Difference between revisions of "BioNLP 2023"

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==BIONLP 2015 Workshop Schedule==
 
==BIONLP 2015 Workshop Schedule==
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<table cellspacing="0" cellpadding="5" border="0">
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<tr><td colspan=2><b>Thursday, July 30</b></td></tr>
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<tr><td style="width:10%; vertical-align:top">8:00&#8211;8:20</td><td valign=top><b> Opening remarks</b></td></tr>
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<tr><td valign=top>&nbsp;</td><td valign=top><b>Session 1: Reading biomedical literature</b></td></tr>
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<tr><td valign=top>8:20&#8211;8:40</td><td>Complex Event Extraction using DRUM<br><em>James Allen<sup>1</sup>,&nbsp;Will de Beaumont<sup>2</sup>,&nbsp;Lucian Galescu<sup>2</sup>,&nbsp;Choh Man Teng<sup>2</sup></em><br><sup>1</sup>Institute for Human and Machine Cognition and University of Rochester, <sup>2</sup>Institute for Human and Machine Cognition</td></tr>
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<tr><td valign=top>8:40&#8211;9:00</td><td>Making the most of limited training data using distant supervision<br><em>Roland Roller and Mark Stevenson</em><br>University of Sheffield</td></tr>
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<tr><td valign=top>9:00&#8211;9:20</td><td>An extended dependency graph for relation extraction in biomedical texts<br><em>Yifan Peng<sup>1</sup>,&nbsp;Samir Gupta<sup>2</sup>,&nbsp;Cathy Wu<sup>2</sup>,&nbsp;Vijay Shanker<sup>2</sup></em><br><sup>1</sup>Computer and Information Sciences,  University of Delaware,&nbsp;<sup>2</sup>University of Delaware</td></tr>
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<tr><td valign=top>9:20&#8211;9:40</td><td>Event Extraction in pieces:Tackling the partial event identification problem on unseen corpora<br<em>Chrysoula Zerva and Sophia Ananiadou</em><br>University of Manchester</td></tr>
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<tr><td valign=top>9:40&#8211;10:00</td><td>Extracting Biological Pathway Models From NLP Event Representations<br><em>Michael Spranger<sup>1</sup>,&nbsp;Sucheendra Palaniappan<sup>2</sup>,&nbsp;Samik Ghosh<sup>3</sup></em><br><sup>1</sup>Sony Computer Science Laboratories Inc., <sup>2</sup>INRIA, Campus de Beaulieu, Rennes, France, <sup>3</sup>The Systems Biology Institute, Minato-ku, Tokyo, Japan</td></tr>
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<tr><td valign=top>10:00&#8211;10:20</td><td>Extracting Disease-Symptom Relationships by Learning Syntactic Patterns from Dependency Graphs<br><em>Mohsen Hassan<sup>1</sup>,&nbsp;Olfa Makkaoui<sup>2</sup>,&nbsp;Adrien Coulet<sup>1</sup>,&nbsp;Yannick Toussain<sup>1</sup></em><br><sup>1</sup>LORIA (CNRS, Inria NGE, Universit&eacute;  de Lorraine), <sup>2</sup>LORIA (Inria NGE)</td></tr>
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<tr><td valign=top>10:30&#8211;11:00</td><td valign=top><b>Coffee Break</b></td></tr>
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<tr><td valign=top>11:00&#8211;11:45</td><td valign=top><b><font face="verdana" color="#000080"> Keynote: "Machine Reading: Attempting to model and understand biological processes" - Christopher Manning</font></b></td></tr>
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<tr><td valign=top>11:45&#8211;12:30</td><td valign=top><b><font face="verdana" color="#000080"> Keynote: “The DARPA Big Mechanism Program” - Kevin Knight</font></b></td></tr>
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<tr><td valign=top>12:30&#8211;14:00</td><td valign=top><b>Lunch</b></td></tr>
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<tr><td valign=top>14:00&#8211;15:00</td><td valign=top><b>Poster session</b></td></tr>
