Statistical Bioinformatics with R

2. Auflage 2026
ISBN: 978-0-443-40437-5
Verlag: Elsevier Science & Technology

Buch, Englisch, Format (B × H): 191 mm x 235 mm

Statistical Bioinformatics with R, Second Edition offers a balanced treatment of statistical theory within the context of bioinformatics applications. Designed for a one- or two-semester senior undergraduate or graduate statistical bioinformatics course, this text provides a comprehensive overview of the statistical methods that can be used to analyze bioinformatics data including omics and single cell-RNA seq data. It goes beyond gene expression and sequence analysis to include a careful integration of statistical theory in bioinformatics. The inclusion of R codes, along with the development of advanced methodologies such as Bayesian and Markov models, equips students with a solid foundation for conducting bioinformatics research. Statistical Bioinformatics with R, Second Edition expands upon the original material by incorporating the latest advancements in bioinformatics and statistical methodologies, including new chapters and sections that explore cutting-edge topics such as high-throughput sequencing data analysis, AI/machine learning applications in bioinformatics, and advanced statistical methods. From new and updated practical examples and case studies that illustrate real-world applications of statistical techniques to bioinformatic problems, to enhanced end-of-chapter exercises, detailed code annotations, and an improved companion website with supplementary materials, including datasets and R scripts, this book is a valuable resource for both self-study and formal coursework, fostering a deeper understanding of statistical bioinformatics and equipping readers with the skills needed to tackle complex biological data analysis challenges. Ancillary materials including PowerPoint lectures for both students and instructors and an Instructors Manual provide support for students across upper-level undergraduate and graduate courses in bioinformatics, computational biology, and biostatistics.

Autoren/Hrsg.

Mathur, Sunil K.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik

Inhaltsverzeichnis

1. Introduction
2. Fundamentals of Molecular Biology
3. Exploratory Data Analysis
4. Statistical Methods for Bioinformatics
5. Bayesian Methods in Bioinformatics
6. AI/Machine Learning in Bioinformatics
7. Sequence Analysis
8. Genomic Data Analysis
9. Transcriptomics Data Analysis
10. Transcriptomics Data Analysis
11. Metabolomics

Über Autor(innen)

Mathur, Sunil K.
Dr. Sunil Mathur is a distinguished professor of Biostatistics at Weill Cornell Medical College and a full member of both the Houston Methodist Academic Institute and the Houston Methodist Neal Cancer Center. He serves as the Director of Biostatistics and Co-Director of the Biostatistics and Bioinformatics Shared Resources at the Houston Methodist Neal Cancer Center and the Houston Methodist Research Institute. Dr. Mathur has previously held several key positions: he was a Professor and Chair of the Department of Mathematics and Statistics and Assistant to the Dean for Research Development at Texas A&M University-Corpus Christi; a Professor and Director of the Research Support Center at Augusta University's Medical College of Georgia; an Associate Professor at the School of Public Health, University of Memphis; and an Associate Professor and Director of the Statistical Consulting Center at the University of Mississippi. Dr. Mathur is the Editor-in-Chief of the American Journal of Statistical Science and Applications and serves as an Associate Editor for multiple journals, including the Journal of Applied Statistics and the International Journal of Statistics and Systems. He is also on the editorial boards of the Global Journal of Medicine and Public Health and the Austin Journal of Public Health and Epidemiology. He has successfully secured over $50 million in external grant funding from various sources, including the NIH, DOD, NSF, DOE, and the US Army as PI/Co-PI/Co-I. Dr. Mathur reviews grant proposals for the National Science Foundation, DOD, and other agencies, and he is a member of the Data Safety and Monitoring Board for NIH grants. His contributions have been recognized with numerous awards, such as the Digital Innovator of the Year Award and the Graduate Resource and Opportunity Workspace Friends Award. Dr. Mathur is currently the President of the San Antonio Chapter of the American Statistical Association and a former President of the Texas Association of Academic Administrators in the Mathematical Sciences (T3AMS). He is an elected member of the International Statistical Institute and is a member of the American Statistical Association and the International Indian Statistical Association, USA.