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Life science data mining /
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,...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor Corporativo: | |
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Singapore ; Hackensack, N.J. :
World Scientific,
Ã2006.
|
| Colección: | Science, engineering, and biology informatics ;
v. 2. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Ch. 1. Survey of early warning systems for environmental and public health applications
- ch. 2. Time-lapse cell cycle quantitative data analysis using gaussian mixture models
- ch. 3. Diversity and accuracy of data mining ensemble
- ch. 4. Integrated clustering for microarray data
- ch. 5. Complexity and synchronization of EEG with parametric modeling
- ch. 6. Bayesian fusion of syndromic surveillance with sensor data for disease outbreak classification
- ch. 7. An evaluation of over-the-counter medication sales for syndromic surveillance
- ch. 8. Collaborative health sentinel
- ch. 9. A multi-modal system approach for drug abuse research and treatment evaluation: information system needs and challenges
- ch. 10. Knowledge representation for versatile hybrid intelligent processing applied in predictive toxicology
- ch. 11. Ensemble classification system implementation for biomedical microarray data
- ch. 12. An automated method for cell phase identification in high throughput time-lapse screens
- ch. 13. Inference of transcriptional regulatory networks based on cancer microarray data
- ch. 14. Data mining in biomedicine
- ch. 15. Mining multilevel association rules from gene ontology and microarray data
- ch. 16. A proposed sensor-configuration and sensitivity analysis of parameters with applications to biosensors.