Random walk elephant swarm water search algorithm for identifying order-preserving submatrices in gene expression data: a new approach using elephant swarm water search algorithm

Abstract This research proposes a new variant of Elephant Swarm Water Search Algorithm (ESWSA), namely, Random Walk Elephant Swarm Water Search Algorithm (RW-ESWSA) to find order-preserving submatrices (OPSM) from gene expression data sets expressed in a matrix form. The OPSM is a submatrix where a subset of genes changes its expression rate in approximately similar manner in different conditions of a disease. This is the first attempt to identify OPSMs using metaheuristic approaches. In this work, the proposed variant RW-ESWSA, which has better exploration in the search strategy incorporating randomized walk or movements, proves its efficacy in its performance on benchmark functions and statistical analysis. Having better exploration capability, it has performed better than other metaheuristic algorithms in convergence analysis. Apart from benchmark functions, all these algorithms have been executed on two gene expression data sets: yeast and leukemia. The significant OPSMs have been retrieved using each of the algorithms.