↓ Skip to main content

Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

Overview of attention for book
Cover of 'Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Association Study between Gene Expression and Multiple Relevant Phenotypes with Cluster Analysis.
  3. Altmetric Badge
    Chapter 2 Gaussian Graphical Models to Infer Putative Genes Involved in Nitrogen Catabolite Repression in S. cerevisiae
  4. Altmetric Badge
    Chapter 3 Chronic Rat Toxicity Prediction of Chemical Compounds Using Kernel Machines
  5. Altmetric Badge
    Chapter 4 Simulating Evolution of Drosophila Melanogaster Ebony Mutants Using a Genetic Algorithm
  6. Altmetric Badge
    Chapter 5 Microarray Biclustering: A Novel Memetic Approach Based on the PISA Platform
  7. Altmetric Badge
    Chapter 6 F-score with Pareto Front Analysis for Multiclass Gene Selection
  8. Altmetric Badge
    Chapter 7 A Hierarchical Classification Ant Colony Algorithm for Predicting Gene Ontology Terms
  9. Altmetric Badge
    Chapter 8 Conquering the Needle-in-a-Haystack: How Correlated Input Variables Beneficially Alter the Fitness Landscape for Neural Networks
  10. Altmetric Badge
    Chapter 9 Optimal Use of Expert Knowledge in Ant Colony Optimization for the Analysis of Epistasis in Human Disease
  11. Altmetric Badge
    Chapter 10 On the Efficiency of Local Search Methods for the Molecular Docking Problem
  12. Altmetric Badge
    Chapter 11 A Comparison of Genetic Algorithms and Particle Swarm Optimization for Parameter Estimation in Stochastic Biochemical Systems
  13. Altmetric Badge
    Chapter 12 Guidelines to Select Machine Learning Scheme for Classification of Biomedical Datasets
  14. Altmetric Badge
    Chapter 13 Evolutionary Approaches for Strain Optimization Using Dynamic Models under a Metabolic Engineering Perspective
  15. Altmetric Badge
    Chapter 14 Clustering Metagenome Short Reads Using Weighted Proteins
  16. Altmetric Badge
    Chapter 15 A Memetic Algorithm for Phylogenetic Reconstruction with Maximum Parsimony
  17. Altmetric Badge
    Chapter 16 Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
  18. Altmetric Badge
    Chapter 17 Refining Genetic Algorithm Based Fuzzy Clustering through Supervised Learning for Unsupervised Cancer Classification
Attention for Chapter 8: Conquering the Needle-in-a-Haystack: How Correlated Input Variables Beneficially Alter the Fitness Landscape for Neural Networks
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

Mentioned by

blogs
1 blog

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
27 Mendeley
citeulike
1 CiteULike
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.
Chapter title
Conquering the Needle-in-a-Haystack: How Correlated Input Variables Beneficially Alter the Fitness Landscape for Neural Networks
Chapter number 8
Book title
Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Published in
Lecture notes in computer science, April 2009
DOI 10.1007/978-3-642-01184-9_8
Book ISBNs
978-3-64-201183-2, 978-3-64-201184-9
Authors

Stephen D. Turner, Marylyn D. Ritchie, William S. Bush

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 11%
Italy 1 4%
Malaysia 1 4%
United Kingdom 1 4%
Brazil 1 4%
Unknown 20 74%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 22%
Student > Doctoral Student 4 15%
Student > Master 4 15%
Professor > Associate Professor 4 15%
Researcher 4 15%
Other 4 15%
Unknown 1 4%
Readers by discipline Count As %
Computer Science 12 44%
Agricultural and Biological Sciences 6 22%
Engineering 2 7%
Biochemistry, Genetics and Molecular Biology 1 4%
Economics, Econometrics and Finance 1 4%
Other 3 11%
Unknown 2 7%
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 March 2013.
All research outputs
#5,716,386
of 22,703,044 outputs
Outputs from Lecture notes in computer science
#1,872
of 8,124 outputs
Outputs of similar age
#26,880
of 93,678 outputs
Outputs of similar age from Lecture notes in computer science
#6
of 21 outputs
Altmetric has tracked 22,703,044 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 8,124 research outputs from this source. They receive a mean Attention Score of 5.0. This one has done well, scoring higher than 76% 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 93,678 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 21 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 71% of its contemporaries.