{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T16:46:05Z","timestamp":1764002765263,"version":"3.41.2"},"reference-count":31,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T00:00:00Z","timestamp":1733356800000},"content-version":"vor","delay-in-days":7,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["T2122015"],"award-info":[{"award-number":["T2122015"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,11,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Neuroscientists have long endeavored to map brain connectivity, yet the intricate nature of brain networks often leads them to concentrate on specific regions, hindering efforts to unveil a comprehensive connectivity map. Recent advancements in imaging and text mining techniques have enabled the accumulation of a vast body of literature containing valuable insights into brain connectivity, facilitating the extraction of whole-brain connectivity relations from this corpus. However, the diverse representations of brain region names and connectivity relations pose a challenge for conventional machine learning methods and dictionary-based approaches in identifying all instances accurately.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We propose BioSEPBERT, a biomedical pre-trained model based on start-end position pointers and BERT. In addition, our model integrates specialized identifiers with enhanced self-attention capabilities for preceding and succeeding brain regions, thereby improving the performance of named entity recognition and relation extraction in neuroscience. Our approach achieves optimal F1 scores of 85.0%, 86.6%, and 86.5% for named entity recognition, connectivity relation extraction, and directional relation extraction, respectively, surpassing state-of-the-art models by 2.6%, 1.1%, and 1.1%. Furthermore, we leverage BioSEPBERT to extract 22.6 million standardized brain regions and 165\u00a0072 directional relations from a corpus comprising 1.3 million abstracts and 193\u00a0100 full-text articles. The results demonstrate that our model facilitates researchers to rapidly acquire knowledge regarding neural circuits across various brain regions, thereby enhancing comprehension of brain connectivity in specific regions.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>Data and source code are available at: http:\/\/atlas.brainsmatics.org\/res\/BioSEPBERT and https:\/\/github.com\/Brainsmatics\/BioSEPBERT.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btae648","type":"journal-article","created":{"date-parts":[[2024,12,10]],"date-time":"2024-12-10T20:34:09Z","timestamp":1733862849000},"source":"Crossref","is-referenced-by-count":1,"title":["Knowledge mining of brain connectivity in massive literature based on transfer learning"],"prefix":"10.1093","volume":"40","author":[{"given":"Xiaokang","family":"Chai","sequence":"first","affiliation":[{"name":"Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology , Wuhan 430074,","place":["China"]}]},{"given":"Sile","family":"An","sequence":"additional","affiliation":[{"name":"Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology , Wuhan 430074,","place":["China"]}]},{"given":"Simeng","family":"Chen","sequence":"additional","affiliation":[{"name":"Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology , Wuhan 430074,","place":["China"]}]},{"given":"Wenwei","family":"Li","sequence":"additional","affiliation":[{"name":"Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology , Wuhan 430074,","place":["China"]}]},{"given":"Zhao","family":"Feng","sequence":"additional","affiliation":[{"name":"Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University , Haikou 570228,","place":["China"]}]},{"given":"Xiangning","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University , Haikou 570228,","place":["China"]},{"name":"HUST-Suzhou Institute for Brainsmatics, JITRI , Suzhou 215123,","place":["China"]}]},{"given":"Hui","family":"Gong","sequence":"additional","affiliation":[{"name":"Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology , Wuhan 430074,","place":["China"]},{"name":"HUST-Suzhou Institute for Brainsmatics, JITRI , Suzhou 215123,","place":["China"]}]},{"given":"Qingming","family":"Luo","sequence":"additional","affiliation":[{"name":"Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University , Haikou 570228,","place":["China"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5877-4813","authenticated-orcid":false,"given":"Anan","family":"Li","sequence":"additional","affiliation":[{"name":"Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology , Wuhan 430074,","place":["China"]},{"name":"Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University , Haikou 570228,","place":["China"]},{"name":"HUST-Suzhou Institute for Brainsmatics, JITRI , Suzhou 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