{"id":"https://openalex.org/W4406271295","doi":"https://doi.org/10.1109/bibm62325.2024.10822462","title":"Integrating Biological Language Processing and Memory Attention Model for Protein-DNA Binding Residue Prediction","display_name":"Integrating Biological Language Processing and Memory Attention Model for Protein-DNA Binding Residue Prediction","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4406271295","doi":"https://doi.org/10.1109/bibm62325.2024.10822462"},"language":"en","primary_location":{"id":"doi:10.1109/bibm62325.2024.10822462","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822462","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059750805","display_name":"Shixuan Guan","orcid":"https://orcid.org/0000-0003-4564-6297"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shixuan Guan","raw_affiliation_strings":["University of Tsukuba,Department of Computer Science,Tsukuba,Japan,3058577"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tsukuba,Department of Computer Science,Tsukuba,Japan,3058577","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072571384","display_name":"Xiucai Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xiucai Ye","raw_affiliation_strings":["University of Tsukuba,Department of Computer Science,Tsukuba,Japan,3058577"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tsukuba,Department of Computer Science,Tsukuba,Japan,3058577","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038336830","display_name":"Tetsuya Sakurai","orcid":"https://orcid.org/0000-0002-5789-7547"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsuya Sakurai","raw_affiliation_strings":["University of Tsukuba,Department of Computer Science,Tsukuba,Japan,3058577"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tsukuba,Department of Computer Science,Tsukuba,Japan,3058577","institution_ids":["https://openalex.org/I146399215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I146399215"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"25","last_page":"30"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9972000122070312,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9972000122070312,"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.9889000058174133,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6785932183265686},{"id":"https://openalex.org/keywords/residue","display_name":"Residue (chemistry)","score":0.44123658537864685},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.38124388456344604},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3375853896141052},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.180363267660141},{"id":"https://openalex.org/keywords/biochemistry","display_name":"Biochemistry","score":0.07366380095481873}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6785932183265686},{"id":"https://openalex.org/C2781338088","wikidata":"https://www.wikidata.org/wiki/Q903495","display_name":"Residue (chemistry)","level":2,"score":0.44123658537864685},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.38124388456344604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3375853896141052},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.180363267660141},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.07366380095481873}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm62325.2024.10822462","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822462","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5799999833106995}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2043638247","https://openalex.org/W2089716128","https://openalex.org/W2128533758","https://openalex.org/W2140538197","https://openalex.org/W2146315633","https://openalex.org/W2149997286","https://openalex.org/W2154139219","https://openalex.org/W2156136208","https://openalex.org/W2170747616","https://openalex.org/W2531919408","https://openalex.org/W2767813457","https://openalex.org/W2918335507","https://openalex.org/W2933350524","https://openalex.org/W3043233893","https://openalex.org/W3095319910","https://openalex.org/W3146944767","https://openalex.org/W3199041041","https://openalex.org/W3208957581","https://openalex.org/W4212940766","https://openalex.org/W4283316050","https://openalex.org/W4285414302","https://openalex.org/W4388296685","https://openalex.org/W4394715402","https://openalex.org/W4395660271","https://openalex.org/W4400803523","https://openalex.org/W6739901393","https://openalex.org/W6749669830","https://openalex.org/W6755207826"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Proteins":[0],"are":[1,32],"among":[2],"the":[3,8,44,56],"most":[4],"important":[5],"substances":[6],"in":[7,47,121],"human":[9],"body,":[10],"and":[11,35,103],"identifying":[12],"protein-DNA":[13,72,143],"binding":[14,73,144],"sites":[15],"is":[16],"crucial":[17],"for":[18,70],"studying":[19],"their":[20],"interactions.":[21],"Although":[22],"traditional":[23],"wet-lab":[24],"methods":[25],"can":[26],"accurately":[27],"identify":[28],"these":[29],"sites,":[30],"they":[31],"time-consuming,":[33],"labor-intensive,":[34],"expensive,":[36],"making":[37],"it":[38],"challenging":[39],"to":[40,82,99,138],"keep":[41],"pace":[42],"with":[43],"rapid":[45],"increase":[46],"protein":[48,87,135],"sequence":[49],"data.":[50],"In":[51],"this":[52],"study,":[53],"we":[54],"propose":[55],"Memory":[57,68,97],"Attention-Based":[58],"Protein-DNA":[59],"Binding":[60],"Sites":[61],"Prediction":[62],"(MAPDB)":[63],"model,":[64],"which":[65],"leverages":[66],"multi-head":[67],"Attention":[69,98],"predicting":[71],"sites.":[74],"Our":[75],"model":[76,115],"employs":[77],"a":[78,91],"pre-trained":[79],"embedding":[80],"module":[81,94],"generate":[83],"numerical":[84],"representations":[85],"of":[86,142],"sequences,":[88,136],"followed":[89],"by":[90],"feature":[92],"extraction":[93],"that":[95,113,128],"uses":[96],"capture":[100],"both":[101],"intra-sequence":[102],"inter-sequence":[104],"relationships.":[105],"Extensive":[106],"experiments":[107],"on":[108],"five":[109],"benchmark":[110],"datasets":[111],"show":[112],"our":[114],"outperforms":[116],"other":[117],"state-of-the-art":[118],"methods,":[119],"especially":[120],"improving":[122],"MCC":[123],"scores.":[124],"These":[125],"results":[126],"indicate":[127],"MAPDB":[129],"effectively":[130],"captures":[131],"complex":[132],"relationships":[133],"within":[134],"leading":[137],"more":[139],"accurate":[140],"predictions":[141],"residues.":[145]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}