05354nam 2200697Ia 450 991045380550332120200520144314.01-281-92440-79786611924409981-277-266-9(CKB)1000000000555515(EBL)1679435(OCoLC)879023420(SSID)ssj0000301752(PQKBManifestationID)12090539(PQKBTitleCode)TC0000301752(PQKBWorkID)10266026(PQKB)11346691(MiAaPQ)EBC1679435(WSP)00006268(Au-PeEL)EBL1679435(CaPaEBR)ebr10699038(CaONFJC)MIL192440(EXLCZ)99100000000055551520070423d2006 uy 0engur|n|---|||||txtccrLife science data mining[electronic resource] /editors, Stephen Wong, Chung-Sheng LiSingapore ;Hackensack, NJ World Scientificc20061 online resource (388 p.)Science, engineering, and biology informatics ;v. 2.Description based upon print version of record.981-270-065-X 981-270-064-1 Includes bibliographical references and index.CONTENTS ; Preface ; Chapter 1 Survey of Early Warning Systems for Environmental and Public Health Applications ; 1. Introduction ; 2. Disease Surveillance ; 3. Reference Architecture for Model Extraction ; 4. Problem Domain ; 5. Data Sources ; 6. Detection Methods7. Summary and Conclusion References ; Chapter 2 Time-Lapse Cell Cycle Quantitative Data Analysis Using Gaussian Mixture Models ; 1. Introduction ; 2. Material and Feature Extraction ; 3. Problem Statement and Formulation ; 4. Classification Methods ; 5. Experimental Results6. Conclusion Appendix A ; Appendix B ; References ; Chapter 3 Diversity and Accuracy of Data Mining Ensemble ; 1. Introduction ; 2. Ensemble and Diversity ; 3. Probability Analysis ; 4. Coincident Failure Diversity ; 5. Ensemble Accuracy ; 6. Construction of Effective Ensembles7. An Application: Osteoporosis Classification Problem 8. Discussion and Conclusions ; References ; Chapter 4 Integrated Clustering for Microarray Data ; 1. Introduction ; 2. Related Work ; 3. Data Preprocessing ; 4. Integrated Clustering ; 5. Experimental Evaluation6. Conclusions References ; Chapter 5 Complexity and Synchronization of EEG with Parametric Modeling ; 1. Introduction ; 2. TVAR Modeling ; 3. Complexity Measure ; 4. Synchronization Measure ; 5. Conclusions ; ReferencesChapter 6 Bayesian Fusion of Syndromic Surveillance with Sensor Data for Disease Outbreak ClassificationThis timely book identifies and highlights the latest data mining paradigms to analyze, combine, integrate, model and simulate vast amounts of heterogeneous multi-modal, multi-scale data for emerging real-world applications in life science. The cutting-edge topics presented include bio-surveillance, disease outbreak detection, high throughput bioimaging, drug screening, predictive toxicology, biosensors, and the integration of macro-scale bio-surveillance and environmental data with micro-scale biological data for personalized medicine. This collection of works from leading researchers in thScience, engineering, and biology informatics ;v. 2.Computational biologyMethodologyBioinformaticsElectronic books.Computational biologyMethodology.Bioinformatics.570.2856312Wong Stephen T. C871702Li Chung-Sheng1962-943815MiAaPQMiAaPQMiAaPQBOOK9910453805503321Life science data mining2130513UNINA