↓ Skip to main content

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

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 (95th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

blogs
2 blogs
twitter
40 X users
googleplus
1 Google+ user

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
26 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
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

X Demographics

X Demographics

The data shown below were collected from the profiles of 40 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 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

Attention Score in Context

This research output has an Altmetric Attention Score of 34. 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
#1,156,594
of 25,305,422 outputs
Outputs from Methods in molecular biology
#108
of 14,173 outputs
Outputs of similar age
#19,961
of 406,423 outputs
Outputs of similar age from Methods in molecular biology
#17
of 1,465 outputs
Altmetric has tracked 25,305,422 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 14,173 research outputs from this source. They receive a mean Attention Score of 3.5. 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 406,423 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 95% of its contemporaries.
We're also able to compare this research output to 1,465 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.