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Prediction of activity and specificity of CRISPR-Cpf1 using convolutional deep learning neural networks.
Luo, Jiesi; Chen, Wei; Xue, Li; Tang, Bin.
Affiliation
  • Luo J; Department of Pharmacology, Key Laboratory for Aging and Regenerative Medicine, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China. ljs@swmu.edu.cn.
  • Chen W; Center for Bioinformatics and Systems Biology and Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA. ljs@swmu.edu.cn.
  • Xue L; Center for Bioinformatics and Systems Biology and Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA.
  • Tang B; School of Public Health, Southwest Medical University, Luzhou, Sichuan, China.
BMC Bioinformatics ; 20(1): 332, 2019 Jun 13.
Article in En | MEDLINE | ID: mdl-31195957
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Neural Networks, Computer / Endonucleases / CRISPR-Cas Systems / Deep Learning Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: BMC Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2019 Document type: Article Affiliation country: China Country of publication: United kingdom
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Neural Networks, Computer / Endonucleases / CRISPR-Cas Systems / Deep Learning Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: BMC Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2019 Document type: Article Affiliation country: China Country of publication: United kingdom