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Journal of Biomedical Semantics

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https://www.readbyqxmd.com/read/29925405/adverse-event-detection-by-integrating-twitter-data-and-vaers
#1
Junxiang Wang, Liang Zhao, Yanfang Ye, Yuji Zhang
BACKGROUND: Vaccine has been one of the most successful public health interventions to date. However, vaccines are pharmaceutical products that carry risks so that many adverse events (AEs) are reported after receiving vaccines. Traditional adverse event reporting systems suffer from several crucial challenges including poor timeliness. This motivates increasing social media-based detection systems, which demonstrate successful capability to capture timely and prevalent disease information...
June 20, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29895320/disease-mentions-in-airport-and-hospital-geolocations-expose-dominance-of-news-events-for-disease-concerns
#2
Joana M Barros, Jim Duggan, Dietrich Rebholz-Schuhmann
BACKGROUND: In recent years, Twitter has been applied to monitor diseases through its facility to monitor users' comments and concerns in real-time. The analysis of tweets for disease mentions should reflect not only user specific concerns but also disease outbreaks. This requires the use of standard terminological resources and can be focused on selected geographic locations. In our study, we differentiate between hospital and airport locations to better distinguish disease outbreaks from background mentions of disease concerns...
June 12, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29880031/ontology-based-literature-mining-and-class-effect-analysis-of-adverse-drug-reactions-associated-with-neuropathy-inducing-drugs
#3
Junguk Hur, Arzucan Özgür, Yongqun He
BACKGROUND: Adverse drug reactions (ADRs), also called as drug adverse events (AEs), are reported in the FDA drug labels; however, it is a big challenge to properly retrieve and analyze the ADRs and their potential relationships from textual data. Previously, we identified and ontologically modeled over 240 drugs that can induce peripheral neuropathy through mining public drug-related databases and drug labels. However, the ADR mechanisms of these drugs are still unclear. In this study, we aimed to develop an ontology-based literature mining system to identify ADRs from drug labels and to elucidate potential mechanisms of the neuropathy-inducing drugs (NIDs)...
June 7, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29751829/querying-archetype-based-ehrs-by-search-ontology-based-xpath-engineering
#4
Stefan Kropf, Alexandr Uciteli, Katrin Schierle, Peter Krücken, Kerstin Denecke, Heinrich Herre
BACKGROUND: Legacy data and new structured data can be stored in a standardized format as XML-based EHRs on XML databases. Querying documents on these databases is crucial for answering research questions. Instead of using free text searches, that lead to false positive results, the precision can be increased by constraining the search to certain parts of documents. METHODS: A search ontology-based specification of queries on XML documents defines search concepts and relates them to parts in the XML document structure...
May 11, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29743102/extending-the-dideo-ontology-to-include-entities-from-the-natural-product-drug-interaction-domain-of-discourse
#5
John Judkins, Jessica Tay-Sontheimer, Richard D Boyce, Mathias Brochhausen
BACKGROUND: Prompted by the frequency of concomitant use of prescription drugs with natural products, and the lack of knowledge regarding the impact of pharmacokinetic-based natural product-drug interactions (PK-NPDIs), the United States National Center for Complementary and Integrative Health has established a center of excellence for PK-NPDI. The Center is creating a public database to help researchers (primarly pharmacologists and medicinal chemists) to share and access data, results, and methods from PK-NPDI studies...
May 9, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29669592/ggdonto-ontology-as-a-knowledge-base-for-genetic-diseases-and-disorders-of-glycan-metabolism-and-their-causative-genes
#6
Elena Solovieva, Toshihide Shikanai, Noriaki Fujita, Hisashi Narimatsu
BACKGROUND: Inherited mutations in glyco-related genes can affect the biosynthesis and degradation of glycans and result in severe genetic diseases and disorders. The Glyco-Disease Genes Database (GDGDB), which provides information about these diseases and disorders as well as their causative genes, has been developed by the Research Center for Medical Glycoscience (RCMG) and released in April 2010. GDGDB currently provides information on about 80 genetic diseases and disorders caused by single-gene mutations in glyco-related genes...
April 18, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29650041/deep-learning-meets-ontologies-experiments-to-anchor-the-cardiovascular-disease-ontology-in-the-biomedical-literature
#7
Mercedes Arguello Casteleiro, George Demetriou, Warren Read, Maria Jesus Fernandez Prieto, Nava Maroto, Diego Maseda Fernandez, Goran Nenadic, Julie Klein, John Keane, Robert Stevens
BACKGROUND: Automatic identification of term variants or acceptable alternative free-text terms for gene and protein names from the millions of biomedical publications is a challenging task. Ontologies, such as the Cardiovascular Disease Ontology (CVDO), capture domain knowledge in a computational form and can provide context for gene/protein names as written in the literature. This study investigates: 1) if word embeddings from Deep Learning algorithms can provide a list of term variants for a given gene/protein of interest; and 2) if biological knowledge from the CVDO can improve such a list without modifying the word embeddings created...
