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Inter-species inference of gene set enrichment in lung epithelial cells from proteomic and large transcriptomic datasets.

Hormoz S, Bhanot G, Biehl M, Bilal E, Meyer P, Norel R, Rhrissorrakrai K, Dayarian A - Bioinformatics (2014)

Bottom Line: Translating findings in rodent models to human models has been a cornerstone of modern biology and drug development.However, in many cases, a naive 'extrapolation' between the two species has not succeeded.In spite of this difference, we were able to develop a robust algorithm to predict gene set activation in NHBE with high accuracy using simple analytical methods.

View Article: PubMed Central - PubMed

Affiliation: Kavli Institute for Theoretical Physics, Kohn Hall, University of California, Santa Barbara, CA 93106, USA, Department of Physics, Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, USA, Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands and IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10003, USA.

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(A) Gene set enrichment under the 26 training stimuli for rat and human. The FDR scores of the gene sets are displayed above; white implies differential expression (FDR < 0.25). The number of gene sets that turn on in rat and human are dramatically different. (B) The prediction compared with the actual measurements of differential expression in human gene sets under the 26 test stimuli. The color bar indicates level of confidence in the prediction: 0 off, 0.5 uncertain, 1 on
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btu569-F5: (A) Gene set enrichment under the 26 training stimuli for rat and human. The FDR scores of the gene sets are displayed above; white implies differential expression (FDR < 0.25). The number of gene sets that turn on in rat and human are dramatically different. (B) The prediction compared with the actual measurements of differential expression in human gene sets under the 26 test stimuli. The color bar indicates level of confidence in the prediction: 0 off, 0.5 uncertain, 1 on


Inter-species inference of gene set enrichment in lung epithelial cells from proteomic and large transcriptomic datasets.

Hormoz S, Bhanot G, Biehl M, Bilal E, Meyer P, Norel R, Rhrissorrakrai K, Dayarian A - Bioinformatics (2014)

(A) Gene set enrichment under the 26 training stimuli for rat and human. The FDR scores of the gene sets are displayed above; white implies differential expression (FDR < 0.25). The number of gene sets that turn on in rat and human are dramatically different. (B) The prediction compared with the actual measurements of differential expression in human gene sets under the 26 test stimuli. The color bar indicates level of confidence in the prediction: 0 off, 0.5 uncertain, 1 on
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4325538&req=5

btu569-F5: (A) Gene set enrichment under the 26 training stimuli for rat and human. The FDR scores of the gene sets are displayed above; white implies differential expression (FDR < 0.25). The number of gene sets that turn on in rat and human are dramatically different. (B) The prediction compared with the actual measurements of differential expression in human gene sets under the 26 test stimuli. The color bar indicates level of confidence in the prediction: 0 off, 0.5 uncertain, 1 on
Bottom Line: Translating findings in rodent models to human models has been a cornerstone of modern biology and drug development.However, in many cases, a naive 'extrapolation' between the two species has not succeeded.In spite of this difference, we were able to develop a robust algorithm to predict gene set activation in NHBE with high accuracy using simple analytical methods.

View Article: PubMed Central - PubMed

Affiliation: Kavli Institute for Theoretical Physics, Kohn Hall, University of California, Santa Barbara, CA 93106, USA, Department of Physics, Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, USA, Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands and IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10003, USA.

Show MeSH
Related in: MedlinePlus