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<tr><td valign=top>15:00&#8211;15:30</td><td valign=top><b><font face="verdana" color="#000080"> Invited Talk: “Overview of BioCreative V Challenge Tasks” - Zhiyong Lu</font></b></td></tr>
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<tr><td valign=top>15:30&#8211;16:00</td><td valign=top><b>Coffee Break</b></td></tr>
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<tr><td valign=top>&nbsp;</td><td valign=top><b>Session 2: Clinical text processing</b></td></tr>
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<tr><td valign=top>16:00&#8211;16:20</td><td>Stacked Generalization for Medical Concept Extraction from Clinical Notes<br><em>Youngjun Kim and Ellen Riloff</em><br>University of Utah</td></tr>
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<tr><td valign=top>16:20&#8211;16:40</td><td>Shallow Training is cheap but is it good enough? Experiments with Medical Fact Coding<br><em>Ramesh Nallapati and Radu Florian</em><br>IBM T. J. Watson Research Center</td></tr>
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<tr><td valign=top>16:40&#8211;17:00</td><td>Extracting Time Expressions from Clinical Text<br><em>Timothy Miller<sup>1</sup>,&nbsp;Steven Bethard<sup>2</sup>,&nbsp;Dmitriy Dligach<sup>1</sup>,&nbsp;Chen Lin<sup>3</sup>,&nbsp;Guergana Savova<sup>4</sup></em><br><sup>1</sup>Boston Children's Hospital and Harvard Medical School, <sup>2</sup>University of Alabama at Birmingham, <sup>3</sup>Boston Children's Hospital, <sup>4</sup>Harvard</td></tr>
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<tr><td valign=top>17:00&#8211;17:20</td><td>Exploiting Task-Oriented Resources to Learn Word Embeddings for Clinical Abbreviation Expansion<br><em>Yue Liu<sup>1</sup>,&nbsp;Tao Ge<sup>2</sup>,&nbsp;Kusum Mathews<sup>3</sup>,&nbsp;Heng Ji<sup>1</sup>,&nbsp;Deborah McGuinness<sup>1</sup></em><br><sup>1</sup>Rensselaer Polytechnic Institute, <sup>2</sup>Key Laboratory of Computational Linguistics, Peking University, <sup>3</sup>Departments of Medicine and Emergency Medicine, Icahn School of Medicine at Mount Sinai</td></tr>
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<tr><td valign=top>17:20&#8211;17:40</td><td>Semantic Type Classification of Common Words in Biomedical Noun Phrases<br><em>Amy Siu and Gerhard Weikum</em><br>Max Planck Institute for Informatics</td></tr>
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<tr><td valign=top>17:40&#8211;18:00</td><td>CoMAGD: Annotation of Gene-Depression Relations<br><em>Rize Jin<sup>1</sup>,&nbsp;Jinseon You<sup>1</sup>,&nbsp;Jin-Woo Chung<sup>2</sup>,&nbsp;Hee-Jin Lee<sup>1</sup>,&nbsp;Maria Wolters<sup>3</sup>,&nbsp;Jong Park<sup>2</sup></em><br><sup>1</sup>Korea Advanced Institute of Science and Technology, <sup>2</sup>KAIST, <sup>3</sup>The University of Edinburgh</td></tr>
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<tr><td valign=top>18:00</td><td valign=top><b>Closing remarks</b></td></tr>
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<tr><td valign=top>&nbsp;</td><td valign=top><b>Posters</b></td></tr>
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<tr><td valign=top>&nbsp;</td><td valign=top>Lexical Characteristics Analysis of Chinese Clinical Documents<br><em>Meizhi Ju<sup>1</sup>,&nbsp;Haomin Li<sup>2</sup>,&nbsp;Huilong Duan<sup>1</sup></em><br><sup>1</sup>College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China., <sup>2</sup>The Children’s Hospital of Zhejiang University, Hangzhou, China;The Institute of Translational Medicine, Zhejiang University, Hangzhou, China.</td></tr>
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<tr><td valign=top>&nbsp;</td><td valign=top>Using word embedding for bio-event extraction<br><em>Chen Li<sup>1</sup>,&nbsp;Runqing Song<sup>2</sup>,&nbsp;Maria Liakata<sup>3</sup>,&nbsp;Andreas Vlachos<sup>4</sup>,&nbsp;Stephanie Seneff<sup>1</sup>,&nbsp;Xiangrong Zhang<sup>2</sup></em><br><sup>1</sup>Massachusetts Institute of Technology, <sup>2</sup>Xidian University, <sup>3</sup>University of Warwick, <sup>4</sup>University College London</td></tr>
