Buch, Englisch, 336 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 454 g
An Algorithmic Approach
Buch, Englisch, 336 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 454 g
Reihe: Chapman & Hall/CRC Computer Science & Data Analysis
ISBN: 978-1-138-11515-6
Verlag: Taylor & Francis Ltd
The book first explores a new technique that takes advantage of a multiview approach to image analysis and addresses the challenges of applying powerful traditional techniques, such as clustering, to full-scale microarray experiments. It then presents an effective feature identification approach, an innovative technique that renders highly detailed surface models, a new approach to subgrid detection, a novel technique for the background removal process, and a useful technique for removing "noise." The authors also develop an expectation–maximization (EM) algorithm for modeling gene regulatory networks from gene expression time series data. The final chapter describes the overall benefits of these techniques in the biological and computer sciences and reviews future research topics.
This book systematically brings together the fields of image processing, data analysis, and molecular biology to advance the state of the art in this important area. Although the text focuses on improving the processes involved in the analysis of microarray image data, the methods discussed can be applied to a broad range of medical and computer vision analysis areas.
Zielgruppe
Professional
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Introduction. Background. Data Services. Structure Extrapolation I. Structure Extrapolation II. Feature Identification I. Feature Identification II. Chained Fourier Background Reconstruction. Graph-Cutting for Improving Microarray Gene Expression. Stochastic Dynamic Modeling of Short Gene Expression Time Series Data. Conclusions. Appendices. References.