Buch, Englisch, 180 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 477 g
Toward Information-Based Medicine
Buch, Englisch, 180 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 477 g
Reihe: Cancer Treatment and Research
ISBN: 978-0-387-69320-0
Verlag: Springer US
Medical information science requires analytic tools. This is achieved by developing and assessing methods and systems for the acquisition, processing, and interpretation of patient data, aided by scientific discovery. Cancer Informatics in Post-Genomic Era provides both the necessary methodology and practical information tools.
Key challenges include integrating research and clinical care, sharing data, and establishing partnerships within and across sectors of patient diagnosis and treatment.
Addressing important clinical questions in cancer research will benefit from expanding computational biology.
The advent of genomic and proteomic technologies has ushered forth the era of genuine medicine. The promise of these advances is true "personalized medicine" where treatment strategies can be individually tailored and advance to initiating intervention before visible symptoms appear.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Vorklinische Medizin: Grundlagenfächer Humangenetik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Onkologie, Krebsforschung
- Naturwissenschaften Biowissenschaften Molekularbiologie
- Mathematik | Informatik EDV | Informatik Informatik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
Weitere Infos & Material
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.