DEEP LEARNING METHODS FOR BIOSYNTHETIC GENE CLUSTER DISCOVERY

The present disclosure relates to computer-implemented methods and systems for identifying biosynthetic gene clusters (BGCs) that encode pathways for the production of secondary metabolites. Secondary metabolites that target genes or gene products that are homologous to, e.g., human genes or gene pr...

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Bibliographic Details
Main Authors DIMUCCI, DEMETRIUS MICHAEL, DING, MICHAEL QI, VERDINE, GREG, ZHANG, NANCY ANN, MCFADYEN, IAIN JAMES, HADJITHOMAS, MICHALIS
Format Patent
LanguageEnglish
French
Published 01.06.2023
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS
PHYSICS
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Summary:The present disclosure relates to computer-implemented methods and systems for identifying biosynthetic gene clusters (BGCs) that encode pathways for the production of secondary metabolites. Secondary metabolites that target genes or gene products that are homologous to, e.g., human genes or gene products may have utility as potential drug compounds. La présente divulgation concerne des procédés et des systèmes mis en ?uvre par ordinateur pour identifier des groupes de gènes biosynthétiques (BGC) qui codent des voies pour la production de métabolites secondaires. Des métabolites secondaires qui ciblent des gènes ou des produits géniques qui sont homologues, par exemple, à des gènes ou des produits géniques humains peuvent avoir une utilité en tant que composés médicamenteux potentiels.
Bibliography:Application Number: CA20223238783