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Advances in Bioinformatics and Computational Biology

Overview of attention for book
Cover of 'Advances in Bioinformatics and Computational Biology'

Table of Contents

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    Book Overview
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    Chapter 1 Genotype Tagging with Limited Overfitting
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    Chapter 2 Constraint Programming Models for Transposition Distance Problem
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    Chapter 3 Comparison of Spectra in Unsequenced Species
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    Chapter 4 BiHEA: A Hybrid Evolutionary Approach for Microarray Biclustering
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    Chapter 5 Using Supervised Complexity Measures in the Analysis of Cancer Gene Expression Data Sets
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    Chapter 6 Quantitative Improvements in cDNA Microarray Spot Segmentation
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    Chapter 7 SOM-PORTRAIT: Identifying Non-coding RNAs Using Self-Organizing Maps
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    Chapter 8 Automatic Classification of Enzyme Family in Protein Annotation
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    Chapter 9 Representations for Evolutionary Algorithms Applied to Protein Structure Prediction Problem Using HP Model
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    Chapter 10 Comparing Methods for Multilabel Classification of Proteins Using Machine Learning Techniques
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    Chapter 11 Comparative Study of Classification Algorithms Using Molecular Descriptors in Toxicological DataBases
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    Chapter 12 Influence of Antigenic Mutations in Time Evolution of the Immune Memory – A Dynamic Modeling
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    Chapter 13 FReDD: Supporting Mining Strategies through a Flexible-Receptor Docking Database
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    Chapter 14 A Wide Antimicrobial Peptides Search Method Using Fuzzy Modeling
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    Chapter 15 Identification of Proteins from Tuberculin Purified Protein Derivative (PPD) with Potential for TB Diagnosis Using Bioinformatics Analysis
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    Chapter 16 Mapping HIV-1 Subtype C gp120Epitopes Using a Bioinformatic Approach
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    Chapter 17 MHC: Peptide Analysis: Implications on the Immunogenicity of Hantaviruses’ N protein
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    Chapter 18 An Ontology to Integrate Transcriptomics and Interatomics Data Involved in Gene Pathways of Genome Stability
Overall attention for this book and its chapters
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Mentioned by

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1 X user

Readers on

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49 Mendeley
Summary X
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Title
Advances in Bioinformatics and Computational Biology
Published by
ADS, July 2009
DOI 10.1007/978-3-642-03223-3
ISBNs
978-3-64-203222-6, 978-3-64-203223-3
Editors

Guimarães, Katia S., Panchenko, Anna, Przytycka, Teresa M.

View on publisher site
X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 3 6%
Portugal 1 2%
Unknown 45 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 22%
Student > Master 5 10%
Student > Bachelor 4 8%
Researcher 4 8%
Professor 2 4%
Other 5 10%
Unknown 18 37%
Readers by discipline Count As %
Computer Science 11 22%
Agricultural and Biological Sciences 9 18%
Biochemistry, Genetics and Molecular Biology 3 6%
Chemistry 2 4%
Arts and Humanities 1 2%
Other 3 6%
Unknown 20 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 21 June 2014.
All research outputs
#18,601,965
of 23,041,514 outputs
Outputs from ADS
#31,583
of 37,451 outputs
Outputs of similar age
#102,203
of 111,167 outputs
Outputs of similar age from ADS
#340
of 371 outputs
Altmetric has tracked 23,041,514 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 37,451 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 8th percentile – i.e., 8% of its peers scored the same or lower than it.
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 111,167 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 371 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.

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