Sub-Challenge 1: Intra-Species Protein Phosphorylation Prediction

Sub-Challenge 1: Intra-Species Protein Phosphorylation Prediction

Sub-Challenge 1 is closed



The overview of the challenge is provided by Figure SC1.A. Participants will be provided with Gene Expression (GEx) and Protein Phosphorylation (P) from Subset A for training. For testing, the participants will be asked to predict which proteins show changes in their phosphorylation status (up or down regulation) for each stimulus in Subset B. These predictions will be reported as confidence values between 0 and 1 where 1 indicates the highest confidence of a phosphorylation change as measured by the Luminex xMAP technology in normal human and rat bronchial epithelial cells. These measurements were performed in triplicate, at both 5 and 25 minutes, after the cells' growing conditions were modified by adding one of the 52 stimuli. Luminex xMAP is a bead based assay where microspheres are coated with antibodies designed to bind specifically to phosphorylated proteins. The signal from individual beads was then measured by a flow cytometry detection device as a distribution of fluorescent intensities. Finally, the median value from each distribution was calculated as the signal intensity value for each protein. 

Figure SC1.A: The objective of sub-challenge 1 is the prediction of the activation status of phosphoproteins based on gene expression data in Subset B for 26 stimuli. Data in Subset A, collected with 26 different stimuli, is provided for training.  


While the main aim of the set of sub-challenges is focused on translation between species, this particular sub-challenge focuses on translation between gene expression data and the corresponding phosphoprotein data in rat only. The gene expression data were that were collected using the Affymetrix®microarray platform, are a standard data type in the field with mature analysis techniques. On the other hand, transcriptomics data have known limitations. The systems biology field is therefore, moving to proteomics in order to provide a more comprehensive view of cellular dynamics. The expression level of protein phosphorylation is one type of proteomic data that can augment gene expression data in order to provide a more complete view of cellular signaling.

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