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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
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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.
  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 17: Molecular Network Analysis of Diseases and Drugs in KEGG.
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About this Attention Score

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  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

Mentioned by

wikipedia
2 Wikipedia pages

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
56 Mendeley
citeulike
1 CiteULike
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Chapter title
Molecular Network Analysis of Diseases and Drugs in KEGG.
Chapter number 17
Book title
Data Mining for Systems Biology
Published in
Methods in molecular biology, December 2012
DOI 10.1007/978-1-62703-107-3_17
Pubmed ID
Book ISBNs
978-1-62703-106-6, 978-1-62703-107-3
Authors

Kanehisa M, Minoru Kanehisa, Kanehisa, Minoru

Abstract

KEGG (http://www.genome.jp/kegg/) is an integrated database resource for linking genomes or molecular datasets to molecular networks (pathways, etc.) representing higher-level systemic functions of the cell, the organism, and the ecosystem. Major efforts have been undertaken for capturing and representing experimental knowledge as manually drawn KEGG pathway maps and for genome-based generalization of experimental knowledge through the KEGG Orthology (KO) system. Current knowledge on diseases and drugs has also been integrated in the KEGG pathway maps, especially in terms of known disease genes and drug targets. Thus, KEGG can be used as a reference knowledge base for integration and interpretation of large-scale datasets generated by high-throughput experimental technologies, as well for finding their practical values. Here we give an introduction to the KEGG Mapper tools, especially for understanding disease mechanisms and adverse drug interactions.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Italy 1 2%
Belgium 1 2%
Spain 1 2%
United States 1 2%
Unknown 51 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 27%
Student > Ph. D. Student 11 20%
Unspecified 6 11%
Other 4 7%
Student > Postgraduate 4 7%
Other 11 20%
Unknown 5 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 34%
Biochemistry, Genetics and Molecular Biology 7 13%
Unspecified 6 11%
Medicine and Dentistry 4 7%
Computer Science 3 5%
Other 10 18%
Unknown 7 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 16 November 2021.
All research outputs
#7,668,611
of 23,344,526 outputs
Outputs from Methods in molecular biology
#2,379
of 13,338 outputs
Outputs of similar age
#83,566
of 280,476 outputs
Outputs of similar age from Methods in molecular biology
#98
of 352 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,338 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 75% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 280,476 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 352 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.