Journal article
Harnessing model organism genomics to underpin the machine learning-based prediction of essential genes in eukaryotes – Biotechnological implications
TL Campos, PK Korhonen, A Hofmann, RB Gasser, ND Young
Biotechnology Advances | Published : 2022
Abstract
The availability of high-quality genomes and advances in functional genomics have enabled large-scale studies of essential genes in model eukaryotes, including the ‘elegant worm’ (Caenorhabditis elegans; Nematoda) and the ‘vinegar fly’ (Drosophila melanogaster; Arthropoda). However, this is not the case for other, much less-studied organisms, such as socioeconomically important parasites, for which functional genomic platforms usually do not exist. Thus, there is a need to develop innovative techniques or approaches for the prediction, identification and investigation of essential genes. A key approach that could enable the prediction of such genes is machine learning (ML). Here, we undertak..
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Funding Acknowledgements
This research was supported by grants from the National Health and Medical Research Council (NHMRC) of Australia, the Australian Research Council (ARC) and Yourgene Health. TLC was the recipient of a Research Training Program Scholarship via The University of Melbourne and was supported by Fiocruz, Brazil (Fundacao Oswaldo Cruz/Instituto Aggeu Magalhaes-IAM) .