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Pro-Forma for Posting Studentships on Jobs

1) Title of studentship: Text Mining for Systems Biology 2) Anticipated start date for project: 01 September 2008 3) Closing date for applications: 1st July 2008 4) Information about the project: We offer one fully-funded BBSRC studentship associated with the ONDEX (http://www.ondex.org/) project. The studentship is available for three years. This PhD will investigate the recognition of contradictory evidence for molecular interactions from biomedical text using deep parsing, textual entailment and ontologies for pathway construction. The student will use NaCTeM's text mining tools adapted to biology (named entity recognisers, parsers, taggers) to extract entities and relations for systems biology applications. The successful applicant will be part of a team working in text mining in systems biology at the National Centre for Text Mining. She or he will also work directly with a team of systems biologists who are involved in the construction of computational models and who will act as users of the text mining results as well as domain specialists. Supervisors: a) Sophia Ananiadou, Reader in Text Mining, Director, National Centre for Text Mining, School of Computer Science, University of Manchester, [email protected] b) Pedro Mendes, Chair in Computational Systems Biology, School of Computer Science, University of Manchester, [email protected] The School of Computer Science at Manchester is globally renowned for its research quality, having contributed to some of the discipline’s most exciting and important innovations, from the creation of the world’s first stored program computer, to the development of next generation web technologies. We received a 6* rating at the last RAE. See www.cs.manchester.ac.uk/ for more information. The National Centre for Text Mining is the first centre for text mining in the world and has a growing team of 14 researchers and 4 staff. See www.nactem.ac.uk for more information. NaCTeM is located at the Manchester Interdisciplinary Biocentre (www.mib.ac.uk) and collaborates closely with the Manchester Centre for Integrative Systems Biology. The applicant will collaborate with members of both NaCTeM and MCISB. 5) Qualifications applicants should have/expected to receive: The applicant must have a minimum 2:1 (or equivalent) in Computer Science or a related discipline. Excellent programming skills and knowledge in text mining/natural language processing are prerequisites. 6) Amount of funding available and eligibility: The studentship is available for three years and covers tuition fees and a bursary of £12,600 per year (tax free). Candidates should be UK citizens or EU/EEA citizens with a relevant connection to the UK (a minimum of 3 years residence). See the BBSRC guidance for details: www.bbsrc.ac.uk/funding/training/eligibility.pdf 7) Contact for further information: Please send an email to Sophia Ananiadou ([email protected]) with your full CV including transcripts of courses taken and a page discussing your interests in this topic. 8) How to apply: Please send your application to Sophia Ananiadou in the first instance. .

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BMC Bioinformatics Biomed Central
BMC Bioinformatics BioMed Central Introduction Open Access Proceedings of the Second International Symposium for Semantic Mining in Biomedicine Sophia Ananiadou*1 and Juliane Fluck*2 Address: 1School of Computer Science, National Centre for Text Mining, Manchester Interdisciplinary Biocentre, University of Manchester, Oxford Road, M13 9PL, Manchester, UK and 2Fraunhofer Institute SCAI, Schloss Birlinghoven, 53754 St. Augustin, Germany Email: Sophia Ananiadou* - [email protected]; Juliane Fluck* - [email protected] * Corresponding authors from Second International Symposium on Semantic Mining in Biomedicine (SMBM) Jena, Germany. 9–12 April 2006 Published: 24 November 2006 <supplement> <title> <p>Second International Symposium on Semantic Mining in Biomedicine (SMBM)</p> </title> <editor>Sophia Ananiadou, Juliane Fluck</editor> <note>Proceedings</note> </supplement> BMC Bioinformatics 2006, 7(Suppl 3):S1 doi:10.1186/1471-2105-7-S3-S1 © 2006 Ananiadou and Fluck; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Introduction • discovery of semantic relations between entities With an overwhelming amount of biomedical knowledge recorded in texts, it is not surprising that there is so much • event discovery interest in techniques which can identify, extract, manage, integrate and exploit this knowledge, and moreover dis- The current limitations of using existing terminological cover new, hidden or unsuspected knowledge. For this and ontological resources such as the Gene Ontology, reason, in the past five years, there has been an upsurge of Swiss-Prot, Entrez Gene, UMLS, and Mesh etc.
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