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A machine learning approach for the curation of biomedical literature

S. Sathiya Keerthi, Jonathan Y. K. Lim, Han Tong Loh, Chong Jin Ong, Keng Boon Siah, David B. L. Lim, Wei Chu, Min Shi, David S. Edwin, Rakesh Menon, Lixiang Shen
2002 SIGKDD Explorations  
In this paper, we present an automated text classification system for the classification of biomedical papers.  ...  This classification is based on whether there is experimental evidence for the expression of molecular gene products for specified genes within a given paper.  ...  Kolatkar from the Genome Institute of Singapore for their contributions to this work.  ... 
doi:10.1145/772862.772875 fatcat:vhezxpubqvcupdg5qcbnuclfca

A Machine Learning Approach for the Curation of Biomedical Literature [chapter]

Min Shi, David S. Edwin, Rakesh Menon, Lixiang Shen, Jonathan Y. K. Lim, Han Tong Loh, S. Sathiya Keerthi, Chong Jin Ong
2003 Lecture Notes in Computer Science  
In this paper, we present an automated text classification system for the classification of biomedical papers.  ...  This classification is based on whether there is experimental evidence for the expression of molecular gene products for specified genes within a given paper.  ...  Kolatkar from the Genome Institute of Singapore for their contributions to this work.  ... 
doi:10.1007/3-540-36618-0_47 fatcat:lyluktk6ifbmxdrz57fimuh2oq

The TREC 2004 genomics track categorization task: classifying full text biomedical documents

Aaron M Cohen, William R Hersh
2006 Journal of Biomedical Discovery and Collaboration  
that make automated classification feasible and useful for biomedical document curation.  ...  The annotation subtask had a mean F-measure of 0.3824, with a top score of 0.5611. The mean F-measure for the annotation plus evidence codes subtask was 0.3676, with a top score of 0.4224.  ...  The TREC 2004 Genomics Track would like to acknowledge the assistance of Judith Blake and her staff at the Mouse Genome Institute for their support in creating the tasks and preparing the data for this  ... 
doi:10.1186/1747-5333-1-4 pmid:16722582 pmcid:PMC1440303 fatcat:4s72k77fl5cidi4qdoomcoyygi

Evaluation of BioCreAtIvE assessment of task 2

Christian Blaschke, Eduardo Leon, Martin Krallinger, Alfonso Valencia
2005 BMC Bioinformatics  
to biomedical literature.  ...  Due to the growing accumulation of functional descriptions in biomedical literature the need for text mining tools to facilitate the extraction of such annotations is urgent.  ...  In the domain of biomedical literature, the knowledge discovery and data mining (KDD) challenge cup [7] evaluated how text mining tools could aid in the process of database curation, in this case of  ... 
doi:10.1186/1471-2105-6-s1-s16 pmid:15960828 pmcid:PMC1869008 fatcat:2pbvytvsqjcdbivxu7yia6oyue

Mining the biomedical literature using semantic analysis and natural language processing techniques

Ronen Feldman, Yizhar Regev, Eyal Hurvitz, Michal Finkelstein-Landau
2003 BIOSILICO  
The LitMiner™ system, developed specifically for this purpose; is described in relation to the Knowledge Discovery and Data Mining Cup 2002, which serves as a formal evaluation of the system. www.drugdiscoverytoday.com  ...  Here, we focus on text mining as applied to the biomedical literature.  ...  Acknowledgements The KDD Cup work was performed in cooperation with a team from Celera Genomics (http://www.celera.com), headed by Hagit Shatkay, and with the help of Meir Shamay of the Weizmann Institute  ... 
doi:10.1016/s1478-5382(03)02330-8 fatcat:flak6ux5crcjnj3l6is7w62kki

Evaluation of text data mining for database curation: lessons learned from the KDD Challenge Cup

A. S. Yeh, L. Hirschman, A. A. Morgan
2003 Bioinformatics  
Results: We report on a Challenge Evaluation task that we created for the Knowledge Discovery and Data Mining (KDD) Challenge Cup.  ...  Motivation: The biological literature is a major repository of knowledge. Many biological databases draw much of their content from a careful curation of this literature.  ...  In addition, many people at FlyBase have contributed to the KDD Cup task, especially William Gelbart, Beverly Matthews, Leyla Bayraktaroglu, David Emmert and Don Gilbert.  ... 
doi:10.1093/bioinformatics/btg1046 pmid:12855478 fatcat:bjfhisawmzcwnp2hwb3e23coiy

Evaluation of text data mining for database curation: lessons learned from the KDD Challenge Cup [article]

Alexander S. Yeh, Lynette Hirschman, Alexander A. Morgan
2003 arXiv   pre-print
RESULTS: We report on a Challenge Evaluation task that we created for the Knowledge Discovery and Data Mining (KDD) Challenge Cup.  ...  MOTIVATION: The biological literature is a major repository of knowledge. Many biological databases draw much of their content from a careful curation of this literature.  ...  In addition, many people at FlyBase have contributed to the KDD Cup task, especially William Gelbart, Beverly Matthews, Leyla Bayraktaroglu, David Emmert and Don Gilbert.  ... 
arXiv:cs/0308032v1 fatcat:u5qu25hggbctrk6if4vgdgyhbe

Mining the Biomedical Literature in the Genomic Era: An Overview

Hagit Shatkay, Ronen Feldman
2003 Journal of Computational Biology  
most relevant and useful for specific analysis tasks.  ...  During the last few years, there was a surge of interest in using the biomedical literature, (e.  ...  ACKNOWLEDGMENTS We thank the ClearForest-Celera team for their work towards the KDD-cup 2002. HS thanks Stephen Edwards, Mark Boguski, and John Wilbur for their collaboration on the GenTheme project.  ... 
doi:10.1089/106652703322756104 pmid:14980013 fatcat:vbwcpl66ujhqdgq4wdjtllbg5e

