I.- II.- Bio-Medical Platforms.- In Vivo Systems for Studying Cancer.- Molecular Subtypes of Cancer from Gene Expression Profiling.- Mass Spectrometry-based Systems Biology.- III.- Computational Platforms.- Informatics.- Integrative Computational Biology.- IV.- Future Steps and Challenges.
Part I. Introduction.- Part II. Bio-Medical Platforms.- In-vivo systems for studying cancer.- Molecular subtypes of cancer from gene expression profiling.- Mass spectrometry-based systems biology.- Part III. Computational Platforms.- Informatics.- Integrative Computational Biology.- Part IV. Future Steps and Challenges.- Glossary.- References.- Index.
Cancer Informatics in Post-Genomic Era provides both the necessary methodology and practical information tools for analyzing data in the field of medical information science. This, of course, requires analytic tools. Those tools are garnered by developing and assessing methods and systems for the acquisition, processing, and interpretation of patient data, aided by scientific discovery. Key challenges in this field include integrating research and clinical care, sharing data, and establishing partnerships within and across sectors of patient diagnosis and treatment.
Assesses methods and systems for acquisition, processing, and interpretation of patient data
Provides necessary methodology and practical information tools
Integrates research and clinical care, data sharing, and establishing partnerships within and across sectors of patient diagnosis and treatment
Important clinical questions in cancer research benefit from expanding computational biology