Evolutionary Bioinformatics · 2014 · 28 citations · 9 references
ComputingBioinformaticsHigh-performance ComputingBig Data AnalyticsComputational BiologyGenomic Data AnalysisComputational GenomicsData ParallelismAll-pairs ComparisonsParallel Data ProcessingParallel Processing
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.
9
Detecting Novel Associations in Large Data Sets
David N. Reshef, Yakir Reshef, Hilary K. Finucane et al. · Science · 2011 · 3.4K citations
Comparing Statistical Methods for Constructing Large Scale Gene Networks
Jeffrey D. Allen, Yang Xie, Min Chen et al. · PLoS ONE · 2012 · 194 citations · Full text