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<tr><td valign=top>&nbsp;</td><td valign=top>Measuring the readability of medical research journal abstracts<br><em>Samuel J. Severance<sup>1</sup> and K. Bretonnel Cohen<sup>2</sup></em><br><sup>1</sup>School of Education, Institute of Cognitive Science, University of Colorado, <sup>2</sup>U. Colorado School of Medicine</td></tr>
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<tr><td valign=top>&nbsp;</td><td valign=top>Translating Electronic Health Record Notes from English to Spanish: A Preliminary Study<br><em>Weisong Liu<sup>1</sup> and Shu Cai<sup>2</sup></em><br><sup>1</sup>UMass Medical School, <sup>2</sup>Information Sciences Institute</td></tr>
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<tr><td valign=top>&nbsp;</td><td valign=top>Automatic Detection of Answers to Research Questions from Medline Abstracts<br><em>Abdulaziz Alamri<sup>1</sup> and Mark Stevenson<sup>2</sup></em><br><sup>1</sup>PhD Student, The university of Sheffield, <sup>2</sup>University of Sheffield</td></tr>
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<tr><td valign=top>&nbsp;</td><td valign=top>A preliminary study on automatic identification of patient smoking status in unstructured electronic health records<br><em>Jitendra Jonnagaddala<sup>1</sup>,&nbsp;Hong-Jie Dai<sup>2</sup>,&nbsp;Pradeep Ray<sup>1</sup>,&nbsp;Siaw-Teng Liaw<sup>1</sup></em><br><sup>1</sup>UNSW Australia, <sup>2</sup>Taipei Medical University</td></tr>
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<tr><td valign=top>&nbsp;</td><td valign=top>Restoring the intended structure of Hungarian ophthalmology documents<br><em>Borbala Siklosi<sup>1</sup> and Attila Novak<sup>2</sup></em><br><sup>1</sup>Pazmany Peter Catholic University, <sup>2</sup>MTA-PPKE Hungarian Language Technology Research Group, Faculty of Information Technology and Bionics, Pazmany Peter Catholic University, Budapest</td></tr>
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<tr><td valign=top>&nbsp;</td><td valign=top>Evaluating distributed word representations for capturing semantics of biomedical concepts<br><em>MUNEEB TH<sup>1</sup>,&nbsp;Sunil Sahu<sup>2</sup>,&nbsp;Ashish Anand<sup>2</sup></em><br><sup>1</sup>IIT GUWAHATI, <sup>2</sup>Indian Institute of Technology Guwahati</td></tr>
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<tr><td valign=top>&nbsp;</td><td valign=top>Investigating Public Health Surveillance using Twitter<br><em>Antonio Jimeno Yepes<sup>1</sup>,&nbsp;Andrew MacKinlay<sup>1</sup>,&nbsp;Bo Han<sup>2</sup></em><br><sup>1</sup>IBM, <sup>2</sup>IBM Research</td></tr>
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<tr><td valign=top>&nbsp;</td><td valign=top>Clinical Abbreviation Disambiguation Using Neural Word Embeddings<br><em>Yonghui Wu<sup>1</sup>,&nbsp;Jun Xu<sup>2</sup>,&nbsp;Yaoyun Zhang<sup>3</sup>,&nbsp;Hua Xu<sup>1</sup></em><br><sup>1</sup>The University of Texas Health Science Center at Houston, <sup>2</sup>School of Biomedical Informatics, The University of Texas Health Science Center at Houston, <sup>3</sup>University of Texas School of Biomedical Informatics at Houston</td></tr>
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<tr><td valign=top>&nbsp;</td><td valign=top>Representing Clinical Diagnostic Criteria in Quality Data Model Using Natural Language Processing<br><em>Na Hong<sup>1</sup>,&nbsp;Dingcheng Li<sup>1</sup>,&nbsp;Yue Yu<sup>1</sup>,&nbsp;Hongfang Liu<sup>1</sup>,&nbsp;Christopher G. Chute<sup>2</sup>,&nbsp;Guoqian Jiang<sup>1</sup></em><br><sup>1</sup>Mayo Clinic, <sup>2</sup>Johns Hopkins University</td></tr>
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</table>
  
