Data Mining for Biomedical Applications PAKDD 2006 Workshop, BioDM 2006, Singapore, April 9, 2006. Proceedings /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Li, Jinyan (Επιμελητής έκδοσης), Yang, Qiang (Επιμελητής έκδοσης), Tan, Ah-Hwee (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006.
• Σειρά: Lecture Notes in Computer Science, 3916
• Θέματα: Computer science.; Health informatics.; Mathematical statistics.; Database management.; Information storage and retrieval.; Artificial intelligence.; Bioinformatics.; Computer Science.; Artificial Intelligence (incl. Robotics).; Database Management.; Information Storage and Retrieval.; Probability and Statistics in Computer Science.; Health Informatics.

Πίνακας περιεχομένων:

• 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.