Elements of Computational Systems Biology (Wiley Series in Bioinformatics) (in English)
Synopsis "Elements of Computational Systems Biology (Wiley Series in Bioinformatics) (in English)"
Groundbreaking, long-ranging research in this emergent fieldthat enables solutions to complex biological problemsComputational systems biology is an emerging discipline that isevolving quickly due to recent advances in biology such as genomesequencing, high-throughput technologies, and the recentdevelopment of sophisticated computational methodologies. Elementsof Computational Systems Biology is a comprehensive referencecovering the computational frameworks and techniques needed to helpresearch scientists and professionals in computer science, biology,chemistry, pharmaceutical science, and physics solve complexbiological problems. Written by leading experts in the field, thispractical resource gives detailed descriptions of core subjects,including biological network modeling, analysis, and inference;presents a measured introduction to foundational topics likegenomics; and describes state-of-the-art software tools for systemsbiology.Offers a coordinated integrated systems view of defining andapplying computational and mathematical tools and methods tosolving problems in systems biologyChapters provide a multidisciplinary approach and range fromanalysis, modeling, prediction, reasoning, inference, andexploration of biological systems to the implications ofcomputational systems biology on drug design and medicineHelps reduce the gap between mathematics and biology bypresenting chapters on mathematical models of biologicalsystemsEstablishes solutions in computer science, biology, chemistry,and physics by presenting an in-depth description of computationalmethodologies for systems biologyElements of Computational Systems Biology is intended foracademic/industry researchers and scientists in computer science,biology, mathematics, chemistry, physics, biotechnology, andpharmaceutical science. It is also accessible to undergraduate andgraduate students in machine learning, data mining, bioinformatics,computational biology, and systems biology courses.
