Book chapter
Chapter 16 - Cytomics: From Cell States to Predictive Medicine
Computational Systems Biology, pp 363-381
2006
Abstract
This chapter reviews various approaches in basic biological research and medicine for generating quantitative, flow, and image-based data for a comprehensive profiling and structural state space analysis. The value of the single-cell or single-individual analysis concept resides in its clinical value for the individual patient as well as in the bio-parameter patterns being of interest for molecular reverse engineering by systems biology. Currently, the concept of cytomics profits from advances in areas such as location proteomics, flow and tissue cytometry, screening assays, and cell and tissue arrays. Such advances move us toward a broad, systematic collection of information for clustering and cataloging cells according to their molecular, organelle, and morphometric phenotypes. One of the most important outcomes of the Human Genome Project is the realization that there is considerably more biocomplexity in the genome and the proteome than previously appreciated. A substantial advantage over flow cytometry is that cells in adherent cell cultures and tissues can be analyzed without prior disintegration.
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Details
- Title
- Chapter 16 - Cytomics: From Cell States to Predictive Medicine
- Creators
- G. Valet - Max Planck Institute of BiochemistryR.F. Murphy - Carnegie Mellon UniversityJ.P. Robinson - Purdue University West LafayetteA. Tarnok - University Hospital LeipzigA. Kriete - Coriell Institute For Medical Research
- Publication Details
- Computational Systems Biology, pp 363-381
- Publisher
- Elsevier
- Resource Type
- Book chapter
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Scopus ID
- 2-s2.0-33646165894
- Other Identifier
- 991019173890804721