Towards BIMAX: Binary Inclusion-MAXimal Parallel Implementation for Gene Expression Analysis Alejandra

Authors

  • Angélica Alejandra Serrano Rubio Centro de Investigación y de Estudios Avanzados
  • Amilcar Meneses Viveros Centro de Investigación y de Estudios Avanzados
  • Guillermo B. Morales Luna Centro de Investigación y de Estudios Avanzados
  • Mireya Paredes López Universidad de las Américas Puebla, Departamento de Computación, Electrónica y Mecatrónica

DOI:

https://doi.org/10.13053/cys-1-1-2979

Keywords:

Biclustering, clustering, gene expression, high-performance computing, parallelism

Abstract

Differential gene expression analysis and clustering techniques have been current tools to study the relation between a gene and biological processes. Since a group of genes may show co-expression under certain conditions, biclustering techniques have been used to find sets of genes sharing similar expression patterns. We present an analysis of the performance of the BIMAX: Binary Inclusion-MAXimal sequential biclustering algorithm. Its performance is evaluated using synthetic datasets. Finally, we propose a strategy of parallelization for optimizing the performance of the BIMAX using parallel programming techniques.

Author Biography

Angélica Alejandra Serrano Rubio, Centro de Investigación y de Estudios Avanzados

Researcher

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Published

2020-03-25

Issue

Vol. 24 No. 1 (2020): 24(1)2020

Section

Articles

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