@neuLink: a service-oriented application for biomedical knowledge discovery.

We introduce the architecture of @neuLink, a service-oriented environment for biomedical knowledge discovery which has been developed in the course of EU Integrated Project @neurIST. The application integrates data from databases with information extracted from unstructured text sources. Moreover, @neuLink supports the analysis of primary biomolecular data associated with individual patients and thus enables the interpretation of molecular data inside a clinical research environment. Based on an assembly of data services, @neuLink interacts with the complex @neurIST grid infrastructure through a dedicated data access and data mediation service. Data types integrated by @neuLink are covering the entire span of biomolecular entities: from gene names in text to entries in EntrezGene; from mentions of drugs to Drugbank, from information on allelic variants in scientific literature to entries in dbSNP. The architecture of @neuLink allows easy integration of other webservice-based applications and thus the spectrum of analysis capabilities of @neuLink can be extended following the requirements of the users of the @neurIST system.

OSIRISv1.2: a named entity recognition system for sequence variants of genes in biomedical literature.

BACKGROUND: Single Nucleotide Polymorphisms, among other type of sequence variants, constitute key elements in genetic epidemiology and pharmacogenomics. While sequence data about genetic variation is found at databases such as dbSNP, clues about the functional and phenotypic consequences of the variations are generally found in biomedical literature. The identification of the relevant documents and the extraction of the information from them are hampered by the large size of literature databases and the lack of widely accepted standard notation for biomedical entities. Thus, automatic systems for the identification of citations of allelic variants of genes in biomedical texts are required. RESULTS: Our group has previously reported the development of OSIRIS, a system aimed at the retrieval of literature about allelic variants of genes http://ibi.imim.es/osirisform.html. Here we describe the development of a new version of OSIRIS (OSIRISv1.2, http://ibi.imim.es/OSIRISv1.2.html) which incorporates a new entity recognition module and is built on top of a local mirror of the MEDLINE collection and HgenetInfoDB: a database that collects data on human gene sequence variations. The new entity recognition module is based on a pattern-based search algorithm for the identification of variation terms in the texts and their mapping to dbSNP identifiers. The performance of OSIRISv1.2 was evaluated on a manually annotated corpus, resulting in 99% precision, 82% recall, and an F-score of 0.89. As an example, the application of the system for collecting literature citations for the allelic variants of genes related to the diseases intracranial aneurysm and breast cancer is presented. CONCLUSION: OSIRISv1.2 can be used to link literature references to dbSNP database entries with high accuracy, and therefore is suitable for collecting current knowledge on gene sequence variations and supporting the functional annotation of variation databases. The application of OSIRISv1.2 in combination with controlled vocabularies like MeSH provides a way to identify associations of biomedical interest, such as those that relate SNPs with diseases.