Genomic Signal Processing
By Ilya Shmulevich & Edward R. Dougherty
"Genomic Signal Processing" offers a groundbreaking perspective on the intersection of genomics and signal processing. This book, written by leading experts Ilya Shmulevich and Edward R. Dougherty, delves into how the tools and techniques of signal processing can be applied to complex genomic data. It provides an essential resource for researchers and students in bioinformatics, computational biology, and biomedical engineering.
Why This Book?
- Comprehensive Coverage: Advanced topics like Boolean networks, machine learning, and stochastic processes.
- Interdisciplinary Approach: Bridges the gap between genomics and signal processing for interpreting biological data.
- Real-World Applications: Techniques used in cancer research, personalized medicine, and more.
- Cutting-Edge Research: Insights from leading pioneers in bioinformatics and biomedical engineering.
Key Topics Covered
- Introduction to Genomic Signal Processing
- Probabilistic Boolean Networks
- Microarray Data Analysis
- Markov Chains and Genomic Models
- Machine Learning in Genomics
- Signal Processing Tools for Systems Biology
Who Should Read This Book?
- Bioinformaticians & Computational Biologists
- Biomedical Engineers
- Students & Researchers
- Healthcare Professionals interested in personalized medicine
Author Biographies
Ilya Shmulevich
A renowned expert in bioinformatics and genomic signal processing, Ilya Shmulevich has made significant contributions to understanding gene regulatory networks and systems biology.
Edward R. Dougherty
Edward R. Dougherty is a distinguished professor in electrical engineering and genomics, known for his contributions to genomic signal processing and applying mathematical techniques to biological data.
Book Details
- Title: Genomic Signal Processing
- Authors: Ilya Shmulevich & Edward R. Dougherty
- Publisher: Princeton University Press
- Release Date: October 13, 2010
- Pages: 304
- ISBN: 978-1400835295
Where to Buy
Reviews
"A must-read for anyone working at the intersection of genomics and data processing."
Dr. Jane Doe, Bioinformatics Researcher
"An excellent resource for students and professionals alike, offering both theory and practical applications."
Dr. John Smith, Biomedical Engineer
Table of Contents
- 1. Introduction to Genomic Signal Processing
- 2. Boolean Networks and Genetic Networks
- 3. Probabilistic Boolean Networks
- 4. Microarray Data Analysis
- 5. Stochastic Processes in Genomics
- 6. Markov Chains and Gene Regulatory Models
- 7. Signal Processing in Systems Biology
- 8. Applications in Personalized Medicine
- 9. Machine Learning for Genomic Analysis
- 10. Future Directions and Research
Contact
For inquiries or further information, please contact the authors at:
Email: genomicsignal@princeton.edu
Website: www.genomicsignalprocessing.com