We propose a novel, high-level model of human learning and cognition, based on association forming. The model configures any input data stream featuring a high incidence of repeti...
In the last decade, recurrent neural networks (RNNs) have attracted more efforts in inferring genetic regulatory networks (GRNs), using time series gene expression data from micro...
Rui Xu, Ganesh K. Venayagamoorthy, Donald C. Wunsc...
In this work a hybrid training scheme for the supervised learning of feedforward neural networks is presented. In the proposed method, the weights of the last layer are obtained em...
—Transcriptional regulation by transcription factors (TFs) and microRNAs controls when and how much RNA is created. Due to technical limitations, the protein level expressions of...
Jia Meng, Hung-I Harry Chen, Jianqiu Zhang, Yidong...
Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant Colony Optimization (ACO) is one such algorithm based on s...