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Computational Intelligence Methods for Bioinformatics and Biostatistics

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Cover of 'Computational Intelligence Methods for Bioinformatics and Biostatistics'

Table of Contents

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    Book Overview
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    Chapter 1 Coarse-Grained Modeling of the HIV–1 Protease Binding Mechanisms: I. Targeting Structural Flexibility of the Protease Flaps and Implications for Drug Design
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    Chapter 2 Coarse-Grained Modeling of the HIV–1 Protease Binding Mechanisms: II. Folding Inhibition
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    Chapter 3 Unsupervised Stability-Based Ensembles to Discover Reliable Structures in Complex Bio-molecular Data
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    Chapter 4 Comparative In Silico Evaluation of MYB Transcription Factors in Eucalyptus, Sugarcane and Rice Transcriptomes
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    Chapter 5 Building Maps of Drugs Mode-of-Action from Gene Expression Data
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    Chapter 6 In Silico Evaluation of Osmoprotectants in Eucalyptus Transcriptome
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    Chapter 7 Mining Association Rule Bases from Integrated Genomic Data and Annotations
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    Chapter 8 Stability and Performances in Biclustering Algorithms
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    Chapter 9 Splice Site Prediction Using Artificial Neural Networks
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    Chapter 10 Interval Length Analysis in Multi Layer Model
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    Chapter 11 A Multivariate Algorithm for Gene Selection Based on the Nearest Neighbor Probability
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    Chapter 12 Control of Cellular Glycolysis by Perturbations in the Glucose Influx
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    Chapter 13 Curating a Large-Scale Regulatory Network by Evaluating Its Consistency with Expression Datasets
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    Chapter 14 Spatial Clustering of Molecular Dynamics Trajectories in Protein Unfolding Simulations
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    Chapter 15 Clustering Bacteria Species Using Neural Gas: Preliminary Study
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    Chapter 16 A New Linear Initialization in SOM for Biomolecular Data
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    Chapter 17 3D Volume Reconstruction and Biometric Analysis of Fetal Brain from MR Images
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    Chapter 18 Searching for Glycomics Role in Stem Cell Development
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    Chapter 19 A New Protein Representation Based on Fragment Contacts: Towards an Improvement of Contact Maps Predictions
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    Chapter 20 Analysis of Kernel Based Protein Classification Strategies Using Pairwise Sequence Alignment Measures
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    Chapter 21 Topology Preserving Neural Networks for Peptide Design in Drug Discovery
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    Chapter 22 A Machine Learning Approach to Mass Spectra Classification with Unsupervised Feature Selection
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    Chapter 23 Liver i-Biopsy TM and the Corresponding Intelligent Fibrosis Scoring Systems: i-Metavir F and i-Ishak F
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    Chapter 24 An Extension of the TIGR M4 Suite to Preprocess and Visualize Affymetrix Binary Files
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    Chapter 25 A Supervised Learning Technique and Its Applications to Computational Biology
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    Chapter 26 A Visualization ToolKit Based Application for Representing Macromolecular Surfaces
Attention for Chapter 5: Building Maps of Drugs Mode-of-Action from Gene Expression Data
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Chapter title
Building Maps of Drugs Mode-of-Action from Gene Expression Data
Chapter number 5
Book title
Computational Intelligence Methods for Bioinformatics and Biostatistics
Published by
Springer, Berlin, Heidelberg, October 2008
DOI 10.1007/978-3-642-02504-4_5
Book ISBNs
978-3-64-202503-7, 978-3-64-202504-4
Authors

Francesco Iorio, Roberto Tagliaferri, Diego di Bernardo

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 40%
Professor > Associate Professor 1 20%
Student > Postgraduate 1 20%
Unknown 1 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 20%
Chemistry 1 20%
Engineering 1 20%
Unknown 2 40%