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CoRE-ATAC: A deep learning model for the functional classification of regulatory elements from single cell and bulk ATAC-seq data.

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Title: CoRE-ATAC: A deep learning model for the functional classification of regulatory elements from single cell and bulk ATAC-seq data.
Authors: Thibodeau, Asa1 (AUTHOR), Khetan, Shubham1 (AUTHOR), Eroglu, Alper1 (AUTHOR), Tewhey, Ryan2 (AUTHOR), Stitzel, Michael L.1,3,4 (AUTHOR), Ucar, Duygu1,3,4 (AUTHOR) duygu.ucar@jax.org
Source: PLoS Computational Biology. 12/13/2021, Vol. 17 Issue 12, p1-32. 32p. 1 Diagram, 3 Charts, 4 Graphs.
Database: Academic Search Ultimate
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  Data: CoRE-ATAC: A deep learning model for the functional classification of regulatory elements from single cell and bulk ATAC-seq data.
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  Data: <searchLink fieldCode="JN" term="%22PLoS+Computational+Biology%22">PLoS Computational Biology</searchLink>. 12/13/2021, Vol. 17 Issue 12, p1-32. 32p. 1 Diagram, 3 Charts, 4 Graphs.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=154101423
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        Value: 10.1371/journal.pcbi.1009670
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      – TitleFull: CoRE-ATAC: A deep learning model for the functional classification of regulatory elements from single cell and bulk ATAC-seq data.
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              Text: 12/13/2021
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