Simon Clematide
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Explore the profile of Simon Clematide including associated specialties, affiliations and a list of published articles.
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12
Citations
191
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Recent Articles
1.
Rinaldi F, Ellendorff T, Madan S, Clematide S, van der Lek A, Mevissen T, et al.
Database (Oxford)
. 2016 Jul;
2016.
PMID: 27402677
Automatic extraction of biological network information is one of the most desired and most complex tasks in biological and medical text mining. Track 4 at BioCreative V attempts to approach...
2.
Kors J, Clematide S, Akhondi S, van Mulligen E, Rebholz-Schuhmann D
J Am Med Inform Assoc
. 2015 May;
22(5):948-56.
PMID: 25948699
Objective: To create a multilingual gold-standard corpus for biomedical concept recognition. Materials And Methods: We selected text units from different parallel corpora (Medline abstract titles, drug labels, biomedical patent claims)...
3.
Rinaldi F, Clematide S, Marques H, Ellendorff T, Romacker M, Rodriguez-Esteban R
BMC Bioinformatics
. 2014 Dec;
15 Suppl 14:S6.
PMID: 25472638
Text mining services are rapidly becoming a crucial component of various knowledge management pipelines, for example in the process of database curation, or for exploration and enrichment of biomedical data...
4.
Gama-Castro S, Rinaldi F, Lopez-Fuentes A, Balderas-Martinez Y, Clematide S, Ellendorff T, et al.
Database (Oxford)
. 2014 Jun;
2014.
PMID: 24903516
Given the current explosion of data within original publications generated in the field of genomics, a recognized bottleneck is the transfer of such knowledge into comprehensive databases. We have for...
5.
Rinaldi F, Clematide S, Hafner S, Schneider G, Grigonyte G, Romacker M, et al.
Database (Oxford)
. 2013 Feb;
2013:bas053.
PMID: 23396322
In this article, we describe the architecture of the OntoGene Relation mining pipeline and its application in the triage task of BioCreative 2012. The aim of the task is to...
6.
Clematide S, Rinaldi F
J Biomed Semantics
. 2012 Oct;
3 Suppl 3:S5.
PMID: 23046495
Background: One of the key pieces of information which biomedical text mining systems are expected to extract from the literature are interactions among different types of biomedical entities (proteins, genes,...
7.
Rinaldi F, Schneider G, Clematide S
J Biomed Inform
. 2012 May;
45(5):851-61.
PMID: 22580177
The mutual interactions among genes, diseases, and drugs are at the heart of biomedical research, and are especially important for the pharmacological industry. The recent trend towards personalized medicine makes...
8.
Rinaldi F, Clematide S, Garten Y, Whirl-Carrillo M, Gong L, Hebert J, et al.
Database (Oxford)
. 2012 Apr;
2012:bas021.
PMID: 22529178
The need for efficient text-mining tools that support curation of the biomedical literature is ever increasing. In this article, we describe an experiment aimed at verifying whether a text-mining tool...
9.
Arighi C, Roberts P, Agarwal S, Bhattacharya S, Cesareni G, Chatr-Aryamontri A, et al.
BMC Bioinformatics
. 2011 Dec;
12 Suppl 8:S4.
PMID: 22151968
Background: The BioCreative challenge evaluation is a community-wide effort for evaluating text mining and information extraction systems applied to the biological domain. The biocurator community, as an active user of...
10.
Schneider G, Clematide S, Rinaldi F
BMC Bioinformatics
. 2011 Dec;
12 Suppl 8:S13.
PMID: 22151872
Background: This article describes the approaches taken by the OntoGene group at the University of Zurich in dealing with two tasks of the BioCreative III competition: classification of articles which...