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.
"Genomic Signal Processing" makes a major contribution to
computational biology, systems biology, and translational genomics
by providing a self-contained explanation of the fundamental
mathematical issues facing researchers in four areas:
classification, clustering, network modeling, and network
intervention.
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