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A deep learning genome-mining strategy for biosynthetic gene cluster prediction.

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第一作者： Geoffrey D,Hannigan

第一单位： Exploratory Science Center, Merck & Co., Inc., Cambridge, Massachusetts, USA.

作者： Geoffrey D,Hannigan ^[1] ; David,Prihoda ^[2] ; Andrej,Palicka ^[3] ; Jindrich,Soukup ^[4] ; Ondrej,Klempir ^[5] ; Lena,Rampula ^[6] ; Jindrich,Durcak ^[5] ; Michael,Wurst ^[3] ; Jakub,Kotowski ^[3] ; Dan,Chang ^[7] ; Rurun,Wang ^[1] ; Grazia,Piizzi ^[1] ; Gergely,Temesi ^[5] ; Daria J,Hazuda ^[8] ; Christopher H,Woelk ^[1] ; Danny A,Bitton ^[5]

作者单位： Exploratory Science Center, Merck & Co., Inc., Cambridge, Massachusetts, USA. ^[1] Big Data Solutions, MSD Czech Republic s.r.o., Prague, Czech Republic.;Department of Informatics and Chemistry, Faculty of Chemical Technology, University of Chemistry and Technology, Prague, Czech Republic. ^[2] AI & Big Data Analytics, MSD Czech Republic s.r.o., Prague, Czech Republic. ^[3] Data Science, MSD Czech Republic s.r.o., Prague, Czech Republic. ^[4] Bioinformatics & Cheminformatics Solutions, MSD Czech Republic s.r.o., Prague, Czech Republic. ^[5] NLP, MSD Czech Republic s.r.o., Prague, Czech Republic. ^[6] Genetics & Pharmacogenomics, Merck & Co., Inc., Boston, MA, USA. ^[7] Exploratory Science Center, Merck & Co., Inc., Cambridge, Massachusetts, USA.;Infectious Diseases and Vaccine Research, MRL, Merck & Co., Inc., West Point, PA, USA. ^[8]

医学主题词生物合成途径(Biosynthetic Pathways);计算生物学(Computational Biology);数据挖掘(Data Mining);基因组(Genome);基因组, 细菌(Genome, Bacterial);多基因族(Multigene Family)

DOI 10.1093/nar/gkz654

PMID 31400112

发布时间 2019-12-03

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准确一般字义偏差语意偏离译文作用小提交