Search Results - "Van Mulligen, Erik M."

A dictionary to identify small molecules and drugs in free text by Hettne, Kristina M., Stierum, Rob H., Schuemie, Martijn J., Hendriksen, Peter J. M., Schijvenaars, Bob J. A., Mulligen, Erik M. van, Kleinjans, Jos, Kors, Jan A.

“…Motivation: From the scientific community, a lot of effort has been spent on the correct identification of gene and protein names in text, while less effort…”
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QTLTableMiner ++ : semantic mining of QTL tables in scientific articles by Singh, Gurnoor, Kuzniar, Arnold, van Mulligen, Erik M, Gavai, Anand, Bachem, Christian W, Visser, Richard G F, Finkers, Richard

“…A quantitative trait locus (QTL) is a genomic region that correlates with a phenotype. Most of the experimental information about QTL mapping studies is…”
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Identifying genes targeted by disease-associated non-coding SNPs with a protein knowledge graph by Vlietstra, Wytze J, Vos, Rein, van Mulligen, Erik M, Jenster, Guido W, Kors, Jan A

“…Genome-wide association studies (GWAS) have identified many single nucleotide polymorphisms (SNPs) that play important roles in the genetic heritability of…”
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Drug prioritization using the semantic properties of a knowledge graph by Malas, Tareq B., Vlietstra, Wytze J., Kudrin, Roman, Starikov, Sergey, Charrout, Mohammed, Roos, Marco, Peters, Dorien J. M., Kors, Jan A., Vos, Rein, ‘t Hoen, Peter A. C., van Mulligen, Erik M., Hettne, Kristina M.

“…Compounds that are candidates for drug repurposing can be ranked by leveraging knowledge available in the biomedical literature and databases. This knowledge,…”
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Parasitic infections related to anti-type 2 immunity monoclonal antibodies: a disproportionality analysis in the food and drug administration’s adverse event reporting system (FAERS) by Pera, Victor, Brusselle, Guy G., Riemann, Sebastian, Kors, Jan A., Van Mulligen, Erik M., Parry, Rowan, de Wilde, Marcel, Rijnbeek, Peter R., Verhamme, Katia M. C.

“…Introduction: Monoclonal antibodies (mAbs) targeting immunoglobulin E (IgE) [omalizumab], type 2 (T2) cytokine interleukin (IL) 5 [mepolizumab, reslizumab],…”
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Automatic vs. manual curation of a multi-source chemical dictionary: the impact on text mining by Hettne, Kristina M, Williams, Antony J, van Mulligen, Erik M, Kleinjans, Jos, Tkachenko, Valery, Kors, Jan A

“…Background Previously, we developed a combined dictionary dubbed Chemlist for the identification of small molecules and drugs in text based on a number of…”
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Alignment of vaccine codes using an ontology of vaccine descriptions by Becker, Benedikt FH, Kors, Jan A, van Mulligen, Erik M, Sturkenboom, Miriam CJM

“…Background Vaccine information in European electronic health record (EHR) databases is represented using various clinical and database-specific coding systems…”
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Interoperability and FAIRness through a novel combination of Web technologies by Wilkinson, Mark D, Verborgh, Ruben, Bonino da Silva Santos, Luiz Olavo, Clark, Tim, Swertz, Morris A, Kelpin, Fleur D.L, Gray, Alasdair J.G, Schultes, Erik A, van Mulligen, Erik M, Ciccarese, Paolo, Kuzniar, Arnold, Gavai, Anand, Thompson, Mark, Kaliyaperumal, Rajaram, Bolleman, Jerven T, Dumontier, Michel

“…Data in the life sciences are extremely diverse and are stored in a broad spectrum of repositories ranging from those designed for particular data types (such…”
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Training text chunkers on a silver standard corpus: can silver replace gold? by Kang, Ning, van Mulligen, Erik M, Kors, Jan A

“…To train chunkers in recognizing noun phrases and verb phrases in biomedical text, an annotated corpus is required. The creation of gold standard corpora…”
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Identifying disease trajectories with predicate information from a knowledge graph by Vlietstra, Wytze J, Vos, Rein, van den Akker, Marjan, van Mulligen, Erik M, Kors, Jan A

