CNN-Peaks: ChIP-Seq peak detection pipeline using convolutional neural networks that imitate human visual inspection.
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| Title: | CNN-Peaks: ChIP-Seq peak detection pipeline using convolutional neural networks that imitate human visual inspection. |
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| Authors: | Oh D; School of Computer Science and Engineering, Pusan National University, Busan, 46241, South Korea., Strattan JS; Department of Genetics, Stanford University, Stanford, 94305, USA., Hur JK; School of Medicine, Kyung Hee University, Seoul, 02447, South Korea., Bento J; Department of Computer Science, Boston College, Chestnut Hill, Philadelphia, MA, 02467, USA., Urban AE; Department of Genetics, Stanford University, Stanford, 94305, USA., Song G; School of Computer Science and Engineering, Pusan National University, Busan, 46241, South Korea. gsong@pusan.ac.kr., Cherry JM; Department of Genetics, Stanford University, Stanford, 94305, USA. |
| Source: | Scientific reports [Sci Rep] 2020 May 13; Vol. 10 (1), pp. 7933. Date of Electronic Publication: 2020 May 13. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 2045-2322 |
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| DOI: | 10.1038/s41598-020-64655-4 |
