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Extensive functional genomic and multi-omic data sets have enabled the discovery and characterisation of \u2018essential\u2019 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\n                    <jats:italic toggle=\"yes\">C. elegans<\/jats:italic>\n                    and\n                    <jats:italic toggle=\"yes\">D. melanogaster<\/jats:italic>\n                    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 non-model organisms within the same group (phylum) of protostome animals. In the present investigation, we cross-predicted essential genes within the phylum Nematoda \u2013 between\n                    <jats:italic toggle=\"yes\">C. elegans<\/jats:italic>\n                    and the parasitic filarial nematodes\n                    <jats:italic toggle=\"yes\">Brugia malayi<\/jats:italic>\n                    and\n                    <jats:italic toggle=\"yes\">Onchocerca volvulus<\/jats:italic>\n                    , and then ranked and prioritised these genes. Highly ranked genes were linked to key biological pathways or processes, such as ribosome biogenesis, translation and RNA processing, and were expressed at relatively high levels in the germline, gonad, hypodermis and\/or nerves. The present\n                    <jats:italic toggle=\"yes\">in silico<\/jats:italic>\n                    workflow is hoped to expedite the identification of drug targets in parasitic organisms for subsequent experimental validation in the laboratory.\n                  <\/jats:p>","DOI":"10.1016\/j.csbj.2024.07.025","type":"journal-article","created":{"date-parts":[[2024,8,2]],"date-time":"2024-08-02T07:13:49Z","timestamp":1722582829000},"page":"3081-3089","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":4,"title":["Inference of essential genes in\n                    <i>Brugia malayi<\/i>\n                    and\n                    <i>Onchocerca volvulus<\/i>\n                    by machine learning and the implications for discovering new interventions"],"prefix":"10.34133","volume":"23","author":[{"given":"T\u00falio L.","family":"Campos","sequence":"first","affiliation":[{"name":"Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, Victoria 3010, Australia"},{"name":"N\u00facleo de Bioinform\u00e1tica, Instituto Aggeu Magalh\u00e3es, Fiocruz., Av. Professor Moraes Rego, s\/n, Cidade Universit\u00e1ria, Recife,\u00a0PE\u00a0CEP 50740\u2013465, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pasi K.","family":"Korhonen","sequence":"additional","affiliation":[{"name":"Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, Victoria 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Neil D.","family":"Young","sequence":"additional","affiliation":[{"name":"Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, Victoria 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bill C.H.","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, Victoria 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robin B.","family":"Gasser","sequence":"additional","affiliation":[{"name":"Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, Victoria 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"221","published-online":{"date-parts":[[2024,8,2]]},"reference":[{"key":"e_1_4_1_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cppeds.2009.01.001"},{"key":"e_1_4_1_3_2","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1159\/000345752","article-title":"Arbonematodes - nematode infections transmissible by arthropods","volume":"40","author":"Khan S.","year":"2013","unstructured":"KhanS.HallT.C.LandW.G.Dov\u010d-Drnov\u0161ekT.KlemencP.ToplakN.Arbonematodes - nematode infections transmissible by arthropodsTransfus Med Hemother402013506223637651","journal-title":"Transfus Med Hemother"},{"key":"e_1_4_1_4_2","first-page":"137","article-title":"Parasitic diseases in humans transmitted by vectors","volume":"61","author":"Cholewinski M.","year":"2015","unstructured":"CholewinskiM.DerdaM.HadasE.Parasitic diseases in humans transmitted by vectorsAnn Parasitol61201513715726568987","journal-title":"Ann Parasitol"},{"key":"e_1_4_1_5_2","doi-asserted-by":"crossref","unstructured":"Berenger J.-M. 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