title: RapidMic: Rapid Computation of the Maximal Information Coefficient.
abstract: To discover relationships and associations rapidly in large-scale datasets, we propose a cross-platform tool for the rapid computation of the maximal information coefficient based on parallel computing methods. Through parallel processing, the provided tool can effectively analyze large-scale biological datasets with a markedly reduced computing time. The experimental results show that the proposed tool is notably fast, and is able to perform an all-pairs analysis of a large biological dataset using a normal computer. The source code and guidelines can be downloaded from https://github.com/HelloWorldCN/RapidMic.
authors: Institute of Information Research, Southwest Jiaotong University, Chengdu, China.
authors: Dongming
authors: D
authors: Tang
authors: School of Mathematics, Southwest Jiaotong University, Chengdu, China.
authors: Mingwen
authors: M
authors: Wang
authors: Institute of Information Research, Southwest Jiaotong University, Chengdu, China.
authors: Weifan
authors: W
authors: Zheng
authors: School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China.
authors: Hongjun
authors: H
authors: Wang
keywords: algorithms; computational biology; gene expression; software; statistical analysis