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Data Mining for Systems Biology

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Cover of 'Data Mining for Systems Biology'

Table of Contents

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    Book Overview
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    Chapter 1 Dense Module Enumeration in Biological Networks
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    Chapter 2 Discovering Interacting Domains and Motifs in Protein–Protein Interactions
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    Chapter 3 Global alignment of protein-protein interaction networks.
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    Chapter 4 Structure learning for bayesian networks as models of biological networks.
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    Chapter 5 Supervised Inference of Gene Regulatory Networks from Positive and Unlabeled Examples
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    Chapter 6 Mining regulatory network connections by ranking transcription factor target genes using time series expression data.
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    Chapter 7 Identifying Pathways of Coordinated Gene Expression
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    Chapter 8 Data Mining for Systems Biology
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    Chapter 9 Chemogenomic approaches to infer drug-target interaction networks.
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    Chapter 10 Localization prediction and structure-based in silico analysis of bacterial proteins: with emphasis on outer membrane proteins.
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    Chapter 11 Analysis Strategy of Protein–Protein Interaction Networks
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    Chapter 12 Data Mining in the MetaCyc Family of Pathway Databases
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    Chapter 13 Gene Set/Pathway Enrichment Analysis
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    Chapter 14 Construction of Functional Linkage Gene Networks by Data Integration
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    Chapter 15 Genome-Wide Association Studies
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    Chapter 16 Viral Genome Analysis and Knowledge Management
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    Chapter 17 Molecular Network Analysis of Diseases and Drugs in KEGG.
Attention for Chapter 11: Analysis Strategy of Protein–Protein Interaction Networks
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Chapter title
Analysis Strategy of Protein–Protein Interaction Networks
Chapter number 11
Book title
Data Mining for Systems Biology
Published in
Methods in molecular biology, January 2013
DOI 10.1007/978-1-62703-107-3_11
Pubmed ID
Book ISBNs
978-1-62703-106-6, 978-1-62703-107-3
Authors

Zhenjun Hu, Hu, Zhenjun

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 2 29%
Researcher 1 14%
Other 1 14%
Unknown 3 43%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 43%
Computer Science 1 14%
Unknown 3 43%