The species translation challenge—A systems biology perspective on human and rat bronchial epithelial cells View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-06-10

AUTHORS

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

ABSTRACT

The biological responses to external cues such as drugs, chemicals, viruses and hormones, is an essential question in biomedicine and in the field of toxicology, and cannot be easily studied in humans. Thus, biomedical research has continuously relied on animal models for studying the impact of these compounds and attempted to ‘translate’ the results to humans. In this context, the SBV IMPROVER (Systems Biology Verification for Industrial Methodology for PROcess VErification in Research) collaborative initiative, which uses crowd-sourcing techniques to address fundamental questions in systems biology, invited scientists to deploy their own computational methodologies to make predictions on species translatability. A multi-layer systems biology dataset was generated that was comprised of phosphoproteomics, transcriptomics and cytokine data derived from normal human (NHBE) and rat (NRBE) bronchial epithelial cells exposed in parallel to more than 50 different stimuli under identical conditions. The present manuscript describes in detail the experimental settings, generation, processing and quality control analysis of the multi-layer omics dataset accessible in public repositories for further intra- and inter-species translation studies. More... »

PAGES

140009

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/sdata.2014.9

DOI

http://dx.doi.org/10.1038/sdata.2014.9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1000535114

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/25977767


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19 schema:description The biological responses to external cues such as drugs, chemicals, viruses and hormones, is an essential question in biomedicine and in the field of toxicology, and cannot be easily studied in humans. Thus, biomedical research has continuously relied on animal models for studying the impact of these compounds and attempted to ‘translate’ the results to humans. In this context, the SBV IMPROVER (Systems Biology Verification for Industrial Methodology for PROcess VErification in Research) collaborative initiative, which uses crowd-sourcing techniques to address fundamental questions in systems biology, invited scientists to deploy their own computational methodologies to make predictions on species translatability. A multi-layer systems biology dataset was generated that was comprised of phosphoproteomics, transcriptomics and cytokine data derived from normal human (NHBE) and rat (NRBE) bronchial epithelial cells exposed in parallel to more than 50 different stimuli under identical conditions. The present manuscript describes in detail the experimental settings, generation, processing and quality control analysis of the multi-layer omics dataset accessible in public repositories for further intra- and inter-species translation studies.
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31 biomedicine
32 bronchial epithelial cells
33 cells
34 chemicals
35 collaborative initiatives
36 compounds
37 computational methodology
38 conditions
39 context
40 control analysis
41 crowd-sourcing techniques
42 cues
43 cytokine data
44 data
45 dataset
46 describes
47 detail
48 different stimuli
49 drugs
50 epithelial cells
51 essential questions
52 experimental settings
53 external cues
54 field
55 field of toxicology
56 fundamental questions
57 further intra
58 generation
59 hormone
60 humans
61 identical conditions
62 impact
63 initiatives
64 intra
65 manuscript describes
66 methodology
67 model
68 normal humans
69 omics datasets
70 parallel
71 perspective
72 phosphoproteomics
73 prediction
74 processing
75 public repositories
76 quality control analysis
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78 rat bronchial epithelial cells
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81 response
82 results
83 scientists
84 setting
85 stimuli
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87 systems biology
88 systems biology datasets
89 systems biology perspective
90 technique
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