Applying Deep Neural Network Analysis to High-Content Image-Based Assays.

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作者： Samuel J,Yang ^[1] ; Scott L,Lipnick ^[2] ; Nina R,Makhortova ^[3] ; Subhashini,Venugopalan ^[4] ; Minjie,Fan ^[2] ; Zan,Armstrong ^[5] ; Thorsten M,Schlaeger ^[1] ; Liyong,Deng ^[1] ; Wendy K,Chung ^[1] ; Liadan,O'Callaghan ^[5] ; Anton,Geraschenko ^[6] ; Dosh,Whye ^[6] ; Marc,Berndl ^[1] ; Jon,Hazard ^[1] ; Brian,Williams ^[2] ; Arunachalam,Narayanaswamy ^[1] ; D Michael,Ando ^[1] ; Philip,Nelson ^[1] ; Lee L,Rubin ^[1]

作者单位： 1 Google, LLC, Mountain View, CA, USA. ^[1] 2 Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA. ^[2] 3 Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. ^[3] 4 Center for Assessment Technology & Continuous Health (CATCH), Massachusetts General Hospital, Boston, MA, USA. ^[4] 5 Stem Cell Program, Boston Children's Hospital, Boston, MA, USA. ^[5] 6 Departments of Pediatrics and Medicine, Columbia University Medical Center, New York, NY, USA. ^[6] 7 Harvard Stem Cell Institute, Cambridge, MA, USA. ^[7]

关键词 assay development deep learning disease modeling high-content screening spinal muscular atrophy

主题词高通量筛选分析(High-Throughput Screening Assays);人类(Humans);图像处理, 计算机辅助(Image Processing, Computer-Assisted);分子显像(Molecular Imaging)

DOI 10.1177/2472555219857715

PMID 31284814

发布时间 2022-08-30

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SLAS discovery

2019年24卷8期

829-841页

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Applying Deep Neural Network Analysis to High-Content Image-Based Assays.

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Applying Deep Neural Network Analysis to High-Content Image-Based Assays.

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