<font face="verdana" color="#000080"> Keynote by Kevin Knight: The DARPA Big Mechanism Program </font>
 
 
DARPA's Big Mechanism Program aims to develop automatic machine-reading technology to distill grounded, causal mechanisms from technical literature, and to assemble those mechanisms into a large, operational model.  The first Big Mechanism domain is cancer biology.  This talk will describe the goals of the program and the techniques being developed.
 
  
 
==BIONLP 2015 Call for Papers==
 
==BIONLP 2015 Call for Papers==

Revision as of 10:04, 9 July 2015

SIGBIOMED

BIONLP 2015 Workshop Schedule

Thursday, July 30
8:00–8:20 Opening remarks
 Session 1: Reading biomedical literature
8:20–8:40Complex Event Extraction using DRUM
James Allen1, Will de Beaumont2, Lucian Galescu2, Choh Man Teng2
1Institute for Human and Machine Cognition and University of Rochester, 2Institute for Human and Machine Cognition
8:40–9:00Making the most of limited training data using distant supervision
Roland Roller and Mark Stevenson
University of Sheffield
9:00–9:20An extended dependency graph for relation extraction in biomedical texts
Yifan Peng1, Samir Gupta2, Cathy Wu2, Vijay Shanker2
1Computer and Information Sciences, University of Delaware, 2University of Delaware
9:20–9:40Event Extraction in pieces:Tackling the partial event identification problem on unseen corpora<brChrysoula Zerva and Sophia Ananiadou
University of Manchester
9:40–10:00Extracting Biological Pathway Models From NLP Event Representations
Michael Spranger1, Sucheendra Palaniappan2, Samik Ghosh3
1Sony Computer Science Laboratories Inc., 2INRIA, Campus de Beaulieu, Rennes, France, 3The Systems Biology Institute, Minato-ku, Tokyo, Japan
10:00–10:20Extracting Disease-Symptom Relationships by Learning Syntactic Patterns from Dependency Graphs
Mohsen Hassan1, Olfa Makkaoui2, Adrien Coulet1, Yannick Toussain1
1LORIA (CNRS, Inria NGE, Université de Lorraine), 2LORIA (Inria NGE)
10:30–11:00Coffee Break
11:00–11:45 Keynote: "Machine Reading: Attempting to model and understand biological processes" - Christopher Manning
11:45–12:30 Keynote: “The DARPA Big Mechanism Program” - Kevin Knight
12:30–14:00Lunch
14:00–15:00Poster session
15:00–15:30 Invited Talk: “Overview of BioCreative V Challenge Tasks” - Zhiyong Lu
15:30–16:00Coffee Break
 Session 2: Clinical text processing
16:00–16:20Stacked Generalization for Medical Concept Extraction from Clinical Notes
Youngjun Kim and Ellen Riloff
University of Utah
16:20–16:40Shallow Training is cheap but is it good enough? Experiments with Medical Fact Coding
Ramesh Nallapati and Radu Florian
IBM T. J. Watson Research Center
16:40–17:00Extracting Time Expressions from Clinical Text
Timothy Miller1, Steven Bethard2, Dmitriy Dligach1, Chen Lin3, Guergana Savova4
1Boston Children's Hospital and Harvard Medical School, 2University of Alabama at Birmingham, 3Boston Children's Hospital, 4Harvard
17:00–17:20Exploiting Task-Oriented Resources to Learn Word Embeddings for Clinical Abbreviation Expansion
Yue Liu1, Tao Ge2, Kusum Mathews3, Heng Ji1, Deborah McGuinness1
