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 DING, Michael Qi, DIMUCCI, Demetrius Michael, HADJITHOMAS, Michalis, ZHANG, Nancy Ann, MCFADYEN, Iain James, VERDINE, Greg
Format Patent
LanguageEnglish
French
German
Published 02.10.2024
Subjects
BEER
BIOCHEMISTRY
CALCULATING
CHEMISTRY
COMPOSITIONS THEREOF
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
CULTURE MEDIA
ENZYMOLOGY
HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA
INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS
METALLURGY
MICROBIOLOGY
MICROORGANISMS OR ENZYMES
MUTATION OR GENETIC ENGINEERING
PHYSICS
PROPAGATING, PRESERVING OR MAINTAINING MICROORGANISMS
SPIRITS
VINEGAR
WINE
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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.
Bibliography:Application Number: EP20220899561