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LegNet: a best-in-class deep learning model for short DNA regulatory regions.
Penzar, Dmitry; Nogina, Daria; Noskova, Elizaveta; Zinkevich, Arsenii; Meshcheryakov, Georgy; Lando, Andrey; Rafi, Abdul Muntakim; de Boer, Carl; Kulakovskiy, Ivan V.
Affiliation
  • Penzar D; Vavilov Institute of General Genetics, Moscow 119991, Russia.
  • Nogina D; Institute of Protein Research, Pushchino 142290, Russia.
  • Noskova E; Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow 117997, Russia.
  • Zinkevich A; Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow 119991, Russia.
  • Meshcheryakov G; Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow 119991, Russia.
  • Lando A; Vavilov Institute of General Genetics, Moscow 119991, Russia.
  • Rafi AM; Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow 119991, Russia.
  • de Boer C; Institute of Protein Research, Pushchino 142290, Russia.
  • Kulakovskiy IV; Yandex N.V., Moscow 119021, Russia.
Bioinformatics ; 39(8)2023 08 01.
Article in En | MEDLINE | ID: mdl-37490428
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Deep Learning Type of study: Prognostic_studies Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2023 Type: Article Affiliation country: RUSSIA
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Deep Learning Type of study: Prognostic_studies Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2023 Type: Article Affiliation country: RUSSIA