Inference of essential genes in Brugia malayi and Onchocerca volvulus by machine learning and the implications for discovering new interventions.

ABSTRACT: Detailed explorations of the model organisms Caenorhabditis elegans (elegant worm) and Drosophila melanogaster (vinegar fly) have substantially improved our knowledge and understanding of biological processes and pathways in metazoan organisms. Extensive functional genomic and multi-omic data sets have enabled the discovery and characterisation of 'essential' genes that are critical for the survival of these organisms. Recently, we showed that a machine learning (ML)-based pipeline could be utilised to predict essential genes in both C. elegans and D. melanogaster using features from DNA, RNA, protein and/or cellular data or associated information. As these distantly-related species are within the Ecdysozoa, we hypothesised that this approach could be suited for

SUBMITTER: Campos TL 

PROVIDER: S-EPMC11342751 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature