{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/dilated-convolutions-for-modeling-long","title":"Dilated Convolutions for Modeling Long-Distance Genomic Dependencies","arxiv_id":"1710.01278","date":"2017-10-03","proceeding":null,"authors":["Ankit Gupta","Alexander M. Rush"],"abstract":"We consider the task of detecting regulatory elements in the human genome\ndirectly from raw DNA. Past work has focused on small snippets of DNA, making\nit difficult to model long-distance dependencies that arise from DNA's\n3-dimensional conformation. In order to study long-distance dependencies, we\ndevelop and release a novel dataset for a larger-context modeling task. Using\nthis new data set we model long-distance interactions using dilated\nconvolutional neural networks, and compare them to standard convolutions and\nrecurrent neural networks. We show that dilated convolutions are effective at\nmodeling the locations of regulatory markers in the human genome, such as\ntranscription factor binding sites, histone modifications, and DNAse\nhypersensitivity sites.","url_abs":"http://arxiv.org/abs/1710.01278v1","url_pdf":"http://arxiv.org/pdf/1710.01278v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"dilated-convolutions-for-modeling-long","repo_url":"https://github.com/harvardnlp/regulatory-prediction","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1710.01278","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}