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Data Mining for Systems Biology

Overview of attention for book
Cover of 'Data Mining for Systems Biology'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Dense Module Enumeration in Biological Networks
  3. Altmetric Badge
    Chapter 2 Discovering Interacting Domains and Motifs in Protein–Protein Interactions
  4. Altmetric Badge
    Chapter 3 Global alignment of protein-protein interaction networks.
  5. Altmetric Badge
    Chapter 4 Structure learning for bayesian networks as models of biological networks.
  6. Altmetric Badge
    Chapter 5 Supervised Inference of Gene Regulatory Networks from Positive and Unlabeled Examples
  7. Altmetric Badge
    Chapter 6 Mining regulatory network connections by ranking transcription factor target genes using time series expression data.
  8. Altmetric Badge
    Chapter 7 Identifying Pathways of Coordinated Gene Expression
  9. Altmetric Badge
    Chapter 8 Data Mining for Systems Biology
  10. Altmetric Badge
    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.
  12. Altmetric Badge
    Chapter 11 Analysis Strategy of Protein–Protein Interaction Networks
  13. Altmetric Badge
    Chapter 12 Data Mining in the MetaCyc Family of Pathway Databases
  14. Altmetric Badge
    Chapter 13 Gene Set/Pathway Enrichment Analysis
  15. Altmetric Badge
    Chapter 14 Construction of Functional Linkage Gene Networks by Data Integration
  16. Altmetric Badge
    Chapter 15 Genome-Wide Association Studies
  17. Altmetric Badge
    Chapter 16 Viral Genome Analysis and Knowledge Management
  18. Altmetric Badge
    Chapter 17 Molecular Network Analysis of Diseases and Drugs in KEGG.
Attention for Chapter 3: Global alignment of protein-protein interaction networks.
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Chapter title
Global alignment of protein-protein interaction networks.
Chapter number 3
Book title
Data Mining for Systems Biology
Published in
Methods in molecular biology, December 2012
DOI 10.1007/978-1-62703-107-3_3
Pubmed ID
Book ISBNs
978-1-62703-106-6, 978-1-62703-107-3
Authors

Mongiovì M, Sharan R, Misael Mongiovì, Roded Sharan, Mongiovì, Misael, Sharan, Roded

Abstract

Sequence-based comparisons have been the workhorse of bioinformatics for the past four decades, furthering our understanding of gene function and evolution. Over the last decade, a plethora of technologies have matured for measuring Protein-protein interactions (PPIs) at large scale, yielding comprehensive PPI networks for over ten species. In this chapter, we review methods for harnessing PPI networks to improve the detection of orthologous proteins across species. In particular, we focus on pairwise global network alignment methods that aim to find a mapping between the networks of two species that maximizes the sequence and interaction similarities between matched nodes. We further suggest a novel evolutionary-based global alignment algorithm. We then compare the different methods on a yeast-fly-worm benchmark, discuss their performance differences, and conclude with open directions for future research.

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The data shown below were collected from the profiles of 2 X users 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 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 13%
Unknown 7 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 38%
Student > Ph. D. Student 2 25%
Other 2 25%
Professor > Associate Professor 1 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 38%
Biochemistry, Genetics and Molecular Biology 2 25%
Mathematics 1 13%
Computer Science 1 13%
Engineering 1 13%
Other 0 0%
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 20 June 2013.
All research outputs
#15,330,390
of 23,577,654 outputs
Outputs from Methods in molecular biology
#4,903
of 13,410 outputs
Outputs of similar age
#177,427
of 281,537 outputs
Outputs of similar age from Methods in molecular biology
#178
of 347 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,410 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 58% of its peers.
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We're also able to compare this research output to 347 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.