In silico-driven analysis of the Glossina morsitans morsitans antennae transcriptome in response to repellent or attractant compounds.

ABSTRACT:

Background

High-throughput sequencing generates large volumes of biological data that must be interpreted to make meaningful inference on the biological function. Problems arise due to the large number of characteristics p (dimensions) that describe each record [n] in the database. Feature selection using a subset of variables extracted from the large datasets is one of the approaches towards solving this problem.

Methodology

In this study we analyzed the transcriptome of Glossina morsitans morsitans (Tsetsefly) antennae after exposure to either a repellant (δ-nonalactone) or an attractant (ε-nonalactone). We identified 308 genes that were upregulated or downregulated due to exposure to a repellant (δ-nonalactone) or an attractant (ε-nonalactone) respect

SUBMITTER: Gakii C 

PROVIDER: S-EPMC8255069 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature