Laura Inés Furlong

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We present the first RDF representation of DisGeNET, a gene-disease database designed to integrate the current knowledge of human diseases. DisGeNET RDF data introduces a harmonized and semantically enriched description of the gene-disease association concept into the Semantic Web (SW) by means of the DisGeNET ontology. The centric view on gene-disease(More)
UNLABELLED DisGeNET is a plugin for Cytoscape to query and analyze human gene-disease networks. DisGeNET allows user-friendly access to a new gene-disease database that we have developed by integrating data from several public sources. DisGeNET permits queries restricted to (i) the original data source, (ii) the association type, (iii) the disease class or(More)
Corpora with specific entities and relationships annotated are essential to train and evaluate text-mining systems that are developed to extract specific structured information from a large corpus. In this paper we describe an approach where a named-entity recognition system produces a first annotation and annotators revise this annotation using a web-based(More)
UNLABELLED Sequence variants, in particular single nucleotide polymorphisms (SNPs), are key elements for the identification of genes associated with complex diseases and with particular drug responses. The search for literature about sequence variation is hampered by the large number of allelic variants reported for many genes and by the variability in both(More)
The influence of genetic variations on diseases or cellular processes is the main focus of many investigations, and results of biomedical studies are often only accessible through scientific publications. Automatic extraction of this information requires recognition of the gene names and the accompanying allelic variant information. In a previous work, the(More)
We present the information extraction system <i>Text2SemRel</i>. The system (semi-) automatically constructs knowledge bases from textual data consisting of facts about entities using semantic relations. An integral part of the system is a graph-based interactive visualization and search layer. The second contribution in this paper is the presentation of a(More)
BACKGROUND Cluster-based descriptions of biological networks have received much attention in recent years fostered by accumulated evidence of the existence of meaningful correlations between topological network clusters and biological functional modules. Several well-performing clustering algorithms exist to infer topological network partitions. However,(More)
A standard model for exposing structured provenance meta-data of scientific assertions on the Semantic Web would increase interop-erability, discoverability, reliability, as well as reproducibility for scientific discourse and evidence-based knowledge discovery. Several Resource Description Framework (RDF) models have been proposed to track prove-nance.(More)
Cancer is a group of diseases that causes millions of deaths worldwide. Among cancers, Solid Tumors (ST) stand-out due to their high incidence and mortality rates. Disruption of cell-cell adhesion is highly relevant during tumor progression. Epithelial-cadherin (protein: E-cadherin, gene: CDH1) is a key molecule in cell-cell adhesion and an abnormal(More)
Most hospitals have already implemented information systems and Electronic Health Records (EHRs), but the reuse of such data for research is still infrequent. We present a pilot project on the exploitation of clinical information from a Spanish hospital database in the context of the European Medical Information Framework project (EMIF). Specific use cases(More)