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The Computational Genomics Research group at NCI CBIIT participated in the HPN-DREAM breast cancer network inference challenge Breast Cancer Network Inference Challenge for the first time in 2013. The challenge comprises network inference, time-course prediction, and visualization of time-course data derived from proteomic experiments in cancer cell lines and in silico simulation. The group developed a novel approach to construct consensus networks and predict phosphoprotein trajectories under the influence of each inhibitor. The time-series data were visualized with in-house R package OmicCircos which is available at bioconductor.org. This novel diagram not only maintains the network structure but also displays the time-course change, biological annotations, and topological features. We submitted results to Synapse.org, a site that Sage Bionetworks has developed for data sharing and live scoring. Our prediction result of 20 phosphoproteins and 10 time points for the sub-challenge 2B "In silico time-course prediction" has been ranked as the best predictor. |
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