Gene name extraction using FlyBase resources

Alex Morgan, Lynette Hirschman, Alexander Yeh, Marc Colosimo
2003 Proceedings of the ACL 2003 workshop on Natural language processing in biomedicine -  
tor), a model organism for genetics research: http://www.flybase.org. 2 Of course most of these early references in FlyBase are not in electronic form.  ...  The FlyBase database has been in existence since 1993. 3  ...  r FlyBase: Organization and Resources We focused on FlyBase because we had access to FlyBase resources from our work in the creation of the KDD 2002 Cup Challenge Task 1 [Yeh03].  ... 
doi:10.3115/1118958.1118959 dblp:conf/bionlp/MorganHYC03 fatcat:y5br6vlv5rfdtll2byszlnipd4

Tough Mining

Steven Dickman
2003 PLoS Biology  
This marking-up process, however it is done, is crucial for machine-learning tasks. Getting these data is both hard and expensive, says Hirschman.  ...  Eighteen participants took a shot at the KDD Cup and their results speak of the infant state of the field.  ... 
doi:10.1371/journal.pbio.0000048 pmid:14624250 pmcid:PMC261887 fatcat:qzd5wnojwjd5zdojprq6rqk2sy

Gene name identification and normalization using a model organism database

Alexander A. Morgan, Lynette Hirschman, Marc Colosimo, Alexander S. Yeh, Jeff B. Colombe
2004 Journal of Biomedical Informatics  
We report here on a series of experiments related to the application of natural language processing to aid in the curation process for FlyBase.  ...  For gene mention tagging, we adopted a statistical approach.  ...  A variety of information retrieval and text mining techniques can be used for this step; the KDD Challenge Cup 2002 [15] focused on this task for Fly-Base curation of gene expression data.  ... 
doi:10.1016/j.jbi.2004.08.010 pmid:15542014 fatcat:f2r63l3ecfhrtjxm2eo2omfxvq

Overview of the BioCreative III Workshop

Cecilia N Arighi, Zhiyong Lu, Martin Krallinger, Kevin B Cohen, W Wilbur, Alfonso Valencia, Lynette Hirschman, Cathy H Wu
2011 BMC Bioinformatics  
Each of these workshops involved humanly annotated test data for several basic tasks in text mining applied to the biomedical literature.  ...  For BioCreative III, a user advisory group (UAG) was assembled and played an important role 1) in producing some of the gold standard annotations for the GN task, 2) in critiquing IAT systems, and 3) in  ...  Author details 1 Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE, USA. 2 National Center for Biotechnology Information, National Library of Medicine, Bethesda,  ... 
doi:10.1186/1471-2105-12-s8-s1 pmid:22151647 pmcid:PMC3269932 fatcat:lp7c4vnknraqrkganmnqt4hfse

Evaluation of text-mining systems for biology: overview of the Second BioCreative community challenge

Martin Krallinger, Alexander Morgan, Larry Smith, Florian Leitner, Lorraine Tanabe, John Wilbur, Lynette Hirschman, Alfonso Valencia
2008 Genome Biology  
These tasks included the recognition of gene mentions in abstracts (gene mention task); the extraction of a list of unique identifiers for human genes mentioned in abstracts (gene normalization task);  ...  The BioCreative challenge (Critical Assessment of Information Extraction in Biology) consists of a collaborative initiative to provide a common evaluation framework for monitoring and assessing the state-of-the-art  ...  We also acknowledge all the publishers for allowing the use of full-text articles for the purpose of the Bio-Creative PPI task, especially Nature Publishing Group (NPG), Elsevier, and Cell Press.  ... 
doi:10.1186/gb-2008-9-s2-s1 pmid:18834487 pmcid:PMC2559980 fatcat:oebtobhdtbfexgyrmymmy7o6vi

Overview of BioCreAtIvE: critical assessment of information extraction for biology

Lynette Hirschman, Alexander Yeh, Christian Blaschke, Alfonso Valencia
2005 BMC Bioinformatics  
The goal of the first BioCreAtIvE challenge (Critical Assessment of Information Extraction in Biology) was to provide a set of common evaluation tasks to assess the state of the art for text mining applied  ...  The results for the advanced task (functional annotation from free text) were significantly lower, demonstrating the current limitations of text-mining approaches where knowledge extrapolation and interpretation  ...  Acknowledgements The work of AV and CB was funded by the European Commission as part of the E-BioSci and ORIEL projects, contract numbers QLRI-CT  ... 
doi:10.1186/1471-2105-6-s1-s1 pmid:15960821 pmcid:PMC1869002 fatcat:kktugbhkrzgwvnnwuo7jxszkaq

Biomedical Language Processing: What's Beyond PubMed?

Lawrence Hunter, K. Bretonnel Cohen
2006 Molecular Cell  
However, PubMed is only the beginning of a revolution in how scientists use the biomedical literature.  ...  The biomedical literature is growing at a double-exponential pace; over the last 20 years, the total size of MEDLINE (the database searched by PubMed) has grown at a ~4.2% compounded annual growth rate  ...  Acknowledgements The authors thank Hao Chen, Hans-Michael Müller, and Parantu Shah for usage data; Lynne Fox for information on PubMed; MITRE's Biomedical Information Processing group for data on Drosophila  ... 
doi:10.1016/j.molcel.2006.02.012 pmid:16507357 pmcid:PMC1702322 fatcat:yqvaab5kvjcl5norxcrh7fbvdm
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