Numerous fascinating breakthroughs in biotechnology have generated large volumes and diverse types of high throughput data that demand the development of efficient and appropriate tools in computational statistics integrated with biological knowledge and computational algorithms. This volume collects contributed chapters from leading researchers to survey the many active research topics and promote the visibility of this research area. This volume is intended to provide an introductory and reference book for students and researchers who are interested in the recent developments of computational statistics in computational biology.
Rezensionen / Stimmen
"This book puts together a nice collection of statistical methods covering a wide range of research topics in computational biology. . I can recommend the book as an overview on methods applied in computational biology for readers already experienced in basic computational statistics. Especially readers interested in systems biology topics will find a comprehensive summary of methods." (Marc Zapatka, Biometrical Journal, Vol. 55 (4), 2013)
Reihe
Auflage
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für Beruf und Forschung
Professional/practitioner
Illustrationen
Maße
Höhe: 235 mm
Breite: 155 mm
Dicke: 35 mm
Gewicht
ISBN-13
978-3-642-26827-4 (9783642268274)
DOI
10.1007/978-3-642-16345-6
Schweitzer Klassifikation
Henry Horng-Shing Lu is a Professor at the National Chiao Tung University's Institute of Statistics in Taiwan. He is also the Chairman of the University's Interdisciplinary Sciences Degree Program in the College of Science. His research interests are in the field of interdisciplinary studies related to statistics, medical images and bioinformatics.Bernhard Schölkopf is a member of the Max Planck Society and Director of the Max Planck Institute for Biological Cybernetics. He is also an Honorary Professor of Machine Learning at the Technical University Berlin. His scientific interests are in the field of inference from empirical data; in particular, in machine learning methods for extracting statistical and causal regularities.Hongyu Zhao is a Professor of Biostatistics, Statistics, and Genetics at Yale University, where he also serves as the Director of the Center for Statistical Genomics and Protoemics. His research interests include statistical genomics, computational biology, statistical proteomics, risk prediction, high dimensional data analysis, and network modeling and inference.
