Beginning with a survey of fundamental concepts associated with
data integration, knowledge representation, and hypothesis
generation from heterogeneous data sets, "Methods in Biomedical
Informatics" provides a practical survey of methodologies used in
biological, clinical, and public health contexts. These concepts
provide the foundation for more advanced topics like information
retrieval, natural language processing, Bayesian modeling, and
learning classifier systems. The survey of topics then concludes
with an exposition of essential methods associated with
engineering, personalized medicine, and linking of genomic and
clinical data. Within an overall context of the scientific method,
"Methods in Biomedical Informatics" provides a practical coverage
of topics that is specifically designed for: (1) domain experts
seeking an understanding of biomedical informatics approaches for
addressing specific methodological needs; or (2) biomedical
informaticians seeking an approachable overview of methodologies
that can be used in scenarios germane to biomedical research.
Contributors represent leading biomedical informatics experts:
individuals who have demonstrated effective use of biomedical
informatics methodologies in the real-world, high-quality
biomedical applicationsMaterial is presented as a balance between
foundational coverage of core topics in biomedical informatics with
practical "in-the-trenches" scenarios.Contains appendices that
function as primers on: (1) Unix; (2) Ruby; (3) Databases; and (4)
Web Services.
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