Parallelization of ARACNe, an Algorithm for the Reconstruction of Gene Regulatory Networks
- Uxía Casal
- Jorge González-Domínguez 1
- María J. Martín
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1
Universidade da Coruña
info
- Alberto Alvarellos González (ed. lit.)
- José Joaquim de Moura Ramos (ed. lit.)
- Beatriz Botana Barreiro (ed. lit.)
- Javier Pereira Loureiro (ed. lit.)
- Manuel F. González Penedo (ed. lit.)
Publisher: MDPI
ISBN: 978-3-03921-444-0, 978-3-03921-443-3
Year of publication: 2019
Congress: XoveTIC (2. 2019. A Coruña)
Type: Conference paper
Abstract
Gene regulatory networks are graphical representations of molecular regulators that interact with each other and with other substances in the cell to govern the gene expression. There are different computational approaches for the reverse engineering of these networks. Most of them require all gene-gene evaluations using different mathematical methods such as Pearson/Spearman correlation, Mutual Information or topology patterns, among others. The Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) is one of the most effective and widely used tools toreconstruct gene regulatory networks. However, the high computational cost of ARACNe prevents its use over large biologic datasets. In this work, we present a hybrid MPI/OpenMP parallelimplementation of ARACNe to accelerate its execution on multi-core clusters, obtaining a speedup of 430.46 using as input a dataset with 41,100 genes and 108 samples and 32 nodes (each of them with 24 cores).