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Data Mining for Biomedical Applications [electronic resource] : PAKDD 2006 Workshop, BioDM 2006, Singapore, April 9, 2006. Proceedings / edited by Jinyan Li, Qiang Yang, Ah-Hwee Tan.

Contributor(s): Material type: TextTextSeries: Lecture Notes in Computer Science ; 3916Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006Description: VIII, 155 p. Also available online. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540331056
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 005.74 23
LOC classification:
  • QA76.9.D3
Online resources:
Contents:
Keynote Talk -- Exploiting Indirect Neighbours and Topological Weight to Predict Protein Function from Protein-Protein Interactions -- Database and Search -- A Database Search Algorithm for Identification of Peptides with Multiple Charges Using Tandem Mass Spectrometry -- Filtering Bio-sequence Based on Sequence Descriptor -- Automatic Extraction of Genomic Glossary Triggered by Query -- Frequent Subsequence-Based Protein Localization -- Bio Data Clustering -- gTRICLUSTER: A More General and Effective 3D Clustering Algorithm for Gene-Sample-Time Microarray Data -- Automatic Orthologous-Protein-Clustering from Multiple Complete-Genomes by the Best Reciprocal BLAST Hits -- A Novel Clustering Method for Analysis of Gene Microarray Expression Data -- Heterogeneous Clustering Ensemble Method for Combining Different Cluster Results -- In-silico Diagnosis -- Rule Learning for Disease-Specific Biomarker Discovery from Clinical Proteomic Mass Spectra -- Machine Learning Techniques and Chi-Square Feature Selection for Cancer Classification Using SAGE Gene Expression Profiles -- Generation of Comprehensible Hypotheses from Gene Expression Data -- Classification of Brain Glioma by Using SVMs Bagging with Feature Selection -- Missing Value Imputation Framework for Microarray Significant Gene Selection and Class Prediction -- Informative MicroRNA Expression Patterns for Cancer Classification.
In: Springer eBooks
Item type: E-BOOKS
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Keynote Talk -- Exploiting Indirect Neighbours and Topological Weight to Predict Protein Function from Protein-Protein Interactions -- Database and Search -- A Database Search Algorithm for Identification of Peptides with Multiple Charges Using Tandem Mass Spectrometry -- Filtering Bio-sequence Based on Sequence Descriptor -- Automatic Extraction of Genomic Glossary Triggered by Query -- Frequent Subsequence-Based Protein Localization -- Bio Data Clustering -- gTRICLUSTER: A More General and Effective 3D Clustering Algorithm for Gene-Sample-Time Microarray Data -- Automatic Orthologous-Protein-Clustering from Multiple Complete-Genomes by the Best Reciprocal BLAST Hits -- A Novel Clustering Method for Analysis of Gene Microarray Expression Data -- Heterogeneous Clustering Ensemble Method for Combining Different Cluster Results -- In-silico Diagnosis -- Rule Learning for Disease-Specific Biomarker Discovery from Clinical Proteomic Mass Spectra -- Machine Learning Techniques and Chi-Square Feature Selection for Cancer Classification Using SAGE Gene Expression Profiles -- Generation of Comprehensible Hypotheses from Gene Expression Data -- Classification of Brain Glioma by Using SVMs Bagging with Feature Selection -- Missing Value Imputation Framework for Microarray Significant Gene Selection and Class Prediction -- Informative MicroRNA Expression Patterns for Cancer Classification.

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The Institute of Mathematical Sciences, Chennai, India