Biocomputing 2018 2017
DOI: 10.1142/9789813235533_0009
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Diffusion mapping of drug targets on disease signaling network elements reveals drug combination strategies

Abstract: The emergence of drug resistance to traditional chemotherapy and newer targeted therapies in cancer patients is a major clinical challenge. Reactivation of the same or compensatory signaling pathways is a common class of drug resistance mechanisms. Employing drug combinations that inhibit multiple modules of reactivated signaling pathways is a promising strategy to overcome and prevent the onset of drug resistance. However, with thousands of available FDA-approved and investigational compounds, it is infeasibl… Show more

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Cited by 12 publications
(10 citation statements)
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“…Thirdly, other pharmacological data resources, e.g., LINCS (reverse gene signature based data) [ 71 ], can be integrated to identify more drugs or prioritize drugs to eliminate the Ovarian CSCs. Also, the drug repositioning [ 72 – 74 ] and drug combination prediction [ 75 – 77 ] are not trivial tasks. In the future work, we will integrate additional data resources to prioritize targets and drug combinations to block multiple TF and signaling interplays to eliminate ovarian CSCs.…”
Section: Discussionmentioning
confidence: 99%
“…Thirdly, other pharmacological data resources, e.g., LINCS (reverse gene signature based data) [ 71 ], can be integrated to identify more drugs or prioritize drugs to eliminate the Ovarian CSCs. Also, the drug repositioning [ 72 – 74 ] and drug combination prediction [ 75 – 77 ] are not trivial tasks. In the future work, we will integrate additional data resources to prioritize targets and drug combinations to block multiple TF and signaling interplays to eliminate ovarian CSCs.…”
Section: Discussionmentioning
confidence: 99%
“…Then, the drug-drug distance matrix was obtained as a similarity matrix. Then, the propagation(AP) clustering algorithm 37,38 was employed to cluster drugs into sub-clusters.…”
Section: Drug Clustering Analysismentioning
confidence: 99%
“…For example, the connectivity map (CMAP) 12,13 and associated network analysis based drug combination prediction models have been used in this context 14,15 . In an analogous manner, message propagation-based models have been developed based on the confluence of drug targeting and genomics data 16,17 . A common thread in the preceding work has been the use of semi-supervised learning models, applied to multiple pharmacogenomics datasets, for drug combination prediction 18 .…”
Section: Introductionmentioning
confidence: 99%