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Pattern Recognition in Bioinformatics

Overview of attention for book
Cover of 'Pattern Recognition in Bioinformatics'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Robust Community Detection Methods with Resolution Parameter for Complex Detection in Protein Protein Interaction Networks
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    Chapter 2 Machine Learning Scoring Functions Based on Random Forest and Support Vector Regression
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    Chapter 3 A Genetic Algorithm for Scale-Based Translocon Simulation
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    Chapter 4 A Framework of Gene Subset Selection Using Multiobjective Evolutionary Algorithm
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    Chapter 5 Multiple Tree Alignment with Weights Applied to Carbohydrates to Extract Binding Recognition Patterns
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    Chapter 6 A Unified Adaptive Co-identification Framework for High-D Expression Data
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    Chapter 7 Protein Clustering on a Grassmann Manifold
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    Chapter 8 Improving the Portability and Performance of jViz.RNA – A Dynamic RNA Visualization Software
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    Chapter 9 Pattern Recognition in Bioinformatics
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    Chapter 10 An Open Framework for Extensible Multi-stage Bioinformatics Software
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    Chapter 11 An Algorithm to Assemble Gene-Protein-Reaction Associations for Genome-Scale Metabolic Model Reconstruction
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    Chapter 12 A Machine Learning and Chemometrics Assisted Interpretation of Spectroscopic Data – A NMR-Based Metabolomics Platform for the Assessment of Brazilian Propolis
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    Chapter 13 Principal Component Analysis for Bacterial Proteomic Analysis
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    Chapter 14 Pattern Recognition in Bioinformatics
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    Chapter 15 Cascading Discriminant and Generative Models for Protein Secondary Structure Prediction
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    Chapter 16 Improvement of the Protein–Protein Docking Prediction by Introducing a Simple Hydrophobic Interaction Model: An Application to Interaction Pathway Analysis
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    Chapter 17 Representation of Protein Secondary Structure Using Bond-Orientational Order Parameters
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    Chapter 18 Diagnose the Premalignant Pancreatic Cancer Using High Dimensional Linear Machine
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    Chapter 19 Predicting V(D)J Recombination Using Conditional Random Fields
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    Chapter 20 A Simple Genetic Algorithm for Biomarker Mining
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    Chapter 21 Finding Conserved Regions in Protein Structures Using Support Vector Machines and Structure Alignment
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    Chapter 22 Aligning Discovered Patterns from Protein Family Sequences
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    Chapter 23 Application of the Burrows-Wheeler Transform for Searching for Approximate Tandem Repeats
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    Chapter 24 Pattern Recognition for Subfamily Level Classification of GPCRs Using Motif Distillation and Distinguishing Power Evaluation
Overall attention for this book and its chapters
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

twitter
2 X users
patent
2 patents

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
1 Mendeley
Summary X Patents Dimensions citations
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Title
Pattern Recognition in Bioinformatics
Published by
Lecture notes in computer science, January 2012
DOI 10.1007/978-3-642-34123-6
ISBNs
978-3-64-234122-9, 978-3-64-234123-6
Authors

Shibuya, Tetsuo, Kashima, Hisashi, Sese, Jun, Ahmad, Shandar

Editors

Tetsuo Shibuya, Hisashi Kashima, Jun Sese, Shandar Ahmad

View on publisher site
X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 100%
Readers by discipline Count As %
Computer Science 1 100%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 15 August 2023.
All research outputs
#6,804,920
of 24,384,776 outputs
Outputs from Lecture notes in computer science
#2,083
of 8,152 outputs
Outputs of similar age
#59,034
of 252,131 outputs
Outputs of similar age from Lecture notes in computer science
#124
of 489 outputs
Altmetric has tracked 24,384,776 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 8,152 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has gotten more attention than average, scoring higher than 74% 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 252,131 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 76% of its contemporaries.
We're also able to compare this research output to 489 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 74% of its contemporaries.

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