{"id":"https://openalex.org/W2977338442","doi":"https://doi.org/10.1186/s12859-019-3049-1","title":"AIKYATAN: mapping distal regulatory elements using convolutional learning on GPU","display_name":"AIKYATAN: mapping distal regulatory elements using convolutional learning on GPU","publication_year":2019,"publication_date":"2019-10-07","ids":{"openalex":"https://openalex.org/W2977338442","doi":"https://doi.org/10.1186/s12859-019-3049-1","mag":"2977338442","pmid":"https://pubmed.ncbi.nlm.nih.gov/31590652"},"language":"en","primary_location":{"id":"doi:10.1186/s12859-019-3049-1","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-019-3049-1","pdf_url":"https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-019-3049-1.pdf","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-019-3049-1.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055672710","display_name":"Chih-Hao Fang","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chih-Hao Fang","raw_affiliation_strings":["Department of Ag. and Biological Engineering, Purdue University, West Lafayette, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Ag. and Biological Engineering, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070708809","display_name":"Nawanol Theera-Ampornpunt","orcid":"https://orcid.org/0000-0002-7594-8061"},"institutions":[{"id":"https://openalex.org/I131868736","display_name":"Prince of Songkla University","ror":"https://ror.org/0575ycz84","country_code":"TH","type":"education","lineage":["https://openalex.org/I131868736"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Nawanol Theera-Ampornpunt","raw_affiliation_strings":["College of Computing, Prince of Songkla University, Bangkok, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computing, Prince of Songkla University, Bangkok, Thailand","institution_ids":["https://openalex.org/I131868736"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103430368","display_name":"Michael A. Roth","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael A. Roth","raw_affiliation_strings":["Google Inc., Mountain View, California, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Inc., Mountain View, California, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019202832","display_name":"Ananth Grama","orcid":"https://orcid.org/0000-0002-9378-9244"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ananth Grama","raw_affiliation_strings":["Department of Ag. and Biological Engineering, Purdue University, West Lafayette, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Ag. and Biological Engineering, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055585728","display_name":"Somali Chaterji","orcid":"https://orcid.org/0000-0002-3651-6362"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Somali Chaterji","raw_affiliation_strings":["Department of Ag. and Biological Engineering, Purdue University, Purdue University, IN, USA. schaterji@schaterji.io","Department of Ag. and Biological Engineering, Purdue University, Purdue University, IN, USA"],"raw_orcid":"https://orcid.org/0000-0002-3651-6362","affiliations":[{"raw_affiliation_string":"Department of Ag. and Biological Engineering, Purdue University, Purdue University, IN, USA. schaterji@schaterji.io","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"Department of Ag. and Biological Engineering, Purdue University, Purdue University, IN, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5055585728"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":{"value":2790,"currency":"USD","value_usd":2790},"apc_paid":{"value":2790,"currency":"USD","value_usd":2790},"fwci":0.0761,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.43314684,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"20","issue":"1","first_page":"488","last_page":"488"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10222","display_name":"Genomics and Chromatin Dynamics","score":0.8827999830245972,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10222","display_name":"Genomics and Chromatin Dynamics","score":0.8827999830245972,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.08139999955892563,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11642","display_name":"Genomics and Rare Diseases","score":0.007300000172108412,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7810347080230713},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7329344749450684},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6206191182136536},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5842151045799255},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5054001808166504},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.49753955006599426},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.49239814281463623},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.49041080474853516},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48195454478263855},{"id":"https://openalex.org/keywords/epigenomics","display_name":"Epigenomics","score":0.4753689169883728},{"id":"https://openalex.org/keywords/enhancer","display_name":"Enhancer","score":0.4469946622848511},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4440328776836395},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3942640721797943},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.13716340065002441},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.11876732110977173},{"id":"https://openalex.org/keywords/transcription-factor","display_name":"Transcription