Foundations for High-Throughput Omics Data Analysis
Methods, Theories and Applications
1st Edition
Published on 19. August 2023
Book
Hardback
400 pages
978-1-4987-0650-6 (ISBN)
Description
The aim of this textbook is to train new researchers in analyzing high-throughput omics data by building fundamental skills instead of focusing on technology or platform-specific features that change every few years. The authors seek a balance between breadth and depth in the broad field. The book contains many real examples to illustrate the methodological concept and biological relevance. Computer lab materials (data and hands-on programming code) are included along with homework exercises to provide real-world data analysis experiences.
More details
Series
Language
English
Place of publication
Portland
United States
Publishing group
Taylor & Francis Inc
Target group
College/higher education
Professional Practice & Development
Dimensions
Height: 234 mm
Width: 156 mm
ISBN-13
978-1-4987-0650-6 (9781498706506)
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Schweitzer Classification
Persons
George C. Tseng is an associate professor in the Department of Biostatistics at the University of Pittsburgh, Pennsylvania, USA
Zhiguang Huo and Tianzhu Ma are PhD students at the University of Pittsburgh, Pennsylvania, USA
Zhiguang Huo and Tianzhu Ma are PhD students at the University of Pittsburgh, Pennsylvania, USA
Content
High-Throughput Omics Data. Experimental Design and Data Preprocessing. Differential and Association Analysis. Dimension Reduction. Robust Nonparametric Methods. Unsupervised Machine Learning and Clustering. Supervised Machine Learning I: Methods. Supervised Machine Learning II: Concept and Principles. Regularization Method. Bayesian Methods and Applications. Network Analysis. Enrichment Analysis. Meta-Analysis and Integrative Analysis. Selected Computational Algorithms. Reproducible Research and Critical Thinking in Bioinformatics. Appendix: Case Studies.