* METABOLIC NETWORKS AND SIGNALING NETWORKS--Analysis,
reconstruction, and applications of metabolic networks; modeling
and inference of signaling networks; and other topics and new
trends
In addition to theoretical results and methods, many
computational software tools are referenced and available from the
authors' Web sites. Biomolecular Networks is an indispensable
reference for researchers and graduate students in bioinformatics,
computational biology, systems biology, computer science, and
applied mathematics.
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