High-Dimensional Data Analysis in Cancer Research

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Li, Xiaochun (Επιμελητής έκδοσης), Xu, Ronghui (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: New York, NY : Springer New York, 2009.
• Σειρά: Applied Bioinformatics and Biostatistics in Cancer Research
• Θέματα: Medicine.; Cancer research.; Human genetics.; Laboratory medicine.; Medical microbiology.; Molecular biology.; Neurosciences.; Biomedicine.; Cancer Research.; Laboratory Medicine.; Human Genetics.; Medical Microbiology.; Molecular Medicine.

With the advent of high-throughput technologies, various types of high-dimensional data have been generated in recent years for the understanding of biological processes, especially processes that relate to disease occurrence or management of cancer. Motivated by these important applications in canc...

Πίνακας περιεχομένων:

• On the Role and Potential of High-Dimensional Biologic Data in Cancer Research
• Variable selection in regression - estimation, prediction,sparsity, inference
• Multivariate Nonparametric Regression
• Risk Estimation
• Tree-Based Methods
• Support Vector Machine Classification for High Dimensional Microarray Data Analysis, With Applications in Cancer Research
• Bayesian Approaches: Nonparametric Bayesian Analysis of Gene Expression Data.