Life Science Data Mining.
Title:
Life Science Data Mining.
Author:
Wong, Stephen.
ISBN:
9789812772664
Personal Author:
Physical Description:
1 online resource (388 pages)
Series:
Science, Engineering, and Biology Informatics ; v.2
Science, Engineering, and Biology Informatics
Contents:
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 Methods -- 7. 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 Results -- 6. 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 Ensembles -- 7. 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 Evaluation -- 6. 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 -- References -- Chapter 6 Bayesian Fusion of Syndromic Surveillance with Sensor Data for Disease Outbreak Classification -- 1. Introduction -- 2. Approach -- 3. Results -- 4. Summary and Conclusions -- References -- Chapter 7 An Evaluation of Over-the-Counter Medication Sales for Syndromic Surveillance -- 1. Introduction -- 2. Background and Related Work -- 3. Data -- 4. Approaches -- 5. Experiments -- 6. Conclusions and Future Work -- References.
Chapter 8 Collaborative Health Sentinel -- 1. Introduction -- 2. Infectious Disease and Existing Health Surveillance Programs -- 3. Elements of the Collaborative Health Sentinel (CHS) System -- 4. Interaction with the Health Information Technology(HCIT) World -- 5. Conclusion -- References -- Appendix A - HL7 -- Chapter 9 A Multi-Modal System Approach for Drug Abuse Research and Treatment Evaluation: Information Systems Needs and Challenges -- 1. Introduction -- 2. Context -- 3. Possible System Structure -- 4. Challenges in System Development and Implementation -- 5. Summary -- References -- Chapter 10 Knowledge Representation for Versatile Hybrid Intelligent Processing Applied in Predictive Toxicology -- 1. Introduction -- 2. Hybrid Intelligent Techniques for Predictive Toxicology Knowledge Representation -- 3. XML Schemas for Knowledge Representation and Processing in AI and Predictive Toxicology -- 4. Towards a Standard for Chemical Data Representation in Predictive Toxicology -- 5. Hybrid Intelligent Systems for Knowledge Representation in Predictive Toxicology -- 6. A Case Study -- 7. Conclusions -- References -- Chapter 11 Ensemble Classification System Implementation for Biomedical Microarray Data -- 1. Introduction -- 2. Background -- 3. Ensemble Classification System (ECS) Design -- 4. Experiments -- 5. Conclusion and Further Work -- References -- Chapter 12 An Automated Method for Cell Phase Identification in High Throughput Time-Lapse Screens -- 1. Introduction -- 2. Nuclei Segmentation and Tracking -- 3. Cell Phase Identification -- 4. Experimental Results -- 5. Conclusion -- References -- Chapter 13 Inference of Transcriptional Regulatory Networks Based on Cancer Microarray Data -- 1. Introduction -- 2. Subnetworks and Transcriptional Regulatory Networks Inference.
3. Multinomial Probit Regression with Baysian Gene Selection -- 4. Network Construction Based on Clustering and Predictor Design -- 5. Concluding Remarks -- References -- Chapter 14 Data Mining in Biomedicine -- 1. Introduction -- 2. Predictive Model Construction -- 3. Validation -- 4. Impact Analysis -- 5. Summary -- References -- Chapter 15 Mining Multilevel Association Rules from Gene Ontology and Microarray Data -- 1. Introduction -- 2. Proposed Methods -- 3. The MAGO Algorithm -- 4. Experimental Results -- 5. Concluding Remarks -- References -- Chapter 16 A Proposed Sensor-Configuration and Sensitivity Analysis of Parameters with Applications to Biosensors -- 1. Introduction -- 2. Sensor-System Configuration -- 3. Optical Biosensors -- 4. Discussion -- 5. Conclusion -- References -- Epilogue -- References -- Index.
Abstract:
This 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 the field offers readers an exceptional start in these areas. Sample Chapter(s). Chapter 1: Survey of Early Warning Systems for Environmental and Public Health Applications (211 KB). Contents: Survey of Early Warning Systems for Environmental and Public Health Applications; Time-Lapse Cell Cycle Quantitative Data Analysis Using Gaussian Mixture Models; Diversity and Accuracy of Data Mining Ensemble; Integrated Clustering for Microarray Data; Complexity and Synchronization of EEG with Parametric Modeling; Bayesian Fusion of Syndromic Surveillance with Sensor Data for Disease Outbreak Classification; An Evaluation of Over-the-Counter Medication Sales for Syndromic Surveillance; Collaborative Health Sentinel; A Multi-Modal System Approach for Drug Abuse Research and Treatment Evaluation: Information Systems Needs and Challenges; Knowledge Representation for Versatile Hybrid Intelligent Processing Applied in Predictive Toxicology; Ensemble Classification System Implementation for Biomedical Microarray Data; An Automated Method for Cell Phase Identification in High Throughput Time-Lapse Screens; Inference of Transcriptional Regulatory Networks Based on Cancer Microarray Data; Data Mining in Biomedicine; Mining Multilevel Association Rules from Gene Ontology and
Microarray Data; A Proposed Sensor-Configuration and Sensitivity Analysis of Parameters with Applications to Biosensors. Readership: Graduate students, academics, and engineering and IT professionals.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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