Life Science Data Mining

Häftad, Engelska, 2007

Del 2 i serien Science, Engineering, And Biology Informatics

910 kr

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2007-01-04
Mått:226 x 158 x 19 mm
Vikt:556 g
Format:Häftad
Språk:Engelska
Serie:Science, Engineering, And Biology Informatics
Antal sidor:388
Förlag:World Scientific Publishing Co Pte Ltd
ISBN:9789812700650

Utforska kategorier

Biologi inom Naturvetenskap och teknik
Databaser inom Data och IT

Innehållsförteckning

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.