Mohd Saberi Mohamad

TL;DR: Six inference approaches to infer gene regulatory networks from gene expression data are discussed: Boolean network, probabilistic Booleannetwork, ordinary differential equation, neural network, Bayesian network, and dynamic Bayesiannetwork.

TL;DR: It is argued that researchers in the field of energy optimization should use multi-agent systems at those junctures where it is necessary to model energy efficiency solutions that involve a wide range of factors, as well as context independence that they can achieve through the addition of new agents or agent organizations, enabling the development of energy-efficient solutions for smart cities and intelligent buildings.

TL;DR: Experimental results showed that the accuracy of finding the best solution and convergence speed performance of the proposed method is significantly better compared to those achieved by the existing methods.

TL;DR: An improved (modified) binary particle swarm optimization to select the small subset of informative genes that is relevant for the cancer classification by introducing particles' speed for giving the rate at which a particle changes its position, and a rule for updating particle's positions is proposed.

TL;DR: Differential Bees Flux Balance Analysis (DBFBA) with OptKnock is proposed to identify optimal gene knockout strategies for maximizing the production yield of desired phenotypes while sustaining the growth rate.