{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:10:26Z","timestamp":1750219826709,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":21,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,9,3]],"date-time":"2023-09-03T00:00:00Z","timestamp":1693699200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Hong Kong Research Grants Council grants GRF","award":["17113721"],"award-info":[{"award-number":["17113721"]}]},{"name":"Hong Kong Research Grants Council grants TRS","award":["T21-705\/20-N"],"award-info":[{"award-number":["T21-705\/20-N"]}]},{"name":"The Shenzhen Municipal Government General Program","award":["JCYJ20210324134405015"],"award-info":[{"award-number":["JCYJ20210324134405015"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,9,3]]},"DOI":"10.1145\/3584371.3612995","type":"proceedings-article","created":{"date-parts":[[2023,10,4]],"date-time":"2023-10-04T18:52:30Z","timestamp":1696445550000},"page":"1-6","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Large-scale Dataset and Effective Model for Variant-Disease Associations Extraction"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9727-0714","authenticated-orcid":false,"given":"Lei","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Computer Science, The University of Hong Kong, Hong Kong, Hong Kong"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8560-3999","authenticated-orcid":false,"given":"Junhao","family":"Su","sequence":"additional","affiliation":[{"name":"Department of Computer Science, The University of Hong Kong, Hong Kong, Hong Kong"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6546-2324","authenticated-orcid":false,"given":"Zhenxian","family":"Zheng","sequence":"additional","affiliation":[{"name":"Department of Computer Science, The University of Hong Kong, Hong Kong, Hong Kong"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4676-8587","authenticated-orcid":false,"given":"Tak-Wah","family":"Lam","sequence":"additional","affiliation":[{"name":"Department of Computer Science, The University of Hong Kong, Hong Kong, Hong Kong"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9711-6533","authenticated-orcid":false,"given":"Ruibang","family":"Luo","sequence":"additional","affiliation":[{"name":"Department of Computer Science, The University of Hong Kong, Hong Kong, Hong Kong"}]}],"member":"320","published-online":{"date-parts":[[2023,10,4]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Rare variant association analysis methods for complex traits. Annual review of genetics 44","author":"Asimit Jennifer","year":"2010","unstructured":"Jennifer Asimit and Eleftheria Zeggini . 2010. Rare variant association analysis methods for complex traits. Annual review of genetics 44 ( 2010 ), 293--308. Jennifer Asimit and Eleftheria Zeggini. 2010. Rare variant association analysis methods for complex traits. Annual review of genetics 44 (2010), 293--308."},{"key":"e_1_3_2_1_2_1","volume-title":"SciBERT: A pretrained language model for scientific text. arXiv preprint arXiv:1903.10676","author":"Beltagy Iz","year":"2019","unstructured":"Iz Beltagy , Kyle Lo , and Arman Cohan . 2019. SciBERT: A pretrained language model for scientific text. arXiv preprint arXiv:1903.10676 ( 2019 ). Iz Beltagy, Kyle Lo, and Arman Cohan. 2019. SciBERT: A pretrained language model for scientific text. arXiv preprint arXiv:1903.10676 (2019)."},{"key":"e_1_3_2_1_3_1","volume-title":"Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research. BMC bioinformatics 16","author":"Bravo \u00c0lex","year":"2015","unstructured":"\u00c0lex Bravo , Janet Pi\u00f1ero , N\u00faria Queralt-Rosinach , Michael Rautschka , and Laura I Furlong . 2015. Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research. BMC bioinformatics 16 ( 2015 ), 1--17. \u00c0lex Bravo, Janet Pi\u00f1ero, N\u00faria Queralt-Rosinach, Michael Rautschka, and Laura I Furlong. 2015. Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research. BMC bioinformatics 16 (2015), 1--17."},{"key":"e_1_3_2_1_4_1","volume-title":"Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin , Ming-Wei Chang , Kenton Lee , and Kristina Toutanova . 2018 . Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018). Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btq667"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3458754"},{"key":"e_1_3_2_1_7_1","volume-title":"Document-Level N-ary Relation Extraction with Multiscale Representation Learning. arXiv preprint arXiv:1904.02347","author":"Jia Robin","year":"2019","unstructured":"Robin Jia , Cliff Wong , and Hoifung Poon . 2019. Document-Level N-ary Relation Extraction with Multiscale Representation Learning. arXiv preprint arXiv:1904.02347 ( 2019 ). Robin Jia, Cliff Wong, and Hoifung Poon. 2019. Document-Level N-ary Relation Extraction with Multiscale Representation Learning. arXiv preprint arXiv:1904.02347 (2019)."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btz682"},{"key":"e_1_3_2_1_9_1","volume-title":"Carolyn J Mattingly, Thomas C Wiegers, and Zhiyong Lu.","author":"Li Jiao","year":"2016","unstructured":"Jiao Li , Yueping Sun , Robin J Johnson , Daniela Sciaky , Chih-Hsuan Wei , Robert Leaman , Allan Peter Davis , Carolyn J Mattingly, Thomas C Wiegers, and Zhiyong Lu. 2016 . BioCreative V CDR task corpus: a resource for chemical disease relation extraction. Database 2016 (2016). Jiao Li, Yueping Sun, Robin J Johnson, Daniela Sciaky, Chih-Hsuan Wei, Robert Leaman, Allan Peter Davis, Carolyn J Mattingly, Thomas C Wiegers, and Zhiyong Lu. 2016. BioCreative V CDR task corpus: a resource for chemical disease relation extraction. Database 2016 (2016)."},{"key":"e_1_3_2_1_10_1","volume-title":"BioRED: a rich biomedical relation extraction dataset. Briefings in Bioinformatics 23, 5","author":"Luo Ling","year":"2022","unstructured":"Ling Luo , Po-Ting Lai , Chih-Hsuan Wei , Cecilia N Arighi , and Zhiyong Lu. 2022. BioRED: a rich biomedical relation extraction dataset. Briefings in Bioinformatics 23, 5 ( 2022 ), bbac282. Ling Luo, Po-Ting Lai, Chih-Hsuan Wei, Cecilia N Arighi, and Zhiyong Lu. 2022. BioRED: a rich biomedical relation extraction dataset. Briefings in Bioinformatics 23, 5 (2022), bbac282."},{"key":"e_1_3_2_1_11_1","volume-title":"TBGA: a large-scale gene-disease association dataset for biomedical relation extraction. BMC bioinformatics 23, 1","author":"Marchesin Stefano","year":"2022","unstructured":"Stefano Marchesin and Gianmaria Silvello . 2022. TBGA: a large-scale gene-disease association dataset for biomedical relation extraction. BMC bioinformatics 23, 1 ( 2022 ), 1--16. Stefano Marchesin and Gianmaria Silvello. 2022. TBGA: a large-scale gene-disease association dataset for biomedical relation extraction. BMC bioinformatics 23, 1 (2022), 1--16."},{"key":"e_1_3_2_1_12_1","volume-title":"DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic acids research","author":"Pi\u00f1ero Janet","year":"2016","unstructured":"Janet Pi\u00f1ero , \u00c0lex Bravo , N\u00faria Queralt-Rosinach , Alba Guti\u00e9rrez-Sacrist\u00e1n , Jordi Deu-Pons , Emilio Centeno , Javier Garc\u00eda-Garc\u00eda , Ferran Sanz , and Laura I Furlong . 2016. DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic acids research ( 2016 ), gkw943. Janet Pi\u00f1ero, \u00c0lex Bravo, N\u00faria Queralt-Rosinach, Alba Guti\u00e9rrez-Sacrist\u00e1n, Jordi Deu-Pons, Emilio Centeno, Javier Garc\u00eda-Garc\u00eda, Ferran Sanz, and Laura I Furlong. 2016. DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic acids research (2016), gkw943."},{"key":"e_1_3_2_1_13_1","volume-title":"DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes. Database 2015","author":"Pi\u00f1ero Janet","year":"2015","unstructured":"Janet Pi\u00f1ero , N\u00faria Queralt-Rosinach , Alex Bravo , Jordi Deu-Pons , Anna BauerMehren , Martin Baron , Ferran Sanz , and Laura I Furlong . 2015. DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes. Database 2015 ( 2015 ). Janet Pi\u00f1ero, N\u00faria Queralt-Rosinach, Alex Bravo, Jordi Deu-Pons, Anna BauerMehren, Martin Baron, Ferran Sanz, and Laura I Furlong. 2015. DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes. Database 2015 (2015)."},{"key":"e_1_3_2_1_14_1","volume-title":"Josep Sa\u00fcch-Pitarch, Francesco Ronzano, Emilio Centeno, Ferran Sanz, and Laura I Furlong.","author":"Pi\u00f1ero Janet","year":"2020","unstructured":"Janet Pi\u00f1ero , Juan Manuel Ram\u00edrez-Anguita , Josep Sa\u00fcch-Pitarch, Francesco Ronzano, Emilio Centeno, Ferran Sanz, and Laura I Furlong. 2020 . The DisGeNET knowledge platform for disease genomics: 2019 update. Nucleic acids research 48, D1 (2020), D845--D855. Janet Pi\u00f1ero, Juan Manuel Ram\u00edrez-Anguita, Josep Sa\u00fcch-Pitarch, Francesco Ronzano, Emilio Centeno, Ferran Sanz, and Laura I Furlong. 