Data Mining and Bioinformatics (eBook, PDF)

First International Workshop, VDMB 2006, Seoul, Korea, September 11, 2006, Revised Selected Papers
Redaktion: Dalkilic, Mehmet M; Yang, Jiong; Kim, Sun

• Format: PDF

Produktbeschreibung

This book constitutes the thoroughly refereed post-proceedings of the First VLDB 2006 International Workshop on Data Mining and Bioinformatics, VDMB 2006, held in Seoul, Korea in September 2006 in conjunction with VLDB 2006. The 15 revised full papers cover various topics in the areas of microarray data analysis, bioinformatics system and text retrieval, application of gene expression data, and sequence analysis.

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Produktdetails

• Verlag: Springer-Verlag GmbH
• Seitenzahl: 198
• Erscheinungstermin: 28. November 2006
• Englisch
• ISBN-13: 9783540689713
• Artikelnr.: 44221727

Inhaltsangabe

Bioinformatics at Microsoft Research.- A Novel Approach for Effective Learning of Cluster Structures with Biological Data Applications.- Subspace Clustering of Microarray Data Based on Domain Transformation.- Bayesian Hierarchical Models for Serial Analysis of Gene Expression.- Applying Gaussian Distribution-Dependent Criteria to Decision Trees for High-Dimensional Microarray Data.- A Biological Text Retrieval System Based on Background Knowledge and User Feedback.- Automatic Annotation of Protein Functional Class from Sparse and Imbalanced Data Sets.- Bioinformatics Data Source Integration Based on Semantic Relationships Across Species.- An Efficient Storage Model for the SBML Documents Using Object Databases.- Identification of Phenotype-Defining Gene Signatures Using the Gene-Pair Matrix Based Clustering.- TP+Close: Mining Frequent Closed Patterns in Gene Expression Datasets.- Exploring Essential Attributes for Detecting MicroRNA Precursors from Background Sequences.- A Gene Structure Prediction Program Using Duration HMM.- An Approximate de Bruijn Graph Approach to Multiple Local Alignment and Motif Discovery in Protein Sequences.- Discovering Consensus Patterns in Biological Databases.- Comparison of Modularization Methods in Application to Different Biological Networks.