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'Bingo' - a large language model- and graph neural network (LLM-GNN)-based workflow for the prediction of essential genes from protein data

  • Release time:2024-07-20
  • Hits:

  • Impact Factor: 

    9.5

  • Journal: 

    Briefings in Bioinformatics

  • Key Words: 

    essential gene prediction; large language model; graph neural network; adversarial training; biological interpretation

  • Abstract: 

    Theidentificationandcharacterizationofessentialgenesarecentraltoourunderstandingofthecorebiologicalfunctionsineukaryoticorganisms,andhasimportantimplicationsforthetreatmentofdiseasescausedby,forexample,cancersandpathogens.Giventhemajorconstraintsintestingthefunctionsofgenesofmanyorganismsinthelaboratory,duetotheabsenceofinvitroculturesand/orgeneperturbationassaysformostmetazoanspecies,therehasbeenaneedtodevelopinsilicotoolsfortheaccuratepredictionorinferenceofessentialgenestounderpinsystemsbiologicalinvestigations.Majoradvancesinmachinelearningapproachesprovideunprecedentedopportunitiestoovercometheselimitationsandacceleratethediscoveryofessentialgenesonagenome-widescale.Here,wedevelopedandevaluatedalargelanguagemodel-andgraphneuralnetwork(LLM–GNN)-basedapproach,called‘Bingo’,topredictessentialprotein-codinggenesinthemetazoanmodelorganismsCaenorhabditiselegansandDrosophilamelanogasteraswellasinMusmusculusandHomosapiens(aHepG2cellline)byintegratingLLMandGNNswithadversarialtraining.Bingopredictsessentialgenesundertwo‘zero-shot’scenarioswithtransferlearning,showingpromisetocompensateforalackofhigh-qualitygenomicandproteomicdatafornon-modelorganisms.Inaddition,theattentionmechanismsandGNNExplainerwereemployedtomanifestthefunctionalsitesandstructuraldomainwithmostcontributiontoessentiality.Inconclusion,Bingoprovidestheprospectofbeingabletoaccuratelyinfertheessentialgenesoflittle-orunder-studiedorganismsofinterest,andprovidesabiologicalexplanationforgeneessentiality.

  • Indexed by: 

    Journal paper

  • Document Type: 

    J

  • Translation or Not: 

    no

  • Date of Publication: 

    2024-01-12

  • Included Journals: 

    SCI

Attachments:

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