April 12, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29602312/clinical-natural-language-processing-in-languages-other-than-english-opportunities-and-challenges
#8
REVIEW
Aurélie Névéol, Hercules Dalianis, Sumithra Velupillai, Guergana Savova, Pierre Zweigenbaum
BACKGROUND: Natural language processing applied to clinical text or aimed at a clinical outcome has been thriving in recent years. This paper offers the first broad overview of clinical Natural Language Processing (NLP) for languages other than English. Recent studies are summarized to offer insights and outline opportunities in this area. MAIN BODY: We envision three groups of intended readers: (1) NLP researchers leveraging experience gained in other languages, (2) NLP researchers faced with establishing clinical text processing in a language other than English, and (3) clinical informatics researchers and practitioners looking for resources in their languages in order to apply NLP techniques and tools to clinical practice and/or investigation...
March 30, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29554977/matching-biomedical-ontologies-based-on-formal-concept-analysis
#9
Mengyi Zhao, Songmao Zhang, Weizhuo Li, Guowei Chen
BACKGROUND: The goal of ontology matching is to identify correspondences between entities from different yet overlapping ontologies so as to facilitate semantic integration, reuse and interoperability. As a well developed mathematical model for analyzing individuals and structuring concepts, Formal Concept Analysis (FCA) has been applied to ontology matching (OM) tasks since the beginning of OM research, whereas ontological knowledge exploited in FCA-based methods is limited. This motivates the study in this paper, i...
March 19, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29444698/using-owl-reasoning-to-support-the-generation-of-novel-gene-sets-for-enrichment-analysis
#10
David J Osumi-Sutherland, Enrico Ponta, Melanie Courtot, Helen Parkinson, Laura Badi
BACKGROUND: The Gene Ontology (GO) consists of over 40,000 terms for biological processes, cell components and gene product activities linked into a graph structure by over 90,000 relationships. It has been used to annotate the functions and cellular locations of several million gene products. The graph structure is used by a variety of tools to group annotated genes into sets whose products share function or location. These gene sets are widely used to interpret the results of genomics experiments by assessing which sets are significantly over- or under-represented in results lists...
February 14, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29422110/supporting-shared-hypothesis-testing-in-the-biomedical-domain
#11
Asan Agibetov, Ernesto Jiménez-Ruiz, Marta Ondrésik, Alessandro Solimando, Imon Banerjee, Giovanna Guerrini, Chiara E Catalano, Joaquim M Oliveira, Giuseppe Patanè, Rui L Reis, Michela Spagnuolo
BACKGROUND: Pathogenesis of inflammatory diseases can be tracked by studying the causality relationships among the factors contributing to its development. We could, for instance, hypothesize on the connections of the pathogenesis outcomes to the observed conditions. And to prove such causal hypotheses we would need to have the full understanding of the causal relationships, and we would have to provide all the necessary evidences to support our claims. In practice, however, we might not possess all the background knowledge on the causality relationships, and we might be unable to collect all the evidence to prove our hypotheses...
February 8, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29409535/dmto-a-realistic-ontology-for-standard-diabetes-mellitus-treatment
#12
Shaker El-Sappagh, Daehan Kwak, Farman Ali, Kyung-Sup Kwak
BACKGROUND: Treatment of type 2 diabetes mellitus (T2DM) is a complex problem. A clinical decision support system (CDSS) based on massive and distributed electronic health record data can facilitate the automation of this process and enhance its accuracy. The most important component of any CDSS is its knowledge base. This knowledge base can be formulated using ontologies. The formal description logic of ontology supports the inference of hidden knowledge. Building a complete, coherent, consistent, interoperable, and sharable ontology is a challenge...
February 6, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29382397/exploiting-graph-kernels-for-high-performance-biomedical-relation-extraction
#13
Nagesh C Panyam, Karin Verspoor, Trevor Cohn, Kotagiri Ramamohanarao
BACKGROUND: Relation extraction from biomedical publications is an important task in the area of semantic mining of text. Kernel methods for supervised relation extraction are often preferred over manual feature engineering methods, when classifying highly ordered structures such as trees and graphs obtained from syntactic parsing of a sentence. Tree kernels such as the Subset Tree Kernel and Partial Tree Kernel have been shown to be effective for classifying constituency parse trees and basic dependency parse graphs of a sentence...
January 30, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29347997/openbiodiv-o-ontology-of-the-openbiodiv-knowledge-management-system
#14
Viktor Senderov, Kiril Simov, Nico Franz, Pavel Stoev, Terry Catapano, Donat Agosti, Guido Sautter, Robert A Morris, Lyubomir Penev
BACKGROUND: The biodiversity domain, and in particular biological taxonomy, is moving in the direction of semantization of its research outputs. The present work introduces OpenBiodiv-O, the ontology that serves as the basis of the OpenBiodiv Knowledge Management System. Our intent is to provide an ontology that fills the gaps between ontologies for biodiversity resources, such as DarwinCore-based ontologies, and semantic publishing ontologies, such as the SPAR Ontologies. We bridge this gap by providing an ontology focusing on biological taxonomy...
January 18, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29347969/miro-guidelines-for-minimum-information-for-the-reporting-of-an-ontology
#15
REVIEW
Nicolas Matentzoglu, James Malone, Chris Mungall, Robert Stevens
BACKGROUND: Creation and use of ontologies has become a mainstream activity in many disciplines, in particular, the biomedical domain. Ontology developers often disseminate information about these ontologies in peer-reviewed ontology description reports. There appears to be, however, a high degree of variability in the content of these reports. Often, important details are omitted such that it is difficult to gain a sufficient understanding of the ontology, its content and method of creation...
January 18, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29335022/tackling-the-challenges-of-matching-biomedical-ontologies
#16
Daniel Faria, Catia Pesquita, Isabela Mott, Catarina Martins, Francisco M Couto, Isabel F Cruz
BACKGROUND: Biomedical ontologies pose several challenges to ontology matching due both to the complexity of the biomedical domain and to the characteristics of the ontologies themselves. The biomedical tracks in the Ontology Matching Evaluation Initiative (OAEI) have spurred the development of matching systems able to tackle these challenges, and benchmarked their general performance. In this study, we dissect the strategies employed by matching systems to tackle the challenges of matching biomedical ontologies and gauge the impact of the challenges themselves on matching performance, using the AgreementMakerLight (AML) system as the platform for this study...
January 15, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29329592/the-extensible-ontology-development-xod-principles-and-tool-implementation-to-support-ontology-interoperability
#17
REVIEW
Yongqun He, Zuoshuang Xiang, Jie Zheng, Yu Lin, James A Overton, Edison Ong
Ontologies are critical to data/metadata and knowledge standardization, sharing, and analysis. With hundreds of biological and biomedical ontologies developed, it has become critical to ensure ontology interoperability and the usage of interoperable ontologies for standardized data representation and integration. The suite of web-based Ontoanimal tools (e.g., Ontofox, Ontorat, and Ontobee) support different aspects of extensible ontology development. By summarizing the common features of Ontoanimal and other similar tools, we identified and proposed an "eXtensible Ontology Development" (XOD) strategy and its associated four principles...
January 12, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29316970/cuiless2016-a-clinical-corpus-applying-compositional-normalization-of-text-mentions
#18
John D Osborne, Matthew B Neu, Maria I Danila, Thamar Solorio, Steven J Bethard
BACKGROUND: Traditionally text mention normalization corpora have normalized concepts to single ontology identifiers ("pre-coordinated concepts"). Less frequently, normalization corpora have used concepts with multiple identifiers ("post-coordinated concepts") but the additional identifiers have been restricted to a defined set of relationships to the core concept. This approach limits the ability of the normalization process to express semantic meaning. We generated a freely available corpus using post-coordinated concepts without a defined set of relationships that we term "compositional concepts" to evaluate their use in clinical text...
January 10, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29316968/improving-the-interoperability-of-biomedical-ontologies-with-compound-alignments
#19
Daniela Oliveira, Catia Pesquita
BACKGROUND: Ontologies are commonly used to annotate and help process life sciences data. Although their original goal is to facilitate integration and interoperability among heterogeneous data sources, when these sources are annotated with distinct ontologies, bridging this gap can be challenging. In the last decade, ontology matching systems have been evolving and are now capable of producing high-quality mappings for life sciences ontologies, usually limited to the equivalence between two ontologies...
January 9, 2018: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29258588/integrating-phenotype-ontologies-with-phenomenet
#20
Miguel Ángel Rodríguez-García, Georgios V Gkoutos, Paul N Schofield, Robert Hoehndorf
BACKGROUND: Integration and analysis of phenotype data from humans and model organisms is a key challenge in building our understanding of normal biology and pathophysiology. However, the range of phenotypes and anatomical details being captured in clinical and model organism databases presents complex problems when attempting to match classes across species and across phenotypes as diverse as behaviour and neoplasia. We have previously developed PhenomeNET, a system for disease gene prioritization that includes as one of its components an ontology designed to integrate phenotype ontologies...
December 19, 2017: Journal of Biomedical Semantics
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