Inter-species prediction of protein phosphorylation in the sbv IMPROVER species translation challenge

Michael Biehl; Peter Sadowski; Gyan Bhanot; Erhan Bilal; Adel Dayarian; Pablo Meyer; Raquel Norel; Kahn Rhrissorrakrai; Michael D Zeller; Sahand Hormoz

doi:10.1093/bioinformatics/btu407

Back

Inter-species prediction of protein phosphorylation in the sbv IMPROVER species translation challenge

Journal article

Open access

Peer reviewed

Inter-species prediction of protein phosphorylation in the sbv IMPROVER species translation challenge

Michael Biehl, Peter Sadowski, Gyan Bhanot, Erhan Bilal, Adel Dayarian, Pablo Meyer, Raquel Norel, Kahn Rhrissorrakrai, Michael D Zeller and Sahand Hormoz

Bioinformatics (Oxford, England), Vol.31(4), pp.453-461

02/15/2015

DOI: https://doi.org/10.1093/bioinformatics/btu407

PMCID: PMC4325536

PMID: 24994890

Abstract

Algorithms

Animals

Bronchi - cytology

Bronchi - metabolism

Cells, Cultured

Databases, Factual

Epithelial Cells - cytology

Epithelial Cells - metabolism

Gene Expression Profiling

Gene Expression Regulation

Humans

Oligonucleotide Array Sequence Analysis

Phosphoproteins - metabolism

Phosphorylation

Rats

Software

Species Specificity

Systems Biology - methods

Translational Medical Research

Animal models are widely used in biomedical research for reasons ranging from practical to ethical. An important issue is whether rodent models are predictive of human biology. This has been addressed recently in the framework of a series of challenges designed by the systems biology verification for Industrial Methodology for Process Verification in Research (sbv IMPROVER) initiative. In particular, one of the sub-challenges was devoted to the prediction of protein phosphorylation responses in human bronchial epithelial cells, exposed to a number of different chemical stimuli, given the responses in rat bronchial epithelial cells. Participating teams were asked to make inter-species predictions on the basis of available training examples, comprising transcriptomics and phosphoproteomics data. Here, the two best performing teams present their data-driven approaches and computational methods. In addition, post hoc analyses of the datasets and challenge results were performed by the participants and challenge organizers. The challenge outcome indicates that successful prediction of protein phosphorylation status in human based on rat phosphorylation levels is feasible. However, within the limitations of the computational tools used, the inclusion of gene expression data does not improve the prediction quality. The post hoc analysis of time-specific measurements sheds light on the signaling pathways in both species. A detailed description of the dataset, challenge design and outcome is available at www.sbvimprover.com. The code used by team IGB is provided under http://github.com/uci-igb/improver2013. Implementations of the algorithms applied by team AMG are available at http://bhanot.biomaps.rutgers.edu/wiki/AMG-sc2-code.zip. meikelbiehl@gmail.com.

Files and links (1)

url

https://doi.org/10.1093/bioinformatics/btu407View

Version of Record (VoR) Open

Metrics

9 Record Views

5 Times Cited - Web of Science

See more details

Details

Title: Inter-species prediction of protein phosphorylation in the sbv IMPROVER species translation challenge
Creators: Michael Biehl - Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands, University of California, Irvine, CA 92617, Department of Physics and Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10598, Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA 93106, USA
Peter Sadowski - Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands, University of California, Irvine, CA 92617, Department of Physics and Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10598, Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA 93106, USA
Gyan Bhanot - Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands, University of California, Irvine, CA 92617, Department of Physics and Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10598, Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA 93106, USA
Erhan Bilal - Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands, University of California, Irvine, CA 92617, Department of Physics and Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10598, Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA 93106, USA
Adel Dayarian - Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands, University of California, Irvine, CA 92617, Department of Physics and Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10598, Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA 93106, USA
Pablo Meyer - Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands, University of California, Irvine, CA 92617, Department of Physics and Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10598, Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA 93106, USA
Raquel Norel - Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands, University of California, Irvine, CA 92617, Department of Physics and Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10598, Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA 93106, USA
Kahn Rhrissorrakrai - Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands, University of California, Irvine, CA 92617, Department of Physics and Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10598, Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA 93106, USA
Michael D Zeller - Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands, University of California, Irvine, CA 92617, Department of Physics and Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10598, Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA 93106, USA
Sahand Hormoz - Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands, University of California, Irvine, CA 92617, Department of Physics and Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10598, Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA 93106, USA
Publication Details: Bioinformatics (Oxford, England), Vol.31(4), pp.453-461
Date published: 02/15/2015
Grant note: LM010235 / NLM NIH HHS T15 LM07443 / NLM NIH HHS T15 LM007443 / NLM NIH HHS R01 LM010235 / NLM NIH HHS
Academic Unit: Molecular Biology and Biochemistry (SAS)
Language: English
Resource Type: Journal article
Identifiers: 991031666057604646