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Data Integration in the Life Sciences

Volume 5647 of the series Lecture Notes in Computer Science pp 127-140

Slicing through the Scientific Literature

  • Christopher J. O. BakerAffiliated withCarnegie Mellon UniversityDepartment of Computer Science & Applied Statistics, University of New Brunswick
  • , Patrick LambrixAffiliated withCarnegie Mellon UniversityDepartment of Computer and Information Science, Linköpings universitet
  • , Jonas Laurila BergmanAffiliated withCarnegie Mellon UniversityDepartment of Computer and Information Science, Linköpings universitet
  • , Rajaraman KanagasabaiAffiliated withCarnegie Mellon UniversityData Mining Department, Institute for Infocomm Research, Agency for Science Technology and Research
  • , Wee Tiong AngAffiliated withCarnegie Mellon UniversityData Mining Department, Institute for Infocomm Research, Agency for Science Technology and Research

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Abstract

Success in the life sciences depends on access to information in knowlegde bases and literature. Finding and extracting the relevant information depends on a user’s domain knowledge and the knowledge of the search technology. In this paper we present a system that helps users formulate queries and search the scientific literature. The system coordinates ontologies, knowledge representation, text mining and NLP techniques to generate relevant queries in response to keyword input from the user. Queries are presented in natural language, translated to formal query syntax and issued to a knowledge base of scientific literature, documents or aligned document segments. We describe the components of the system and exemplify using real-world examples.