1Rensselaer Polytechnic Institute, 2Key Laboratory of Computational Linguistics, Peking University, 3Departments of Medicine and Emergency Medicine, Icahn School of Medicine at Mount Sinai
17:20–17:40Semantic Type Classification of Common Words in Biomedical Noun Phrases
Amy Siu and Gerhard Weikum
Max Planck Institute for Informatics
17:40–18:00CoMAGD: Annotation of Gene-Depression Relations
Rize Jin1, Jinseon You1, Jin-Woo Chung2, Hee-Jin Lee1, Maria Wolters3, Jong Park2
1Korea Advanced Institute of Science and Technology, 2KAIST, 3The University of Edinburgh
18:00Closing remarks
 Posters
 Lexical Characteristics Analysis of Chinese Clinical Documents
Meizhi Ju1, Haomin Li2, Huilong Duan1
1College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China., 2The Children’s Hospital of Zhejiang University, Hangzhou, China;The Institute of Translational Medicine, Zhejiang University, Hangzhou, China.
 Using word embedding for bio-event extraction
Chen Li1, Runqing Song2, Maria Liakata3, Andreas Vlachos4, Stephanie Seneff1, Xiangrong Zhang2
1Massachusetts Institute of Technology, 2Xidian University, 3University of Warwick, 4University College London
 Measuring the readability of medical research journal abstracts
Samuel J. Severance1 and K. Bretonnel Cohen2
1School of Education, Institute of Cognitive Science, University of Colorado, 2U. Colorado School of Medicine
 Translating Electronic Health Record Notes from English to Spanish: A Preliminary Study
Weisong Liu1 and Shu Cai2
1UMass Medical School, 2Information Sciences Institute
 Automatic Detection of Answers to Research Questions from Medline Abstracts
Abdulaziz Alamri1 and Mark Stevenson2
1PhD Student, The university of Sheffield, 2University of Sheffield
 A preliminary study on automatic identification of patient smoking status in unstructured electronic health records
Jitendra Jonnagaddala1, Hong-Jie Dai2, Pradeep Ray1, Siaw-Teng Liaw1
1UNSW Australia, 2Taipei Medical University
 Restoring the intended structure of Hungarian ophthalmology documents
Borbala Siklosi1 and Attila Novak2
1Pazmany Peter Catholic University, 2MTA-PPKE Hungarian Language Technology Research Group, Faculty of Information Technology and Bionics, Pazmany Peter Catholic University, Budapest
 Evaluating distributed word representations for capturing semantics of biomedical concepts
MUNEEB TH1, Sunil Sahu2, Ashish Anand2
1IIT GUWAHATI, 2Indian Institute of Technology Guwahati
 Investigating Public Health Surveillance using Twitter
Antonio Jimeno Yepes1, Andrew MacKinlay1, Bo Han2
1IBM, 2IBM Research
 Clinical Abbreviation Disambiguation Using Neural Word Embeddings
Yonghui Wu1, Jun Xu2, Yaoyun Zhang3, Hua Xu1
1The University of Texas Health Science Center at Houston, 2School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 3University of Texas School of Biomedical Informatics at Houston
 Representing Clinical Diagnostic Criteria in Quality Data Model Using Natural Language Processing
Na Hong1, Dingcheng Li1, Yue Yu1, Hongfang Liu1, Christopher G. Chute2, Guoqian Jiang1
1Mayo Clinic, 2Johns Hopkins University


BIONLP 2015 Call for Papers

Date of workshop: July 30, 2015

Venue: BioNLP 2015 will be held in conjunction with ACL 2015 in Beijing, People’s Republic of China.

