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For participating in the SemEval 2013 challenge of recognition and classification of drug names, we adapted our chemical entity recognition approach consisting in Conditional Random Fields for recognizing chemical terms and lexical similarity for entity resolution to the ChEBI ontology. We obtained promising results, with a best F-measure of 0.81 for the(More)
According to previous reports, flavonoids and nutraceuticals correct defective electrolyte transport in cystic fibrosis (CF) airways. Traditional medicinal plants from China and Thailand contain phytoflavonoids and other bioactive compounds. We examined herbal extracts of the common Thai medicinal euphorbiaceous plant Phyllanthus acidus for their potential(More)
Chemical entities are ubiquitous through the biomedical literature and the development of text-mining systems that can efficiently identify those entities are required. Due to the lack of available corpora and data resources, the community has focused its efforts in the development of gene and protein named entity recognition systems, but with the release(More)
UNLABELLED The rapid development of CRISPR-Cas9 mediated genome editing techniques has given rise to a number of online and stand-alone tools to find and score CRISPR sites for whole genomes. Here we describe the Wellcome Trust Sanger Institute Genome Editing database (WGE), which uses novel methods to compute, visualize and select optimal CRISPR sites in a(More)
With the amount of chemical data being produced and reported in the literature growing at a fast pace, it is increasingly important to efficiently retrieve this information. To tackle this issue text mining tools have been applied, but despite their good performance they still provide many errors that we believe can be filtered by using semantic similarity.(More)
Biomedical literature is an important source of information for chemical compounds. However, different representations and nomenclatures for chemical entities exist, which makes the reference of chemical entities ambiguous. Many systems already exist for gene and protein entity recognition, however very few exist for chemical entities. The main reason for(More)
This document presents our approach to the BioCreative IV challenge of recognition and classification of drug names (CHEMDNER task). We developed a system based on Conditional Random Fields for recognizing chemical terms, and on ChEBI resolution and semantic similarity techniques for validating the recognition results. Our system created multiple(More)
Biomedical ontologies provide a commonly accepted scheme for the characterization of biological concepts that enable knowledge sharing and integration. Updating and maintaining an ontology requires highly specialized experts and is very time-consuming given the amount of literature that has to be analyzed and the difficulty in reaching consensus. This paper(More)
This software demonstration paper presents Identifying Chemical Entities (ICE), a platform composed by algorithms for chemical entity recognition, entity resolution to a reference database, namely ChEBI, and validation using chemical semantic similarity. It aims to provide the users with an improved display of entity recognition results, exposing outliers(More)
An important research topic in Bioinformatics involves the exploration of vast amounts of biological and biomedical scientific literature (BioLiterature). Over the last few decades, text-mining systems have exploited this BioLiterature to reduce the time spent by researchers in its analysis. However, state-of-the-art approaches are still far from reaching(More)