Detectes deregulated subgraphs in biological networks based on expression differences of the involved genes or proteins. As input, CPLEX requires a biological network and a list of genes with scores that have been derived from expression data and mirror the degree of deregulation. After the scores of the genes have been mapped to the corresponding nodes of the network, our approach calculates the most deregulated subgraph that can be visualized using BiNA.
Aims at detecting the significantly deregulated signaling cascades in tumor cells. The FiDePa algorithm interprets expression differences between tumor and normal tissue and relies on gene set enrichment analysis (GSEA). Since our algorithm allows for comparing a single tumor expression profile with the control group, it facilitates the detection of specific regulatory features of a tumor that may help to optimize tumor therapy.
Enables the user to detect deregulated pathways and subgraphs in biological networks. NetworkTrail is a web service that allows non-experts to carry out network analyses without having to struggle with technical details, such as compiling/installing software or learning cryptic commands. This easy-to-use web services will help to elucidate pathogenic mechanisms, and may also prove to be useful for therapy stratification in cancer therapy.
A network-based classification algorithm using color coding technique to identify optimally discriminative subnetwork markers. Focusing on protein-protein interaction (PPI) networks, we apply our algorithm to drug response studies: we evaluate our algorithm using published cohorts of breast cancer patients treated with combination chemotherapy. We show that our OptDis method improves over previously published subnetwork methods and provides better and more stable performance compared with other subnetwork and single gene methods. We also show that our subnetwork method produces predictive markers that are more reproducible across independent cohorts and offer valuable insight into biological processes underlying response to therapy.
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