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Multiple Information Sources Cooperative Learning

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Cover of 'Multiple Information Sources Cooperative Learning'

Table of Contents

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    Book Overview
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    Chapter 1 Association Analysis Techniques for Bioinformatics Problems
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    Chapter 2 Analyzing and Interrogating Biological Networks (Abstract)
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    Chapter 3 From Architecture to Function (and Back) in Bio-networks
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    Chapter 4 A New Machine Learning Approach for Protein Phosphorylation Site Prediction in Plants
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    Chapter 5 Assembly of Large Genomes from Paired Short Reads
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    Chapter 6 Amino Acid Classification and Hash Seeds for Homology Search
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    Chapter 7 Genotype and Haplotype Reconstruction from Low-Coverage Short Sequencing Reads
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    Chapter 8 Gene Networks Viewed through Two Models
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    Chapter 9 Identifying Evolutionarily Conserved Protein Interaction Modules Using GraphHopper
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    Chapter 10 The 2-Interval Pattern Matching Problems and Its Application to ncRNA Scanning
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    Chapter 11 RNA Pseudoknot Folding through Inference and Identification Using TAG RNA
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    Chapter 12 Comparing Bacterial Genomes by Searching Their Common Intervals
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    Chapter 13 Generalized Binary Tanglegrams: Algorithms and Applications
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    Chapter 14 Three-Dimensional Multimodality Modelling by Integration of High-Resolution Interindividual Atlases and Functional MALDI-IMS Data
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    Chapter 15 Detecting Motifs in a Large Data Set: Applying Probabilistic Insights to Motif Finding
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    Chapter 16 A Biclustering Method to Discover Co-regulated Genes Using Diverse Gene Expression Datasets
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    Chapter 17 Computational Protocol for Screening GPI-anchored Proteins
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    Chapter 18 Towards Large-Scale Molecular Dynamics Simulations on Graphics Processors
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    Chapter 19 An Agent-Based Model of Solid Tumor Progression
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    Chapter 20 Deciphering Drug Action and Escape Pathways: An Example on Nasopharyngeal Carcinoma
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    Chapter 21 Selection of Multiple SNPs in Case-Control Association Study Using a Discretized Network Flow Approach
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    Chapter 22 Biclustering Expression Data Based on Expanding Localized Substructures
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    Chapter 23 Constrained Fisher Scores Derived from Interaction Profile Hidden Markov Models Improve Protein to Protein Interaction Prediction
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    Chapter 24 Improving Protein Localization Prediction Using Amino Acid Group Based Physichemical Encoding
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    Chapter 25 The Impact of Gene Selection on Imbalanced Microarray Expression Data
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    Chapter 26 Spatial Information and Boolean Genetic Regulatory Networks
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    Chapter 27 Modeling of Genetic Regulatory Network in Stochastic π -Calculus
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    Chapter 28 fMRI Activation Detection by MultiScale Hidden Markov Model
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    Chapter 29 cnF2freq : Efficient Determination of Genotype and Haplotype Probabilities in Outbred Populations Using Markov Models
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    Chapter 30 A Comprehensive Analysis Workflow for Genome-Wide Screening Data from ChIP-Sequencing Experiments
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    Chapter 31 A Fitness Distance Correlation Measure for Evolutionary Trees
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    Chapter 32 Alignment and Analysis of Closely Related Genomes
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    Chapter 33 Computational Prediction of Genes Translationally Regulated by Cytoplasmic Polyadenylation Elements
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    Chapter 34 Multiple Sequence Alignment System for Pyrosequencing Reads
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    Chapter 35 A Bayesian Approach to High-Throughput Biological Model Generation
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    Chapter 36 Parallel Selection of Informative Genes for Classification
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    Chapter 37 Simulation Methods in Uncovering New Regulatory Mechanisms in Signaling Pathways
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    Chapter 38 GridSPiM: A Framework for Simple Locality and Containment in the Stochastic π-Calculus
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    Chapter 39 Mutual Information Based Extrinsic Similarity for Microarray Analysis
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    Chapter 40 Graph Spectral Approach for Identifying Protein Domains
Attention for Chapter 6: Amino Acid Classification and Hash Seeds for Homology Search
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Chapter title
Amino Acid Classification and Hash Seeds for Homology Search
Chapter number 6
Book title
Bioinformatics and Computational Biology
Published by
Springer, Berlin, Heidelberg, January 2009
DOI 10.1007/978-3-642-00727-9_6
Book ISBNs
978-3-64-200726-2, 978-3-64-200727-9
Authors

Weiming Li, Bin Ma, Kaizhong Zhang, Li, Weiming, Ma, Bin, Zhang, Kaizhong

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 25%
Professor > Associate Professor 1 25%
Researcher 1 25%
Unknown 1 25%
Readers by discipline Count As %
Computer Science 2 50%
Agricultural and Biological Sciences 1 25%
Unknown 1 25%