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NLLSS / Network-based Laplacian regularized Least Square Synergistic drug combination prediction
Conducts computational ‘screens’. NLLSS integrates several types of information such as known synergistic drug combinations, unlabeled combinations, drug-target interactions, and drug chemical structures. It is an efficient way to find potential synergistic antifungal combinations by exploring new indications of existing antifungal drugs. The tool is based on the framework of Laplacian Regularized Least Square (LapRLS).
CDA / Combinatorial Drug Assembler
Predicts combinatorial drug candidates that target multiple signaling pathways. CDA offers 6,100 expression profiles representing 1,309 molecules which were imported from Connectivity Map. It proceeds to hyper-geometric tests for signaling pathway gene set enrichment analysis. The tool generates lists of single drugs and combinatorial drugs showing similar expression patterns. It has been used to predict synergistic combinatorial drug pairs in lung cancer and triple negative breast cancer.
NIMS / Network target-based Identification of Multicomponent Synergy
Measures synergistic agent combinations. NIMS addresses the network target-based virtual screen and assesses the synergistic strength of multicomponent therapeutics. It captures the node importance from different aspects by integrating the three measures Betweenness, Closeness and PageRank. The tool was used to prioritize synergistic agent pairs from 63 manually collected agents and estimated their effects on angiogenesis.
PDC-SGB / Prediction of effective Drug Combinations using a Stochastic Gradient Boosting algorithm
Predicts effective drug combinations. PDC-SGB is based on a stochastic gradient boosting algorithm. It integrates biological, chemical and pharmacological information. The method aims to help narrow the search space of possible drug combinations. It integrates six types of features to describe the drug combinations, which include the molecular two-dimensional (2D) structures, structural similarity, anatomical therapeutic similarity, protein-protein interaction (PPI), chemical-chemical interaction, and disease pathways.
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