Parallel programming in biological sciences, taking advantage of supercomputing in genomics

Abstract

New sequencing technologies has been increasing the size of current genomes rapidly reducing its cost at the same time, those data need to be processed with efficient and innovated tools using high performance computing (HPC), but for taking advantage of nowadays supercomputers, parallel programming techniques and strategies have to be used. Plant genomes are full of Long Terminal Repeat Retrotransposons (LTR-RT), which are the most frequent repeated sequences; very important agronomical commodity such as Robusta Coffee and Maize have genomes that are composed by ~50% and ~85% respectively of this class of mobile elements, new parallel bioinformatics pipelines are making possible to use whole genomes like those in research projects, generating a lot of new information and impacting in many ways the knowledge that researchers have about them. Here we presented the utility of multi-core architectures and parallel programming for analyzing and classifying massive quantity of genomic information up to 16 times faster.