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This book presents the applications of systems biology and
synthetic biology in cancer medicine. It highlights the use of
computational and mathematical models to decipher the complexity of
cancer heterogeneity. The book emphasizes the modeling approaches
for predicting behavior of cancer cells, tissues in context of drug
response, and angiogenesis. It introduces cell-based therapies for
the treatment of various cancers and reviews the role of neural
networks for drug response prediction. Further, it examines the
system biology approaches for the identification of medicinal
plants in cancer drug discovery. It explores the opportunities for
metabolic engineering in the realm of cancer research towards
development of new cancer therapies based on metabolically derived
targets. Lastly, it discusses the applications of data mining
techniques in cancer research. This book is an excellent guide for
oncologists and researchers who are involved in the latest cancer
research.
This book presents the applications of systems biology and
synthetic biology in cancer medicine. It highlights the use of
computational and mathematical models to decipher the complexity of
cancer heterogeneity. The book emphasizes the modeling approaches
for predicting behavior of cancer cells, tissues in context of drug
response, and angiogenesis. It introduces cell-based therapies for
the treatment of various cancers and reviews the role of neural
networks for drug response prediction. Further, it examines the
system biology approaches for the identification of medicinal
plants in cancer drug discovery. It explores the opportunities for
metabolic engineering in the realm of cancer research towards
development of new cancer therapies based on metabolically derived
targets. Lastly, it discusses the applications of data mining
techniques in cancer research. This book is an excellent guide for
oncologists and researchers who are involved in the latest cancer
research.
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