Computational Biology [electronic resource] / edited by David Fenyö.
- Totowa, NJ : Humana Press : Imprint: Humana Press, 2010.
- Methods in Molecular Biology, Methods and Protocols, 1064-3745 ; 673
Springer Protocols (Springer-12345)
Methods in Molecular Biology, Methods and Protocols, 1064-3745 ; 673
1 online resource (XI, 327 pages) : 81 illustrations.
- Life sciences.
- Local subjects:
- Life Sciences.
Computer Appl. in Life Sciences.
- System Details:
- text file PDF
- Computational biology is an interdisciplinary field that applies mathematical, statistical, and computer science methods to answer biological questions, and its importance has only increased with the introduction of high-throughput techniques such as automatic DNA sequencing, comprehensive expression analysis with microarrays, and proteome analysis with modern mass spectrometry. In Computational Biology, expert practitioners present a broad survey of computational biology methods by focusing on their applications, including primary sequence analysis, protein structure elucidation, transcriptomics and proteomics data analysis, and exploration of protein interaction networks. As a volume in 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. Authoritative and easy to use, Computational Biology is an ideal guide for all scientists interested in quantitative biology.
- Sequencing and Genome Assembly Using Next-Generation Technologies
RNA Structure Prediction
Normalization of Gene-Expression Microarray Data
Prediction of Transmembrane Topology and Signal Peptide Given a Protein's Amino Acid Sequence
Protein Structure Modeling
Template-Based Protein Structure Modeling
Automated Protein NMR Structure Determination in Solution
Computational Tools in Protein Crystallography
3-D Structures of Macromolecules Using Single-Particle Analysis in EMAN
Computational Design of Chimeric Protein Libraries for Directed Evolution
Mass Spectrometric Protein Identification Using the Global Proteome Machine
Unbiased Detection of Posttranslational Modifications Using Mass Spectrometry
Protein Quantitation Using Mass Spectrometry
Modeling Experimental Design for Proteomics
A Functional Proteomic Study of the Trypanosoma brucei Nuclear Pore Complex: An Informatic Strategy
Inference of Signal Transduction Networks from Double Causal Evidence
Reverse Engineering Gene Regulatory Networks Related to Quorum Sensing in the Plant Pathogen Pectobacterium atrosepticum
Parameter Inference and Model Selection in Signaling Pathway Models
Genetic Algorithms and Their Application to In Silico Evolution of Genetic Regulatory Networks.
- Fenyö, David. editor.
SpringerLink (Online service)
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- Printed edition:
- Publisher Number:
- 10.1007/978-1-60761-842-3 doi
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- Restricted for use by site license.
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