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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 Data Mining Techniques for the Life Sciences
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    Chapter 2 Protein Structure Databases.
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    Chapter 3 The MIntAct Project and Molecular Interaction Databases.
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    Chapter 4 Applications of Protein Thermodynamic Database for Understanding Protein Mutant Stability and Designing Stable Mutants.
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    Chapter 5 Classification and Exploration of 3D Protein Domain Interactions Using Kbdock.
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    Chapter 6 Data Mining of Macromolecular Structures.
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    Chapter 7 Criteria to Extract High-Quality Protein Data Bank Subsets for Structure Users.
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    Chapter 8 Homology-Based Annotation of Large Protein Datasets.
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    Chapter 9 Data Mining Techniques for the Life Sciences
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    Chapter 10 Improving the Accuracy of Fitted Atomic Models in Cryo-EM Density Maps of Protein Assemblies Using Evolutionary Information from Aligned Homologous Proteins.
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    Chapter 11 Systematic Exploration of an Efficient Amino Acid Substitution Matrix: MIQS.
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    Chapter 12 Promises and Pitfalls of High-Throughput Biological Assays.
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    Chapter 13 Data Mining Techniques for the Life Sciences
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    Chapter 14 Predicting Conformational Disorder.
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    Chapter 15 Classification of Protein Kinases Influenced by Conservation of Substrate Binding Residues.
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    Chapter 16 Spectral-Statistical Approach for Revealing Latent Regular Structures in DNA Sequence.
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    Chapter 17 Protein Crystallizability.
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    Chapter 18 Data Mining Techniques for the Life Sciences
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    Chapter 19 Data Mining Techniques for the Life Sciences
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    Chapter 20 Functional Analysis of Metabolomics Data.
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    Chapter 21 Data Mining Techniques for the Life Sciences
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    Chapter 22 A Broad Overview of Computational Methods for Predicting the Pathophysiological Effects of Non-synonymous Variants.
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    Chapter 23 Recommendation Techniques for Drug-Target Interaction Prediction and Drug Repositioning.
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    Chapter 24 Protein Residue Contacts and Prediction Methods.
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    Chapter 25 The Recipe for Protein Sequence-Based Function Prediction and Its Implementation in the ANNOTATOR Software Environment.
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    Chapter 26 Data Mining Techniques for the Life Sciences
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    Chapter 27 Data Mining Techniques for the Life Sciences
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

blogs
2 blogs
twitter
42 tweeters
googleplus
1 Google+ user

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
26 Mendeley
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Title
Data Mining Techniques for the Life Sciences
Published by
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3572-7
ISBNs
978-1-4939-3570-3, 978-1-4939-3572-7
Editors

Oliviero Carugo, Frank Eisenhaber

Twitter Demographics

The data shown below were collected from the profiles of 42 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 23%
Researcher 4 15%
Student > Ph. D. Student 4 15%
Student > Bachelor 3 12%
Other 2 8%
Other 1 4%
Unknown 6 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 23%
Agricultural and Biological Sciences 4 15%
Computer Science 2 8%
Engineering 2 8%
Mathematics 1 4%
Other 5 19%
Unknown 6 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 35. 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 11 December 2020.
All research outputs
#914,149
of 21,735,696 outputs
Outputs from Methods in molecular biology
#77
of 12,487 outputs
Outputs of similar age
#17,228
of 281,037 outputs
Outputs of similar age from Methods in molecular biology
#1
of 5 outputs
Altmetric has tracked 21,735,696 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,487 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 99% 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 281,037 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them