factor","score":0.11450117826461792}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7810347080230713},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7329344749450684},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6206191182136536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5842151045799255},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5054001808166504},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.49753955006599426},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.49239814281463623},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.49041080474853516},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48195454478263855},{"id":"https://openalex.org/C121912465","wikidata":"https://www.wikidata.org/wiki/Q3589153","display_name":"Epigenomics","level":5,"score":0.4753689169883728},{"id":"https://openalex.org/C111936080","wikidata":"https://www.wikidata.org/wiki/Q913367","display_name":"Enhancer","level":4,"score":0.4469946622848511},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4440328776836395},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3942640721797943},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.13716340065002441},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.11876732110977173},{"id":"https://openalex.org/C86339819","wikidata":"https://www.wikidata.org/wiki/Q407384","display_name":"Transcription factor","level":3,"score":0.11450117826461792},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C190727270","wikidata":"https://www.wikidata.org/wiki/Q874745","display_name":"DNA methylation","level":4,"score":0.0},{"id":"https://openalex.org/C150194340","wikidata":"https://www.wikidata.org/wiki/Q26972","display_name":"Gene expression","level":3,"score":0.0}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D002460","descriptor_name":"Cell Line","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002460","descriptor_name":"Cell Line","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002460","descriptor_name":"Cell Line","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002874","descriptor_name":"Chromosome Mapping","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D002874","descriptor_name":"Chromosome Mapping","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D002874","descriptor_name":"Chromosome Mapping","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012045","descriptor_name":"Regulatory Sequences, Nucleic Acid","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012045","descriptor_name":"Regulatory Sequences, Nucleic Acid","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012045","descriptor_name":"Regulatory Sequences, Nucleic Acid","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012984","descriptor_name":"Software","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012984","descriptor_name":"Software","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012984","descriptor_name":"Software","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D057890","descriptor_name":"Epigenomics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057890","descriptor_name":"Epigenomics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057890","descriptor_name":"Epigenomics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1186/s12859-019-3049-1","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-019-3049-1","pdf_url":"https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-019-3049-1.pdf","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},{"id":"pmid:31590652","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31590652","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC bioinformatics","raw_type":null},{"id":"pmh:oai:doaj.org/article:02aa026752414ec69617c939aee7594d","is_oa":true,"landing_page_url":"https://doaj.org/article/02aa026752414ec69617c939aee7594d","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Bioinformatics, Vol 20, Iss 1, Pp 1-17 (2019)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:6781298","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6781298","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Bioinformatics","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s12859-019-3049-1","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-019-3049-1","pdf_url":"https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-019-3049-1.pdf","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.6800000071525574}],"awards":[{"id":"https://openalex.org/G1617410416","display_name":null,"funder_award_id":"R01 AI123037","funder_id":"https://openalex.org/F4320337355","funder_display_name":"National Institute of Allergy and Infectious Diseases"},{"id":"https://openalex.org/G6803708143","display_name":"Continued Development and Maintenance of the MG-RAST Metagenomics Pipeline","funder_award_id":"5r01ai123037-05","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337355","display_name":"National Institute of Allergy and Infectious Diseases","ror":"https://ror.org/043z4tv69"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2977338442.pdf","grobid_xml":"https://content.openalex.org/works/W2977338442.grobid-xml"},"referenced_works_count":61,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W1523493493","https://openalex.org/W1568892534","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1865894638","https://openalex.org/W1951403192","https://openalex.org/W1986865417","https://openalex.org/W2007203150","https://openalex.org/W2016015848","https://openalex.org/W2019251848","https://openalex.org/W2019961381","https://openalex.org/W2052815101","https://openalex.org/W2055327776","https://openalex.org/W2073700708","https://openalex.org/W2074531605","https://openalex.org/W2077624120","https://openalex.org/W2079407198","https://openalex.org/W2084160423","https://openalex.org/W2097117768","https://openalex.org/W2100495367","https://openalex.org/W2104846587","https://openalex.org/W2110652811","https://openalex.org/W2135106139","https://openalex.org/W2137396228","https://openalex.org/W2140240158","https://openalex.org/W2144015117","https://openalex.org/W2146502635","https://openalex.org/W2149298154","https://openalex.org/W2158899491","https://openalex.org/W2160815625","https://openalex.org/W2163605009","https://openalex.org/W2168029744","https://openalex.org/W2194775991","https://openalex.org/W2206396100","https://openalex.org/W2259938310","https://openalex.org/W2282866165","https://openalex.org/W2286501826","https://openalex.org/W2308092540","https://openalex.org/W2332754646","https://openalex.org/W2402144811","https://openalex.org/W2475924856","https://openalex.org/W2511261638","https://openalex.org/W2513671774","https://openalex.org/W2550848904","https://openalex.org/W2560048654","https://openalex.org/W2621774891","https://openalex.org/W2763574125","https://openalex.org/W2769715796","https://openalex.org/W2774691683","https://openalex.org/W2774733631","https://openalex.org/W2799357357","https://openalex.org/W2804974840","https://openalex.org/W2807545768","https://openalex.org/W2899771611","https://openalex.org/W2950980382","https://openalex.org/W2963371736","https://openalex.org/W3101749733","https://openalex.org/W3105432754","https://openalex.org/W6607090173","https://openalex.org/W6713134421"],"related_works":["https://openalex.org/W2113330652","https://openalex.org/W2361861616","https://openalex.org/W2061914098","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W4309683845","https://openalex.org/W2392921965","https://openalex.org/W2118646732","https://openalex.org/W4387565139"],"abstract_inverted_index":{"BACKGROUND:":[0],"The":[1,16,298],"data":[2,257],"deluge":[3],"can":[4,253,286],"leverage":[5],"sophisticated":[6],"ML":[7,112,239],"techniques":[8],"for":[9,24,128,200,244,311],"functionally":[10],"annotating":[11],"the":[12,21,25,31,34,38,80,86,115,153,158,162,182,189,214,226,242,303,307,313],"regulatory":[13,49,65,81,130,316],"non-coding":[14],"genome.":[15],"challenge":[17],"lies":[18],"in":[19],"selecting":[20],"appropriate":[22],"classifier":[23,58],"specific":[26],"functional":[27,326],"annotation":[28],"problem,":[29],"within":[30,99],"bounds":[32],"of":[33,111,172,177,238,265,276,306],"hardware":[35],"constraints":[36],"and":[37,95,97,124,174,196,202,225,259,271,295],"model's":[39],"complexity.":[40],"In":[41,261],"our":[42,206],"system":[43],"AIKYATAN,":[44,117],"we":[45,54],"annotate":[46],"distal":[47,64,84,129,314],"epigenomic":[48,283,309],"sites,":[50],"e.g.,":[51],"enhancers.":[52],"Specifically,":[53,216],"develop":[55,108],"a":[56,109,144,187,245,263],"binary":[57],"that":[59,247,285],"classifies":[60],"genome":[61],"sequences":[62],"as":[63,229],"regions":[66,82],"or":[67],"not,":[68],"given":[69],"their":[70],"histone":[71],"modifications'":[72],"combinatorial":[73],"signatures.":[74],"This":[75],"problem":[76],"is":[77,192,248,300],"challenging":[78],"because":[79],"are":[83],"to":[85,157,301,322],"genes,":[87],"with":[88,136,255,292,325],"diverse":[89,282],"signatures":[90],"across":[91],"classes":[92],"(e.g.,":[93,102],"enhancers":[94],"insulators)":[96],"even":[98],"each":[100],"class":[101],"different":[103],"enhancer":[104],"sub-classes).":[105],"RESULTS:":[106],"We":[107,134],"suite":[110,280],"models,":[113,120],"under":[114],"banner":[116],"including":[118],"SVM":[119],"random":[121],"forest":[122],"variants,":[123],"deep":[125,140],"learning":[126,141],"architectures,":[127],"element":[131],"(DRE)":[132],"detection.":[133],"demonstrate,":[135],"strong":[137],"empirical":[138],"evidence,":[139],"approaches":[142],"have":[143,268,319],"computational":[145],"advantage.":[146],"Plus,":[147],"convolutional":[148],"neural":[149],"networks":[150],"(CNN)":[151],"provide":[152],"best-in-class":[154],"accuracy,":[155],"superior":[156,210],"vanilla":[159],"variant.":[160],"With":[161],"human":[163],"embryonic":[164],"cell":[165],"line":[166],"H1,":[167],"CNN":[168,207],"achieves":[169],"an":[170,175,236],"accuracy":[171,228],"97.9%":[173],"order":[176],"magnitude":[178],"lower":[179],"runtime":[180],"than":[181],"kernel":[183],"SVM.":[184],"Running":[185],"on":[186],"GPU,":[188],"training":[190],"time":[191],"sped":[193],"up":[194],"21x":[195],"30x":[197],"(over":[198],"CPU)":[199],"DNN":[201],"CNN,":[203],"respectively.":[204],"Finally,":[205],"model":[208,246],"enjoys":[209],"prediction":[211],"performance":[212],"vis-'a-vis":[213],"competition.":[215],"AIKYATAN-CNN":[217],"achieved":[218],"40%":[219],"higher":[220],"validation":[221],"rate":[222],"versus":[223],"CSIANN":[224],"same":[227],"RFECS.":[230],"CONCLUSIONS:":[231],"Our":[232,278,328],"exhaustive":[233],"experiments":[234],"using":[235,290],"array":[237],"tools":[240],"validate":[241],"need":[243],"not":[249],"only":[250],"expressive":[251],"but":[252],"scale":[254],"increasing":[256],"volumes":[258],"diversity.":[260],"addition,":[262],"subset":[264],"these":[266],"datasets":[267,284,310],"image-like":[269],"properties":[270],"benefit":[272],"from":[273],"spatial":[274],"pooling":[275,296],"features.":[277],"AIKYATAN":[279],"leverages":[281],"then":[287],"be":[288,323,332],"modeled":[289],"CNNs":[291],"optimized":[293],"activation":[294],"functions.":[297],"goal":[299],"capture":[302],"salient":[304],"features":[305],"integrated":[308],"deciphering":[312],"(non-coding)":[315],"elements,":[317],"which":[318],"been":[320],"found":[321],"associated":[324],"variants.":[327],"source":[329],"code":[330],"will":[331],"made":[333],"publicly":[334],"available":[335],"at:":[336],"https://bitbucket.org/cellsandmachines/aikyatan.":[337]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-10-10T00:00:00"}