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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): Li, Jinyan [editor.] | Yang, Qiang [editor.] | Tan, Ah-Hwee [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Bioinformatics: 3916Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2006Edition: 1st ed. 2006.Description: VIII, 155 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540331056.Subject(s): Artificial intelligence | Database management | Information storage and retrieval systems | Bioinformatics | Computer science -- Mathematics | Mathematical statistics | Medical informatics | Artificial Intelligence | Database Management | Information Storage and Retrieval | Bioinformatics | Probability and Statistics in Computer Science | Health InformaticsAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
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 Nature eBook
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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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