## Genomic Signal Processing |

Genomic signal processing (GSP) can be defined as the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applications that can be used to diagnose and treat genetic diseases. Situated at the crossroads of engineering, biology, mathematics, statistics, and computer science, GSP requires the development of both nonlinear dynamical models that adequately represent genomic regulation, and diagnostic and therapeutic tools based on these models. This book facilitates these developments by providing rigorous mathematical definitions and propositions for the main elements of GSP and by paying attention to the validity of models relative to the data. Ilya Shmulevich and Edward Dougherty cover real-world situations and explain their mathematical modeling in relation to systems biology and systems medicine. " "Overall, this book should be useful for individuals with a background in computer science and machine learning who wish to see the applications of mathematics to genomics."
"There is a genuine need for this concise, informative, clearly written book. In systems biology, engineers, mathematicians, and computer scientists are collaborating increasingly with biologists and researchers in medicine. This book goes a long way toward narrowing the gap on this front, and it lays a rigorous foundation for a new discipline."
- Princeton Series in Applied Mathematics
Ingrid Daubechies, Weinan E, Jan Karel Lenstra, and Endre Süli, Editors
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