Trader as a new optimization algorithm predicts drug-target interactions efficiently

P14: Mitochondria as a Target for Drug Therapy in Epilepsy

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Developing Adaptive Differential Evolution as a New Evolutionary Algorithm, Application in Optimization of Chemical Processes

Predicting Drug-Target Interactions Using Drug-Drug Interactions

Computational methods for predicting drug-target interactions have become important in drug research because they can help to reduce the time, cost, and failure rates for developing new drugs. Recently, with the accumulation of drug-related data sets related to drug side effects and pharmacological data, it has became possible to predict potential drug-target interactions. In this study, we foc...

A New Numerical Algorithm for Efficiently

To efficiently implement implicit Runge-Kutta (IRK) methods for solving large scale stiff ordinary differential equation systems, this paper proposes a new numerical algorithm, which contains a new modified Newton iterative method for solving the nonlinear stage equations of IRK, and two new rules for controlling the updating of Jacobian matrices. A convergence analysis shows that the new modif...

DASPfind: new efficient method to predict drug–target interactions

BACKGROUND Identification of novel drug-target interactions (DTIs) is important for drug discovery. Experimental determination of such DTIs is costly and time consuming, hence it necessitates the development of efficient computational methods for the accurate prediction of potential DTIs. To-date, many computational methods have been proposed for this purpose, but they suffer the drawback of a ...