{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,1,26]],"date-time":"2023-01-26T05:20:36Z","timestamp":1674710436808},"reference-count":30,"publisher":"Oxford University Press (OUP)","issue":"18","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011,9,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Gene normalization (GN) is the task of normalizing a textual gene mention to a unique gene database ID. Traditional top performing GN systems usually need to consider several constraints to make decisions in the normalization process, including filtering out false positives, or disambiguating an ambiguous gene mention, to improve system performance. However, these constraints are usually executed in several separate stages and cannot use each other's input\/output interactively. In this article, we propose a novel approach that employs a Markov logic network (MLN) to model the constraints used in the GN task. Firstly, we show how various constraints can be formulated and combined in an MLN. Secondly, we are the first to apply the two main concepts of co-reference resolution\u2014discourse salience in centering theory and transitivity\u2014to GN models. Furthermore, to make our results more relevant to developers of information extraction applications, we adopt the instance-based precision\/recall\/F-measure (PRF) in addition to the article-wide PRF to assess system performance.<\/jats:p>\n               <jats:p>Results: Experimental results show that our system outperforms baseline and state-of-the-art systems under two evaluation schemes. Through further analysis, we have found several unexplored challenges in the GN task.<\/jats:p>\n               <jats:p>Contact: \u00a0hongjie@iis.sinica.edu.tw<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btr358","type":"journal-article","created":{"date-parts":[[2011,6,18]],"date-time":"2011-06-18T04:15:07Z","timestamp":1308370507000},"page":"2586-2594","source":"Crossref","is-referenced-by-count":10,"title":["Integration of gene normalization stages and co-reference resolution using a Markov logic network"],"prefix":"10.1093","volume":"27","author":[{"given":"Hong-Jie","family":"Dai","sequence":"first","affiliation":[{"name":"1 Department of Computer Science, National Tsing\u2212Hua University, Hsinchu, 2Intelligent Agent Systems Lab., Institute of Information Science, Academia Sinica, 3Department of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei and 4Department of Computer Science and Engineering, Yuan Ze University, Chung-Li, Taiwan, R.O.C."},{"name":"1 Department of Computer Science, National Tsing\u2212Hua University, Hsinchu, 2Intelligent Agent Systems Lab., Institute of Information Science, Academia Sinica, 3Department of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei and 4Department of Computer Science and Engineering, Yuan Ze University, Chung-Li, Taiwan, R.O.C."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yen\u2212Ching","family":"Chang","sequence":"additional","affiliation":[{"name":"1 Department of Computer Science, National Tsing\u2212Hua University, Hsinchu, 2Intelligent Agent Systems Lab., Institute of Information Science, Academia Sinica, 3Department of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei and 4Department of Computer Science and Engineering, Yuan Ze University, Chung-Li, Taiwan, R.O.C."},{"name":"1 Department of Computer Science, National Tsing\u2212Hua University, Hsinchu, 2Intelligent Agent Systems Lab., Institute of Information Science, Academia Sinica, 3Department of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei and 4Department of Computer Science and Engineering, Yuan Ze University, Chung-Li, Taiwan, R.O.C."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Richard Tzong-Han","family":"Tsai","sequence":"additional","affiliation":[{"name":"1 Department of Computer Science, National Tsing\u2212Hua University, Hsinchu, 2Intelligent Agent Systems Lab., Institute of Information Science, Academia Sinica, 3Department of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei and 4Department of Computer Science and Engineering, Yuan Ze University, Chung-Li, Taiwan, R.O.C."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wen\u2212Lian","family":"Hsu","sequence":"additional","affiliation":[{"name":"1 Department of Computer Science, National Tsing\u2212Hua University, Hsinchu, 2Intelligent Agent Systems Lab., Institute of Information Science, Academia Sinica, 3Department of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei and 4Department of Computer Science and Engineering, Yuan Ze University, Chung-Li, Taiwan, R.O.C."},{"name":"1 Department of Computer Science, National Tsing\u2212Hua University, Hsinchu, 2Intelligent Agent Systems Lab., Institute of Information Science, Academia Sinica, 3Department of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei and 4Department of Computer Science and Engineering, Yuan Ze University, Chung-Li, Taiwan, R.O.C."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2011,6,17]]},"reference":[{"key":"2023012512003318300_B1","first-page":"199","article-title":"A comparative evaluation of sequential feature selection algorithms","volume-title":"Learning from Data: Artificial Intelligence and Statistics V","author":"Aha","year":"1995"},{"key":"2023012512003318300_B2","first-page":"257","article-title":"An integrated approach to concept recognition in biomedical text","author":"Baumgartner","year":"2007","journal-title":"Proceedings of the Second BioCreative Challenge Evaluation Workshop, CNIO (Centro Nacional de Investigaciones Oncologicas)"},{"key":"2023012512003318300_B3","first-page":"951","article-title":"Ultraconservative online algorithms for multiclass problems","volume":"3","author":"Crammer","year":"2003","journal-title":"J. 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