2020. The DisGeNET knowledge platform for disease genomics: 2019 update. Nucleic acids research 48, D1 (2020), D845--D855."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"crossref","unstructured":"Richard J Roberts. 2001. PubMed Central: The GenBank of the published literature. 381--382 pages.  Richard J Roberts. 2001. PubMed Central: The GenBank of the published literature. 381--382 pages.","DOI":"10.1073\/pnas.98.2.381"},{"key":"e_1_3_2_1_16_1","volume-title":"RENET2: high-performance full-text gene-disease relation extraction with iterative training data expansion. NAR Genomics and Bioinformatics 3, 3","author":"Su Junhao","year":"2021","unstructured":"Junhao Su , Ye Wu , Hing-Fung Ting , Tak-Wah Lam , and Ruibang Luo . 2021. RENET2: high-performance full-text gene-disease relation extraction with iterative training data expansion. NAR Genomics and Bioinformatics 3, 3 ( 2021 ), lqab062. Junhao Su, Ye Wu, Hing-Fung Ting, Tak-Wah Lam, and Ruibang Luo. 2021. RENET2: high-performance full-text gene-disease relation extraction with iterative training data expansion. NAR Genomics and Bioinformatics 3, 3 (2021), lqab062."},{"key":"e_1_3_2_1_17_1","volume-title":"Document-level relation extraction with adaptive focal loss and knowledge distillation. arXiv preprint arXiv:2203.10900","author":"Tan Qingyu","year":"2022","unstructured":"Qingyu Tan , Ruidan He , Lidong Bing , and Hwee Tou Ng. 2022. Document-level relation extraction with adaptive focal loss and knowledge distillation. arXiv preprint arXiv:2203.10900 ( 2022 ). Qingyu Tan, Ruidan He, Lidong Bing, and Hwee Tou Ng. 2022. Document-level relation extraction with adaptive focal loss and knowledge distillation. arXiv preprint arXiv:2203.10900 (2022)."},{"key":"e_1_3_2_1_18_1","volume-title":"W1","author":"Wei Chih-Hsuan","year":"2013","unstructured":"Chih-Hsuan Wei , Hung-Yu Kao , and Zhiyong Lu. 2013. PubTator: a web-based text mining tool for assisting biocuration. Nucleic acids research 41 , W1 ( 2013 ), W518--W522. Chih-Hsuan Wei, Hung-Yu Kao, and Zhiyong Lu. 2013. PubTator: a web-based text mining tool for assisting biocuration. Nucleic acids research 41, W1 (2013), W518--W522."},{"key":"e_1_3_2_1_19_1","volume-title":"Medical reference services quarterly 39, 4","author":"White Jacob","year":"2020","unstructured":"Jacob White . 2020. PubMed 2.0. Medical reference services quarterly 39, 4 ( 2020 ), 382--387. Jacob White. 2020. PubMed 2.0. Medical reference services quarterly 39, 4 (2020), 382--387."},{"key":"e_1_3_2_1_20_1","volume-title":"Hing-Fung Ting, and Tak-Wah Lam.","author":"Wu Ye","year":"2019","unstructured":"Ye Wu , Ruibang Luo , Henry CM Leung , Hing-Fung Ting, and Tak-Wah Lam. 2019 . Renet : A deep learning approach for extracting gene-disease associations from literature. In RECOMB 2019. Springer , 272--284. Ye Wu, Ruibang Luo, Henry CM Leung, Hing-Fung Ting, and Tak-Wah Lam. 2019. Renet: A deep learning approach for extracting gene-disease associations from literature. In RECOMB 2019. Springer, 272--284."},{"key":"e_1_3_2_1_21_1","volume-title":"Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling. In AAAI","author":"Zhou Wenxuan","year":"2021","unstructured":"Wenxuan Zhou , Kevin Huang , Tengyu Ma , and Jing Huang . 2021 . Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling. In AAAI 2021. Wenxuan Zhou, Kevin Huang, Tengyu Ma, and Jing Huang. 2021. Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling. In AAAI 2021."}],"event":{"name":"BCB '23: 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","sponsor":["SIGBio ACM Special Interest Group on Bioinformatics"],"location":"Houston TX USA","acronym":"BCB '23"},"container-title":["Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3584371.3612995","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3584371.3612995","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:46:26Z","timestamp":1750178786000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3584371.3612995"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,3]]},"references-count":21,"alternative-id":["10.1145\/3584371.3612995","10.1145\/3584371"],"URL":"https:\/\/doi.org\/10.1145\/3584371.3612995","relation":{},"subject":[],"published":{"date-parts":[[2023,9,3]]},"assertion":[{"value":"2023-10-04","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}