Related Experiment Video
Updated: Apr 26, 2026
Oligopeptide Competition Assay for Phosphorylation Site Determination
Published on: May 18, 2017
Predicting protein phosphorylation from gene expression: top methods from the IMPROVER Species Translation Challenge
Adel Dayarian1, Roberto Romero1, Zhiming Wang2
1Kavli Institute for Theoretical Physics, Kohn Hall, University of California, Santa Barbara, CA 93106, Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD, and Detroit, MI 48201, USA, College of Plant Protection and College of Science, Hunan Agricultural University, Changsha, 410128, China, School of Computing, Clemson University, Clemson, SC 29634, USA, Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands, IBM T.J. Watson Research Center, Computational Biology Center, Yorktown Heights, NY 10003, Department of Molecular Biology and Biochemistry, Department of Physics and BioMaPS Institute, Rutgers University, Piscataway, NJ 08854 and Department of Computer Science, Wayne State University, Detroit, MI 48202, USA.
Motivation:
Using gene expression to infer changes in protein phosphorylation levels induced in cells by various stimuli is an outstanding problem. The intra-species protein phosphorylation challenge organized by the IMPROVER consortium provided the framework to identify the best approaches to address this issue.
Results:
Rat lung epithelial cells were treated with 52 stimuli, and gene expression and phosphorylation levels were measured. Competing teams used gene expression data from 26 stimuli to develop protein phosphorylation prediction models and were ranked based on prediction performance for the remaining 26 stimuli. Three teams were tied in first place in this challenge achieving a balanced accuracy of about 70%, indicating that gene expression is only moderately predictive of protein phosphorylation. In spite of the similar performance, the approaches used by these three teams, described in detail in this article, were different, with the average number of predictor genes per phosphoprotein used by the teams ranging from 3 to 124. However, a significant overlap of gene signatures between teams was observed for the majority of the proteins considered, while Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were enriched in the union of the predictor genes of the three teams for multiple proteins.
Availability And Implementation:
Gene expression and protein phosphorylation data are available from ArrayExpress (E-MTAB-2091). Software implementation of the approach of Teams 49 and 75 are available at http://bioinformaticsprb.med.wayne.edu and http://people.cs.clemson.edu/∼luofeng/sbv.rar, respectively.
Contact:
gyanbhanot@gmail.com or luofeng@clemson.edu or atarca@med.wayne.edu
Supplementary Information:
Supplementary data are available at Bioinformatics online.
Related Concept Videos
02:54Protein Kinases and Phosphatases
Protein kinases
Many proteins in the cell are regulated by phosphorylation, the addition of a phosphate group. A family of enzymes called kinases...
02:54Protein Kinases and Phosphatases
01:42What is Gene Expression?
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
01:36What is Gene Expression?
02:24Ribosome Profiling
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
01:58Cell Specific Gene Expression