IMPORTANT DATES

  • 14 May 2015: Submission due date
  • 4 June 2015: Notification of acceptance
  • 21 June 2015: Camera-ready papers due
  • 30 July 2015: Workshop, Beijing, PRC


Over the course of the past thirteen years, the ACL BioNLP workshop associated with the SIGBIOMED special interest group has established itself as the primary venue for presenting foundational research in language processing for the biological and medical domains. The workshop serves as both a venue for bringing together researchers in bio- and clinical NLP and exposing these researchers to the mainstream ACL research, and a venue for informing the mainstream ACL researchers about this fast-growing and important domain. The workshop will continue presenting work on a broad and interesting range of topics in NLP. Submissions are particularly solicited in the areas of:

  • Wide-scale entity identification and normalization
  • Extraction of complex relations and events
  • Discourse analysis
  • Coreference resolution
  • Text mining
  • Literature based discovery
  • Summarization
  • Question-answering
  • Lexical and terminological resources for BioNLP
  • Annotation (corpora), standards
  • Resources and strategies for system testing and evaluation
  • Processing and annotation platforms
  • Interoperable platforms for biomedical text mining
  • Domain adaptation
  • Translating NLP research to practice

Submission instructions:

Long papers may consist of up to eight (8) pages of content, plus two pages for references; final versions of long papers will be given one additional page (up to 9 pages with 2 pages for references) so that reviewers’comments can be taken into account.

Poster submissions may consist of up to four (4) pages of content, plus 2 pages for references. Upon acceptance, short papers will be given five (5) pages in the proceedings and 2 pages for references. Authors are encouraged to use this additional page to address reviewers comments in their final versions.

https://www.softconf.com/acl2015/BioNLP/ Authors who cannot submit a PDF file electronically should contact the workshop organizers well in advance of the submission deadline. Dual submission policy: note that papers may NOT be submitted to the BioNLP 2014 workshop if they are or will be concurrently submitted to another meeting or publication. Submissions should be anonymous.

Program committee:
  • Emilia Apostolova, DePaul University, Chicago, USA
  • Eiji Aramaki, University of Tokyo
  • Alan Aronson, National Library of Medicine
  • Sabine Bergler, Concordia University, Canada
  • Olivier Bodenreider, National Library of Medicine
  • Aaron Cohen, Oregon Health and Science University
  • Nigel Collier, EBI, the National Institute of Informatics
  • Noémie Elhadad, Columbia University
  • Marcelo Fiszman, National Library of Medicine
  • Filip Ginter, University of Turku
  • Cyril Grouin, LIMSI - CNRS, France
  • Antonio Jimeno Yepes, IBM, Melbourne Area, Australia
  • Halil Kilicoglu, National Library of Medicine
  • Jin-Dong Kim, Database Center for Life Science, Japan
  • Robert Leaman, National Library of Medicine
  • Zhiyong Lu, National Library of Medicine
  • Timothy Miller, Children's Hospital Boston
  • Makoto Miwa, Toyota Technological Institute, Japan
  • Aurelie Neveol, LIMSI - CNRS, France
  • Naoaki Okazaki, Tohoku University
  • Jong Park, KAIST
  • Sampo Pyysalo, University of Turku
  • Bastien Rance, Hopital Europeen Georges Pompidou
  • Thomas Rindflesch, National Library of Medicine
  • Kirk Roberts, National Library of Medicine
  • Andrey Rzhetsky, University of Chicago
  • Yoshimasa Tsuruoka, University of Tokyo, Japan
  • Karin Verspoor, The University of Melbourne, Australia
  • John Wilbur, National Library of Medicine
  • Pierre Zweigenbaum, LIMSI - CNRS, France
Organizers
 * Kevin Bretonnel Cohen, University of Colorado School of Medicine
 * Dina Demner-Fushman, US National Library of Medicine
 * Sophia Ananiadou, National Centre for Text Mining and University of Manchester, UK
 * Jun-ichi Tsujii, Microsoft Research Asia