Inference of Gene Regulatory Network Based on Legendre Neural Network

Inference of gene regulatory network based on gene expression data is one of the biggest challenges in system biology. In this paper, Legendre neural network (LNN) is proposed to infer gene regulatory network (GRN). Firefly algorithm (FA) is used to optimize the parameters of LNN. E.coli dataset from DREAM5 challenge is used to test the performance of LNN. The results reveal that our method performs better than popular inferred methods.