{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Fang H"],"funding":["Département Caractérisation et Élaboration des Produits Issus de l'Agriculture, Institut National de la Recherche Agronomique","Natural Science Foundation of Guangxi Province","National Natural Science Foundation of China","Département Caractérisation et Élaboration des Produits Issus de l’Agriculture, Institut National de la Recherche Agronomique"],"pagination":["4"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8962045"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["20(1)"],"pubmed_abstract":["<h4>Background</h4>The pathogen of banana Fusarium oxysporum f. sp. cubense race 4(Foc4) infects almost all banana species, and it is the most destructive. The molecular mechanism of the interactions between Fusarium oxysporum and banana still needs to be further investigated.<h4>Methods</h4>We use both the interolog and domain-domain method to predict the protein-protein interactions (PPIs) between banana and Foc4. The predicted protein interaction sequences are encoded by the conjoint triad and autocovariance method respectively to obtain continuous and discontinuous information of protein sequences. This information is used as the input data of the neural network model. The Long Short-Term Memory (LSTM) neural network five-fold cross-validation and independent test methods are used to v"],"journal":["Proteome science"],"pubmed_title":["Predicting protein-protein interactions between banana and Fusarium oxysporum f. sp. cubense race 4 integrating sequence and domain homologous alignment and neural network verification."],"pmcid":["PMC8962045"],"funding_grant_id":["GuiNongKe 2020YM106","2020GXNSFAA259004","61962004"],"pubmed_authors":["Fang H","Zhong C","Tang C"],"additional_accession":[]},"is_claimable":false,"name":"Predicting protein-protein interactions between banana and Fusarium oxysporum f. sp. cubense race 4 integrating sequence and domain homologous alignment and neural network verification.","description":"<h4>Background</h4>The pathogen of banana Fusarium oxysporum f. sp. cubense race 4(Foc4) infects almost all banana species, and it is the most destructive. The molecular mechanism of the interactions between Fusarium oxysporum and banana still needs to be further investigated.<h4>Methods</h4>We use both the interolog and domain-domain method to predict the protein-protein interactions (PPIs) between banana and Foc4. The predicted protein interaction sequences are encoded by the conjoint triad and autocovariance method respectively to obtain continuous and discontinuous information of protein sequences. This information is used as the input data of the neural network model. The Long Short-Term Memory (LSTM) neural network five-fold cross-validation and independent test methods are used to v","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Mar","modification":"2026-04-08T17:53:27.751Z","creation":"2024-11-20T15:46:28.338Z"},"accession":"S-EPMC8962045","cross_references":{"pubmed":["35351140"],"doi":["10.1186/s12953-022-00186-2"]}}