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DNA4mC-LIP: a linear integration method to identify N4-methylcytosine site in multiple species.
Tang, Qiang; Kang, Juanjuan; Yuan, Jiaqing; Tang, Hua; Li, Xianhai; Lin, Hao; Huang, Jian; Chen, Wei.
Afiliación
  • Tang Q; Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
  • Kang J; Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
  • Yuan J; Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
  • Tang H; Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
  • Li X; Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
  • Lin H; Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
  • Huang J; Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
  • Chen W; Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
Bioinformatics ; 36(11): 3327-3335, 2020 06 01.
Article en En | MEDLINE | ID: mdl-32108866
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: ADN / Aprendizaje Automático Tipo de estudio: Prognostic_studies Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido
Texto completo
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PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: ADN / Aprendizaje Automático Tipo de estudio: Prognostic_studies Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido