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The Resource Computational systems biology, edited by Jason McDermott [and others]

Computational systems biology, edited by Jason McDermott [and others]

Label
Computational systems biology
Title
Computational systems biology
Statement of responsibility
edited by Jason McDermott [and others]
Contributor
Subject
Language
eng
Summary
The recent confluence of high throughput methodology for biological data gathering, genome-scale sequencing, and computational processing power has driven a reinvention and expansion of the way we identify, infer, model, and store relationships between molecules, pathways, and cells in living organisms. In Computational Systems Biology, expert investigators contribute chapters which bring together biological data and computational and/or mathematical models of the data to aid researchers striving to create a system that provides both predictive and mechanistic information for a model organism. The volume is organized into five major sections involving network components, network inference, network dynamics, function and evolutionary system biology, and computational infrastructure for systems biology. As a volume of the highly successful Methods in Molecular Biology series, this work provides the kind of detailed description and implementation advice that is crucial for getting optimal results. Comprehensive and up-to-date, Computational Systems Biology serves to motivate and inspire all those who wish to develop a complete description of a biological system
Member of
Cataloging source
CUS
Illustrations
illustrations
Index
index present
Language note
English
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Series statement
  • Methods in molecular biology,
  • Springer protocols
Series volume
541
Computational systems biology, edited by Jason McDermott [and others]
Label
Computational systems biology, edited by Jason McDermott [and others]
Link
http://libproxy.rpi.edu/login?url=http://link.springer.com/10.1007/978-1-59745-243-4
Publication
Related Contributor
Related Location
Related Agents
Related Authorities
Related Subjects
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Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
mixed
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Identification of cis-regulatory elements in gene co-expression networks using A-GLAM / Leonardo Mariño-Ramírez [and others] -- Structure-based Ab Initio prediction of transcription factor-binding sites / L. Angela Liu and Joel S. Bader -- Inferring protein-protein interactions from multiple protein domain combinations / Simon P. Kanaan [and others] -- Prediction of protein-protein interactions : a study of the co-evolution model / Itai Sharon, Jason V. Davis and Golan Yona -- Computational reconstruction of protein-protein interaction networks : algorithms and issues / Eric Franzosa, Bolan Linghu and Yu Xia -- Prediction and integration of regulatory and protein-protein interactions / Duangdao Wichadakul, Jason McDermott and Ram Samudrala -- Detecting hierarchical modularity in biological networks / Erzsébet Ravasz -- Methods to reconstruct and compare transcriptional regulatory networks / M. Madan Babu, Benjamin Lang and L. Aravind -- Learning global models of transcriptional regulatory networks from data / Aviv Madar and Richard Bonneau -- Inferring molecular interactions pathways from eQTL data / Imran Rashid, Jason McDermott and Ram Samudrala -- Methods for the inference of biological pathways and networks / Roger E. Bumgarner and Ka Yee Yeung -- Exploring pathways from gene co-expression to network dynamics / Huai Li, Yu Sun and Ming Zhan -- Network dynamics / Herbert M. Sauro -- Kinetic modeling of biological systems / Haluk Resat, Linda Petzold and Michel F. Pettigrew -- Guidance for data collection and computational modelling of regulatory networks / Adam Christopher Palmer and Keith Edward Shearwin -- A maximum likelihood method for reconstruction of the evolution of eukaryotic gene structure / Liran Carmel [and others] -- Enzyme function prediction with Interpretable models / Umar Syed and Golan Yona -- Using evolutionary information to find specificity-determining and co-evolving residues / Grigory Kolesov and Leonid A. Mirny -- Connecting protein interaction data, mutations, and disease using bioinformatics / Jake Y. Chen, Eunseog Youn and Sean D. Mooney -- Effects of functional bias on supervised learning of a gene network model / Insuk Lee and Edward M. Marcotte -- Comparing algorithms for clustering of expression data : how to assess gene clusters / Golan Yona, William Dirks and Shafquat Rahman -- The bioverse API and web application / Michal Guerquin [and others] -- Computational representation of biological systems / Zach Frazier [and others] -- Biological network inference and analysis using SEBINI and CABIN / Ronald Taylor and Mudita Singhal
http://library.link/vocab/cover_art
https://contentcafe2.btol.com/ContentCafe/Jacket.aspx?Return=1&Type=S&Value=9781597452434&userID=ebsco-test&password=ebsco-test
Dimensions
unknown
http://library.link/vocab/discovery_link
{'f': 'http://opac.lib.rpi.edu/record=b3357362'}
Extent
1 online resource (xviii, 587 pages)
Form of item
online
Isbn
9781597452434
Lccn
2009920380
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other physical details
illustrations (some color).
Reproduction note
Electronic reproduction.
Sound
unknown sound
Specific material designation
remote
System details
Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.

Library Locations

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