The species translation challenge - A systems biology perspective on human and rat bronchial epithelial cells

Scientific Data

Volumn 1, Issue , 2014, Pages

  Poussin, Carine ^a   Mathis, Carole ^a   Alexopoulos, Leonidas G ^b,c   Messinis, Dimitris E ^b,c   Dulize, Rémi H J ^a   Belcastro, Vincenzo ^a   Melas, Ioannis N ^b,c   Sakellaropoulos, Theodore ^c   Rhrissorrakrai, Kahn ^d   Bilal, Erhan ^d   Meyer, Pablo ^d   Talikka, Marja ^a   Boué, Stéphanie ^a   Norel, Raquel ^d   Rice, John J ^a   Stolovitzky, Gustavo ^d   Ivanov, Nikolai V ^a   Peitsch, Manuel C ^a   Hoeng, Julia ^a  

^a PHILIP MORRIS PRODUCTS S A   (Switzerland)

^b PROTATONCE LTD   (Greece)

^c NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

^d IBM   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CYTOKINE; TRANSCRIPTOME;

ANIMAL; ANIMAL MODEL; BRONCHUS; CYTOLOGY; EPITHELIUM CELL; HUMAN; METABOLISM; PROCEDURES; PROTEOMICS; RAT; SYSTEMS BIOLOGY; TRANSLATIONAL RESEARCH;

ANIMALS; BRONCHI; CYTOKINES; EPITHELIAL CELLS; HUMANS; MODELS, ANIMAL; PROTEOMICS; RATS; SYSTEMS BIOLOGY; TRANSCRIPTOME; TRANSLATIONAL MEDICAL RESEARCH;

EID: 84928475201     PISSN: None     EISSN: 20524463     Source Type: Journal    
DOI: 10.1038/sdata.2014.9     Document Type: Article

References (18)

1. Meyer, P. et al. Verification of systems biology research in the age of collaborative competition. Nat. Biotechnol. 29, 811-815 (2011).
2. Meyer, P. et al. Industrial methodology for process verification in research (IMPROVER): toward systems biology verification. Bioinformatics 28, 1193-1201 (2012).
3. Bhattacharya, S., Zhang, Q., Carmichael, P. L., Boekelheide, K. & Andersen, M. E. Toxicity testing in the 21 century: defining new risk assessment approaches based on perturbation of intracellular toxicity pathways. PloS One 6, e20887 (2011).
4. Huber, P. J. Robust Statistics. (John Wiley & Sons, Inc., 1981).
5. Wu, Z., Irizarry, R. A., Gentleman, R., Murillo, F. M. & Spencer, F. A model based background adjustment for oligonucleotide expression arrays. J. Am. Stat. Assoc. 99, 909-917 (2004).
6. Irizarry, R. A. et al. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4, 249-264 (2003).
7. Rayner, T. F. et al. A simple spreadsheet-based, MIAME-supportive format for microarray data: MAGE-TAB. BMC Bioinformatics 7, 489 (2006).
8. Bartelt, R. R., Cruz-Orcutt, N., Collins, M. & Houtman, J. C. Comparison of T cell receptor-induced proximal signaling and downstream functions in immortalized and primary T cells. PloS One 4, e5430 (2009).
9. Boerma, M. et al. Comparative expression profiling in primary and immortalized endothelial cells: changes in gene expression in response to hydroxy methylglutaryl-coenzyme A reductase inhibition. Blood Coagul. Fibrin. 17, 173-180 (2006).
10. Czekanska, E. M., Stoddart, M. J., Ralphs, J. R., Richards, R. G. & Hayes, J. S. A phenotypic comparison of osteoblast cell lines versus human primary osteoblasts for biomaterials testing. J. Biomed. Mater. Res. A (2013).
11. Hou, A., Voorhoeve, P. M., Lan, W., Tin, M. & Tong, L. Comparison of gene expression profiles in primary and immortalized human pterygium fibroblast cells. Exp. Cell Res. 319, 2781-2789 (2013).
12. Pan, C., Kumar, C., Bohl, S., Klingmueller, U. & Mann, M. Comparative proteomic phenotyping of cell lines and primary cells to assess preservation of cell type-specific functions. Mol. Cell. Proteomics 8, 443-450 (2009).
13. Pezzulo, A. A. et al. The air-liquid interface and use of primary cell cultures are important to recapitulate the transcriptional profile of in vivo airway epithelia. Am. J. Physiol.-Lung C 300, L25-L31 (2011).
14. Clarke, D. C., Morris, M. K. & Lauffenburger, D. A. Normalization and statistical analysis of multiplexed bead-based immunoassay data using mixed-effects modeling. Mol. Cell. Proteomics 12, 245-262 (2013).
15. Saez-Rodriguez, J. et al. Flexible informatics for linking experimental data to mathematical models via DataRail. Bioinformatics 24, 840-847 (2008).
16. Alexopoulos, L. G., Saez-Rodriguez, J., Cosgrove, B. D., Lauffenburger, D. A. & Sorger, P.K. Networks inferred from biochemical data reveal profound differences in toll-like receptor and inflammatory signaling between normal and transformed hepatocytes. Mol. Cell. Proteomics 9, 1849-1865 (2010).
17. Lamb, J. et al. The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science 313, 1929-1935 (2006).
18. Iorio, F. et al. Discovery of drug mode of action and drug repositioning from transcriptional responses. Proc. Natl Acad. Sci. USA 107, 14621-14626 (2010).