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Data Mining Techniques for the Life Sciences

Overview of attention for book
Cover of 'Data Mining Techniques for the Life Sciences'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Nucleic Acid Sequence and Structure Databases
  3. Altmetric Badge
    Chapter 2 Genomic Databases and Resources at the National Center for Biotechnology Information
  4. Altmetric Badge
    Chapter 3 Protein Sequence Databases
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    Chapter 4 Protein Structure Databases
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    Chapter 5 Protein Domain Architectures
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    Chapter 6 Thermodynamic Database for Proteins: Features and Applications
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    Chapter 7 Enzyme databases.
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    Chapter 8 Biomolecular Pathway Databases
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    Chapter 9 Databases of Protein–Protein Interactions and Complexes
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    Chapter 10 Proximity Measures for Cluster Analysis
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    Chapter 11 Clustering Criteria and Algorithms
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    Chapter 12 Neural networks.
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    Chapter 13 A User’s Guide to Support Vector Machines
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    Chapter 14 Data Mining Techniques for the Life Sciences
  16. Altmetric Badge
    Chapter 15 Integrated Tools for Biomolecular Sequence-Based Function Prediction as Exemplified by the ANNOTATOR Software Environment
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    Chapter 16 Computational Methods for Ab Initio and Comparative Gene Finding
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    Chapter 17 Sequence and structure analysis of noncoding RNAs.
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    Chapter 18 Conformational Disorder
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    Chapter 19 Protein secondary structure prediction.
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    Chapter 20 Analysis and Prediction of Protein Quaternary Structure
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    Chapter 21 Prediction of Posttranslational Modification of Proteins from Their Amino Acid Sequence
  23. Altmetric Badge
    Chapter 22 Protein Crystallizability
Attention for Chapter 13: A User’s Guide to Support Vector Machines
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

patent
2 patents

Citations

dimensions_citation
29 Dimensions

Readers on

mendeley
866 Mendeley
citeulike
5 CiteULike
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Chapter title
A User’s Guide to Support Vector Machines
Chapter number 13
Book title
Data Mining Techniques for the Life Sciences
Published in
Methods in molecular biology, January 2010
DOI 10.1007/978-1-60327-241-4_13
Pubmed ID
Book ISBNs
978-1-60327-240-7, 978-1-60327-241-4
Authors

Asa Ben-Hur, Jason Weston, Ben-Hur, Asa, Weston, Jason

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 866 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 13 2%
United Kingdom 6 <1%
Germany 5 <1%
Spain 4 <1%
Canada 4 <1%
Brazil 4 <1%
Switzerland 3 <1%
France 3 <1%
Netherlands 2 <1%
Other 19 2%
Unknown 803 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 191 22%
Student > Master 180 21%
Student > Bachelor 96 11%
Researcher 95 11%
Student > Doctoral Student 40 5%
Other 103 12%
Unknown 161 19%
Readers by discipline Count As %
Computer Science 264 30%
Engineering 168 19%
Agricultural and Biological Sciences 47 5%
Biochemistry, Genetics and Molecular Biology 22 3%
Medicine and Dentistry 20 2%
Other 160 18%
Unknown 185 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 27 September 2022.
All research outputs
#4,862,572
of 23,414,653 outputs
Outputs from Methods in molecular biology
#1,420
of 13,324 outputs
Outputs of similar age
#27,703
of 166,564 outputs
Outputs of similar age from Methods in molecular biology
#22
of 121 outputs
Altmetric has tracked 23,414,653 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,324 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 88% 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 166,564 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 121 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.