Parallelization of a Method to Infer Genetic Networks in Multi-CPU Systems

• Javier Darriba ^[1] ; Jorge González ^[1]
  1. [1] Universidade da Coruña

     Universidade da Coruña

     A Coruña, España

     
• Localización: Proceedings XoveTIC 2024: Impulsando el talento científico / coord. por Manuel Lagos Rodríguez, Tirso Varela Rodeiro, Javier Pereira-Loureiro, Manuel Penedo, 2024, págs. 33-40
• Idioma: inglés
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• Resumen

  • Genetic regulatory networks represent the interactions present between genes and are a crucial step in understanding cellular physiology and complex pathological phenotypes. There are various methods to infer these networks from a set of genetic data. Among them, the MRNET method stands out, which is based on the mRMR feature selection algorithm. However, constructing genetic regulatory networks with MRNET is a computationally expensive process for large-scale datasets due to its cubic complexity concerning the number of genes. The objective of this work is to develop parallel versions of MRNET that can be executed on shared-memory parallel systems to accelerate its execution.