{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,26]],"date-time":"2025-10-26T22:46:54Z","timestamp":1761518814136},"reference-count":18,"publisher":"Oxford University Press (OUP)","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2006,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Contrasts are useful conceptual vehicles for learning processes and exploratory research of the unknown. For example, contrastive information between proteins can reveal what similarities, divergences and relations there are of the two proteins, leading to invaluable insights for better understanding about the proteins. Such contrastive information are found to be reported in the biomedical literature. However, there have been no reported attempts in current biomedical text mining work that systematically extract and present such useful contrastive information from the literature for exploitation.<\/jats:p>\n               <jats:p>Results: Our BioContrasts system extracts protein\u2013protein contrastive information from MEDLINE abstracts and presents the information to biologists in a web-application for exploitation. Contrastive information are identified in the text abstracts with contrastive negation patterns such as \u2018A but not B\u2019. A total of 799\u2009169 pairs of contrastive expressions were successfully extracted from 2.5 million MEDLINE abstracts. Using grounding of contrastive protein names to Swiss-Prot entries, we were able to produce 41\u2009471 pieces of contrasts between Swiss-Prot protein entries. These contrastive pieces of information are then presented via a user-friendly interactive web portal that can be exploited for applications such as the refinement of biological pathways.<\/jats:p>\n               <jats:p>Availability: BioContrasts can be accessed at . It is also mirrored at<\/jats:p>\n               <jats:p>Supplementary information: Supplementary materials are available at Bioinformatics online.<\/jats:p>\n               <jats:p>Contact: \u00a0skng@i2r.a-star.edu.sg; park@cs.kaist.ac.kr<\/jats:p>","DOI":"10.1093\/bioinformatics\/btk016","type":"journal-article","created":{"date-parts":[[2005,12,21]],"date-time":"2005-12-21T02:18:10Z","timestamp":1135131490000},"page":"597-605","source":"Crossref","is-referenced-by-count":19,"title":["BioContrasts: extracting and exploiting protein\u2013protein contrastive relations from biomedical literature"],"prefix":"10.1093","volume":"22","author":[{"given":"Jung-jae","family":"Kim","sequence":"first","affiliation":[{"name":"Computer Science Division & AITrc, Korea Advanced Institute of Science and Technology 1 \u00a0 1 \u00a0 \u00a0 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701 South Korea"}]},{"given":"Zhuo","family":"Zhang","sequence":"additional","affiliation":[{"name":"Knowledge Discovery Department, Institute for Infocomm Research 2 \u00a0 2 \u00a0 \u00a0 21 Heng Mui Keng Terrace, Singapore 119613, Singapore"}]},{"given":"Jong C.","family":"Park","sequence":"additional","affiliation":[{"name":"Computer Science Division & AITrc, Korea Advanced Institute of Science and Technology 1 \u00a0 1 \u00a0 \u00a0 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701 South Korea"}]},{"given":"See-Kiong","family":"Ng","sequence":"additional","affiliation":[{"name":"Knowledge Discovery Department, Institute for Infocomm Research 2 \u00a0 2 \u00a0 \u00a0 21 Heng Mui Keng Terrace, Singapore 119613, Singapore"}]}],"member":"286","published-online":{"date-parts":[[2005,12,20]]},"reference":[{"key":"2023012408522950600_b1","doi-asserted-by":"crossref","first-page":"D418","DOI":"10.1093\/nar\/gki051","article-title":"The Biomolecular Interaction Network Database and related tools 2005 update","volume":"33","author":"Alfarano","year":"2005","journal-title":"Nucleic Acids Res."},{"key":"2023012408522950600_b2","doi-asserted-by":"crossref","first-page":"D154","DOI":"10.1093\/nar\/gki070","article-title":"The Universal Protein Resource (UniProt)","volume":"33","author":"Bairoch","year":"2005","journal-title":"Nucleic Acids Res."},{"key":"2023012408522950600_b3","first-page":"543","article-title":"Transformation-based error-driven learning and natural language processing: a case study in part-of-speech tagging","volume":"21","author":"Brill","year":"1995","journal-title":"Comput. 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