Written for drug developers rather than computer scientists,
this monograph adopts a systematic approach to mining scientifi c
data sources, covering all key steps in rational drug discovery,
from compound screening to lead compound selection and personalized
medicine. Clearly divided into four sections, the first part
discusses the different data sources available, both commercial and
non-commercial, while the next section looks at the role and value
of data mining in drug discovery. The third part compares the most
common applications and strategies for polypharmacology, where data
mining can substantially enhance the research effort. The final
section of the book is devoted to systems biology approaches for
compound testing. Throughout the book, industrial and academic drug
discovery strategies are addressed, with contributors coming from
both areas, enabling an informed decision on when and which data
mining tools to use for one's own drug discovery project.
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