Literature DB >> 16098176

Cytomics, the human cytome project and systems biology: top-down resolution of the molecular biocomplexity of organisms by single cell analysis.

G Valet1.   

Abstract

A large amount of structural and functional information is obtained by molecular cell phenotype analysis of tissues, organs and organisms at the single cell level by image or flow cytometry in combination with bioinformatic knowledge extraction (cytomics) concerning nuclei acids, proteins and metabolites (cellular genomics, proteomics and metabolomics) as well as cell function parameters like intracellular pH, transmembrane potentials or ion gradients. In addition, differential molecular cell phenotypes between diseased and healthy cells provide molecular data patterns for (i) predictive medicine by cytomics or for (ii) drug discovery purposes using reverse engineering of the data patterns by biomedical cell systems biology. Molecular pathways can be explored in this way including the detection of suitable target molecules, without detailed a priori knowledge of specific disease mechanisms. This is useful during the analysis of complex diseases such as infections, allergies, rheumatoid diseases, diabetes or malignancies. The top-down approach reaching from single cell heterogeneity in cell systems and tissues down to the molecular level seems suitable for a human cytome project to systematically explore the molecular biocomplexity of human organisms. The analysis of already existing data from scientific studies or routine diagnostic procedures will be of immediate value in clinical medicine, for example as personalized therapy by cytomics.

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Year:  2005        PMID: 16098176      PMCID: PMC6496119          DOI: 10.1111/j.1365-2184.2005.00342.x

Source DB:  PubMed          Journal:  Cell Prolif        ISSN: 0960-7722            Impact factor:   6.831


  33 in total

1.  Quantitative histology by multicolor slide-based cytometry.

Authors:  Andreas O H Gerstner; Christine Trumpfheller; Paul Racz; Pavel Osmancik; Klara Tenner-Racz; Attila Tárnok
Journal:  Cytometry A       Date:  2004-06       Impact factor: 4.355

Review 2.  Flow cytometry for high-throughput, high-content screening.

Authors:  Bruce S Edwards; Tudor Oprea; Eric R Prossnitz; Larry A Sklar
Journal:  Curr Opin Chem Biol       Date:  2004-08       Impact factor: 8.822

Review 3.  Embryonic stem cells.

Authors:  H J Rippon; A E Bishop
Journal:  Cell Prolif       Date:  2004-02       Impact factor: 6.831

4.  Multidimensional drug profiling by automated microscopy.

Authors:  Zachary E Perlman; Michael D Slack; Yan Feng; Timothy J Mitchison; Lani F Wu; Steven J Altschuler
Journal:  Science       Date:  2004-11-12       Impact factor: 47.728

5.  Automated tissue analysis--a bioinformatics perspective.

Authors:  A Kriete; K Boyce
Journal:  Methods Inf Med       Date:  2005       Impact factor: 2.176

Review 6.  Target-based drug discovery: is something wrong?

Authors:  Frank Sams-Dodd
Journal:  Drug Discov Today       Date:  2005-01-15       Impact factor: 7.851

Review 7.  Cytomics goes 3D: toward tissomics.

Authors:  Rupert C Ecker; Attila Tarnok
Journal:  Cytometry A       Date:  2005-05       Impact factor: 4.355

8.  Polychromatic (eight-color) slide-based cytometry for the phenotyping of leukocyte, NK, and NKT subsets.

Authors:  Anja Mittag; Dominik Lenz; Andreas O H Gerstner; Ulrich Sack; Michael Steinbrecher; Mario Koksch; Alexander Raffael; Jozsef Bocsi; Attila Tárnok
Journal:  Cytometry A       Date:  2005-06       Impact factor: 4.355

Review 9.  Cytomics in predictive medicine.

Authors:  Günter K Valet; Attila Tárnok
Journal:  Cytometry B Clin Cytom       Date:  2003-05       Impact factor: 3.058

10.  Cytomics--new technologies: towards a human cytome project.

Authors:  G Valet; J F Leary; A Tárnok
Journal:  Cytometry A       Date:  2004-06       Impact factor: 4.355

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  9 in total

1.  Cytomics emerging from cytometry.

Authors:  A Tárnok; G Brockhoff
Journal:  Cell Prolif       Date:  2006-10       Impact factor: 6.831

2.  Predictive medicine and clinical cytomics research: résumé of the 15th Annual Meeting of the German Society for Cytometry (Deutsche Gesellschaft für Zytometrie, DGfZ).

Authors:  G Brockhoff; S Müller; C Sarraf; A Tarnok
Journal:  Cell Prolif       Date:  2006-04       Impact factor: 6.831

Review 3.  [Cytomics and predictive medicine for oncology].

Authors:  A O H Gerstner; W Laffers
Journal:  HNO       Date:  2008-04       Impact factor: 1.284

4.  Development of analytical methods for multiplex bio-assay with inductively coupled plasma mass spectrometry.

Authors:  Olga I Ornatsky; Robert Kinach; Dmitry R Bandura; Xudong Lou; Scott D Tanner; Vladimir I Baranov; Mark Nitz; Mitchell A Winnik
Journal:  J Anal At Spectrom       Date:  2008       Impact factor: 4.023

5.  Towards in vivo flow cytometry.

Authors:  Valery V Tuchin; Attila Tárnok; Vladimir P Zharov
Journal:  J Biophotonics       Date:  2009-09       Impact factor: 3.207

Review 6.  Cytomics - importance of multimodal analysis of cell function and proliferation in oncology.

Authors:  A Tárnok; J Bocsi; G Brockhoff
Journal:  Cell Prolif       Date:  2006-12       Impact factor: 6.831

7.  Tissue microarrays as a platform for proteomic investigation.

Authors:  Joon-Yong Chung; Till Braunschweig; Kimberly Tuttle; Stephen M Hewitt
Journal:  J Mol Histol       Date:  2006-09-05       Impact factor: 3.156

8.  Early detection in head and neck cancer - current state and future perspectives.

Authors:  Andreas O H Gerstner
Journal:  GMS Curr Top Otorhinolaryngol Head Neck Surg       Date:  2010-10-07

9.  A perspective for biomedical data integration: design of databases for flow cytometry.

Authors:  John Drakos; Marina Karakantza; Nicholas C Zoumbos; John Lakoumentas; George C Nikiforidis; George C Sakellaropoulos
Journal:  BMC Bioinformatics       Date:  2008-02-14       Impact factor: 3.169

  9 in total

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