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Computational Systems Biology

Overview of attention for book
Cover of 'Computational Systems Biology'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Identification of cis -Regulatory Elements in Gene Co-expression Networks Using A-GLAM
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    Chapter 2 Structure-Based Ab Initio Prediction of Transcription Factor–Binding Sites
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    Chapter 3 Inferring Protein–Protein Interactions from Multiple Protein Domain Combinations
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    Chapter 4 Prediction of Protein–Protein Interactions: A Study of the Co-evolution Model
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    Chapter 5 Computational Reconstruction of Protein–Protein Interaction Networks: Algorithms and Issues
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    Chapter 6 Prediction and Integration of Regulatory and Protein–Protein Interactions
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    Chapter 7 Detecting hierarchical modularity in biological networks.
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    Chapter 8 Methods to Reconstruct and Compare Transcriptional Regulatory Networks
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    Chapter 9 Learning Global Models of Transcriptional Regulatory Networks from Data
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    Chapter 10 Inferring Molecular Interactions Pathways from eQTL Data
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    Chapter 11 Methods for the Inference of Biological Pathways and Networks
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    Chapter 12 Exploring Pathways from Gene Co-expression to Network Dynamics
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    Chapter 13 Network Dynamics
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    Chapter 14 Kinetic Modeling of Biological Systems
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    Chapter 15 Guidance for Data Collection and Computational Modelling of Regulatory Networks
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    Chapter 16 A Maximum Likelihood Method for Reconstruction of the Evolution of Eukaryotic Gene Structure
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    Chapter 17 Enzyme Function Prediction with Interpretable Models
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    Chapter 18 Using Evolutionary Information to Find Specificity-Determining and Co-evolving Residues
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    Chapter 19 Connecting Protein Interaction Data, Mutations, and Disease Using Bioinformatics
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    Chapter 20 Effects of Functional Bias on Supervised Learning of a Gene Network Model
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    Chapter 21 Comparing Algorithms for Clustering of Expression Data: How to Assess Gene Clusters
  23. Altmetric Badge
    Chapter 22 The Bioverse API and Web Application
  24. Altmetric Badge
    Chapter 23 Computational Representation of Biological Systems
  25. Altmetric Badge
    Chapter 24 Biological Network Inference and Analysis Using SEBINI and CABIN
Attention for Chapter 7: Detecting hierarchical modularity in biological networks.
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Chapter title
Detecting hierarchical modularity in biological networks.
Chapter number 7
Book title
Computational Systems Biology
Published in
Methods in molecular biology, April 2009
DOI 10.1007/978-1-59745-243-4_7
Pubmed ID
Book ISBNs
978-1-58829-905-5, 978-1-59745-243-4
Authors

Ravasz E, Erzsébet Ravasz, Ravasz, Erzsébet

Abstract

Spatially or chemically isolated modules that carry out discrete functions are considered fundamental building blocks of cellular organization. However, detecting them in highly integrated biological networks requires a thorough understanding of the organization of these networks. In this chapter I argue that many biological networks are organized into many small, highly connected topologic modules that combine in a hierarchical manner into larger, less cohesive units. On top of a scale-free degree distribution, these networks show a power law scaling of the clustering coefficient with the node degree, a property that can be used as a signature of hierarchical organization. As a case study, I identify the hierarchical modules within the Escherichia coli metabolic network, and show that the uncovered hierarchical modularity closely overlaps with known metabolic functions.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 5%
United Kingdom 2 3%
Hungary 1 2%
Sweden 1 2%
Unknown 57 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 27%
Student > Ph. D. Student 16 25%
Student > Doctoral Student 5 8%
Professor 5 8%
Student > Bachelor 4 6%
Other 10 16%
Unknown 7 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 45%
Computer Science 7 11%
Biochemistry, Genetics and Molecular Biology 5 8%
Engineering 4 6%
Medicine and Dentistry 3 5%
Other 6 9%
Unknown 10 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 April 2012.
All research outputs
#15,243,120
of 22,664,644 outputs
Outputs from Methods in molecular biology
#5,283
of 13,025 outputs
Outputs of similar age
#78,637
of 93,185 outputs
Outputs of similar age from Methods in molecular biology
#13
of 25 outputs
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So far Altmetric has tracked 13,025 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 45th percentile – i.e., 45% of its peers scored the same or lower than it.
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We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.