“…Knowledge graphs can represent the contents of biomedical literature and databases as subject-predicate-object triples, thereby enabling comprehensive analyses…”
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Using predicate and provenance information from a knowledge graph for drug efficacy screening by Vlietstra, Wytze J, Vos, Rein, Sijbers, Anneke M, van Mulligen, Erik M, Kors, Jan A

“…Biomedical knowledge graphs have become important tools to computationally analyse the comprehensive body of biomedical knowledge. They represent knowledge as…”
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The EU-ADR Web Platform: delivering advanced pharmacovigilance tools by Oliveira, José Luis, Lopes, Pedro, Nunes, Tiago, Campos, David, Boyer, Scott, Ahlberg, Ernst, van Mulligen, Erik M., Kors, Jan A., Singh, Bharat, Furlong, Laura I., Sanz, Ferran, Bauer-Mehren, Anna, Carrascosa, Maria C., Mestres, Jordi, Avillach, Paul, Diallo, Gayo, Díaz Acedo, Carlos, van der Lei, Johan

“…ABSTRACT Purpose Pharmacovigilance methods have advanced greatly during the last decades, making post‐market drug assessment an essential drug evaluation…”
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Novel protein-protein interactions inferred from literature context by van Haagen, Herman H H B M, 't Hoen, Peter A C, Botelho Bovo, Alessandro, de Morrée, Antoine, van Mulligen, Erik M, Chichester, Christine, Kors, Jan A, den Dunnen, Johan T, van Ommen, Gert-Jan B, van der Maarel, Silvère M, Kern, Vinícius Medina, Mons, Barend, Schuemie, Martijn J

“…We have developed a method that predicts Protein-Protein Interactions (PPIs) based on the similarity of the context in which proteins appear in literature…”
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Using rule-based natural language processing to improve disease normalization in biomedical text by Kang, Ning, Singh, Bharat, Afzal, Zubair, van Mulligen, Erik M, Kors, Jan A

“…In order for computers to extract useful information from unstructured text, a concept normalization system is needed to link relevant concepts in a text to…”
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Annotation-preserving machine translation of English corpora to validate Dutch clinical concept extraction tools by Seinen, Tom M, Kors, Jan A, van Mulligen, Erik M, Rijnbeek, Peter R

“…To explore the feasibility of validating Dutch concept extraction tools using annotated corpora translated from English, focusing on preserving annotations…”
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The added value of text from Dutch general practitioner notes in predictive modeling by Seinen, Tom M, Kors, Jan A, van Mulligen, Erik M, Fridgeirsson, Egill, Rijnbeek, Peter R

“…Abstract Objective This work aims to explore the value of Dutch unstructured data, in combination with structured data, for the development of prognostic…”
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Use of unstructured text in prognostic clinical prediction models: a systematic review by Seinen, Tom M, Fridgeirsson, Egill A, Ioannou, Solomon, Jeannetot, Daniel, John, Luis H, Kors, Jan A, Markus, Aniek F, Pera, Victor, Rekkas, Alexandros, Williams, Ross D, Yang, Cynthia, van Mulligen, Erik M, Rijnbeek, Peter R

“…Abstract Objective This systematic review aims to assess how information from unstructured text is used to develop and validate clinical prognostic prediction…”
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A multilingual gold-standard corpus for biomedical concept recognition: the Mantra GSC by Kors, Jan A, Clematide, Simon, Akhondi, Saber A, van Mulligen, Erik M, Rebholz-Schuhmann, Dietrich

“…Objective To create a multilingual gold-standard corpus for biomedical concept recognition. Materials and methods We selected text units from different…”
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Disproportionality Analysis and Characterisation of Medication Errors in EudraVigilance: Exploring Findings on Sexes and Age Groups by Pera, Victor, Kors, Jan A., van Mulligen, Erik M., de Wilde, Marcel, Rijnbeek, Peter R., Verhamme, Katia M. C.

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A novel feature-based approach to extract drug-drug interactions from biomedical text by Bui, Quoc-Chinh, Sloot, Peter M A, van Mulligen, Erik M, Kors, Jan A

“…Knowledge of drug-drug interactions (DDIs) is crucial for health-care professionals to avoid adverse effects when co-administering drugs to patients. As most…”
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