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The Hi-C assay generates such interactions maps genome-wide, but at relatively low resolutions (e.g. 5-25 kb), which is substantially coarser than the resolution of transcription factor binding sites or open chromatin sites that are potential sources of such interactions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>To predict the sources of Hi-C-identified interactions at a high resolution (e.g. 100\u2009bp), we developed a computational method that integrates data from DNase-seq and ChIP-seq of TFs and histone marks. Our method, \u03c7-CNN, uses this data to first train a convolutional neural network (CNN) to discriminate between called Hi-C interactions and non-interactions. \u03c7-CNN then predicts the high-resolution source of each Hi-C interaction using a feature attribution method. We show these predictions recover original Hi-C peaks after extending them to be coarser. We also show \u03c7-CNN predictions enrich for evolutionarily conserved bases, eQTLs and CTCF motifs, supporting their biological significance. \u03c7-CNN provides an approach for analyzing important aspects of genome architecture and gene regulation at a higher resolution than previously possible.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>\u03c7-CNN software is available on GitHub (https:\/\/github.com\/ernstlab\/X-CNN).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btz843","type":"journal-article","created":{"date-parts":[[2019,11,18]],"date-time":"2019-11-18T06:36:19Z","timestamp":1574058979000},"page":"1704-1711","source":"Crossref","is-referenced-by-count":6,"title":["An integrative approach for fine-mapping chromatin interactions"],"prefix":"10.1093","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1255-3097","authenticated-orcid":false,"given":"Artur","family":"Jaroszewicz","sequence":"first","affiliation":[{"name":"Bioinformatics Interdepartmental Program, University of California , Los Angeles, Los Angeles, CA 90095, USA"},{"name":"Department of Biological Chemistry, University of California , Los Angeles, Los Angeles, CA 90095, USA"}]},{"given":"Jason","family":"Ernst","sequence":"additional","affiliation":[{"name":"Bioinformatics Interdepartmental Program, University of California , Los Angeles, Los Angeles, CA 90095, USA"},{"name":"Department of Biological Chemistry, University of California , Los Angeles, Los Angeles, CA 90095, USA"},{"name":"Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California , Los Angeles, Los Angeles, CA 90095, USA"},{"name":"Computer Science Department, University of California , Los Angeles, Los Angeles, CA 90095, USA"},{"name":"Jonsson Comprehensive Cancer Center, University of California , Los Angeles, Los Angeles, CA 90095, USA"},{"name":"Molecular Biology Institute, University of California , Los Angeles, Los Angeles, CA 90095, USA"}]}],"member":"286","published-online":{"date-parts":[[2019,11,19]]},"reference":[{"key":"2023061002090850300_btz843-B1","first-page":"265","author":"Abadi","year":"2016"},{"key":"2023061002090850300_btz843-B2","doi-asserted-by":"crossref","first-page":"999","DOI":"10.1101\/gr.160374.113","article-title":"Statistical confidence estimation for Hi-C data reveals regulatory chromatin contacts","volume":"24","author":"Ay","year":"2014","journal-title":"Genome Res"},{"key":"2023061002090850300_btz843-B3","first-page":"279","author":"Ballard","year":"1987"},{"key":"2023061002090850300_btz843-B4","first-page":"281","article-title":"Random search for hyper-parameter optimization","volume":"13","author":"Bergstra","year":"2012","journal-title":"J. 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