Data Mining for Biomedical Applications [electronic resource] : PAKDD 2006 Workshop, BioDM 2006, Singapore, April 9, 2006, Proceedings /
Material type: TextSeries: Lecture Notes in Bioinformatics ; 3916Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2006Edition: 1st ed. 2006Description: VIII, 155 p. online resourceContent type:- text
- computer
- online resource
- 9783540331056
- 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 Informatics
- 006.3 23
- Q334-342
- TA347.A78
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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