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RDF2Vec-based Classification of Ontology Alignment Changes [article]

Matthias Jurisch, Bodo Igler
2018 arXiv   pre-print
Especially for large ontologies this is a costly task often consisting of manual work.  ...  When ontologies cover overlapping topics, the overlap can be represented using ontology alignments. These alignments need to be continuously adapted to changing ontologies.  ...  To denote a change of an ontology over time, we use the prime symbol (e.g., a changed version of O is denoted as O ′ ).  ... 
arXiv:1805.09145v1 fatcat:a3vnatg3yvhqtnhvnzf6pkwrxu

Neuro-symbolic representation learning on biological knowledge graphs

Mona Alshahrani, Mohammad Asif Khan, Omar Maddouri, Akira R Kinjo, Núria Queralt-Rosinach, Robert Hoehndorf, Janet Kelso
2017 Bioinformatics  
Through the use of symbolic logic, these embeddings contain both explicit and implicit information.  ...  Our method combines symbolic methods, in particular knowledge representation using symbolic logic and automated reasoning, with neural networks to generate embeddings of nodes that encode for related information  ...  In biological and biomedical ontologies, the OWL 2 EL profile is widely used to develop the large ontologies that are in use in the domain, and has been found to be useful and sufficient for a large number  ... 
doi:10.1093/bioinformatics/btx275 pmid:28449114 pmcid:PMC5860058 fatcat:6henlhfbgvee3m74izxt4rgcmq

Neurological Disorders and Publication Abstracts Follow Elements of Social Network Patterns when Indexed Using Ontology Tree-Based Key Term Search [chapter]

Anand Kulanthaivel, Robert P. Light, Katy Börner, Chin Hua Kong, Josette F. Jones
2014 Lecture Notes in Computer Science  
Lastly, we discuss potential consumer-centered as well as clinic-centered uses for our ontology and search methodology.  ...  Using literal search methodology with our terminology tree, we find over 5,200 relationships between abstracts and clinical diagnostic topics.  ...  Power analysis and regressions were performed in SAS v9.4 [16] . 3 Results & Conclusions Match Rates Match Rate of Publications.  ... 
doi:10.1007/978-3-319-07446-7_27 fatcat:26kzeyfk35gm5fnvu6hlfz6uqa

Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations

Fatima Zohra Smaili, Xin Gao, Robert Hoehndorf
2018 Bioinformatics  
We propose the Onto2Vec method, an approach to learn feature vectors for biological entities based on their annotations to biomedical ontologies.  ...  Our method can be applied to a wide range of bioinformatics research problems such as similarity-based prediction of interactions between proteins, classification of interaction types using supervised  ...  In biology and biomedicine, where a large amount of symbolic structures (ontologies and knowledge graphs) are in use, there are many potential applications for neural-symbolic systems [19] .  ... 
doi:10.1093/bioinformatics/bty259 pmid:29949999 pmcid:PMC6022543 fatcat:nmb7uxfcgzhpvix3ccczi3hlge

Ontology Matching: State of the Art and Future Challenges

P. Shvaiko, J. Euzenat
2013 IEEE Transactions on Knowledge and Data Engineering  
After years of research on ontology matching, it is reasonable to consider several questions: is the field of ontology matching still making progress?  ...  To answer these questions, we review the state of the art of ontology matching and analyze the results of recent ontology matching evaluations.  ...  SAMBO is a system for matching and merging biomedical ontologies [37] . It handles ontologies in OWL and outputs 1:1 alignments between concepts and relations.  ... 
doi:10.1109/tkde.2011.253 fatcat:kswkwny4vreyjlpf2ybpgxpmam

Event Extraction from Biomedical Literature [article]

Abdur Rahman M.A. Basher, Alexander S. Purdy, Inanc Birol
2015 bioRxiv   pre-print
NLP approaches to the automatic extraction of biomedical entities and relationships may assist the development of explanatory models that can comprehensively scan and summarize biomedical articles for  ...  In this article, we explore the latest advances in automated event extraction methods in the biomedical domain, focusing primarily on tools participated in the Biomedical NLP (BioNLP) Shared Task (ST)  ...  The 'Collaborative Annotation of a Large Biomedical Corpus' (CALBC) project offer a list of their gold standard corpora [27] .  ... 
doi:10.1101/034397 fatcat:uq5y7yop2nhyfg4ijjy34mwd6e

Combining gene sequence similarity and textual information for gene function annotation in the literature

Luo Si, Danni Yu, Daisuke Kihara, Yi Fang
2008 Information retrieval (Boston)  
However, the performance of most information extraction techniques of function annotation in the biomedical literature is not satisfactory due to the large variability in the expression of concepts in  ...  the biomedical literature.  ...  The GO ontology used in this work (version of Dec 12, 2006) contains about 23,000 gene ontology terms.  ... 
doi:10.1007/s10791-008-9053-0 fatcat:vxlvdeza2rbjfmcx2hvuosc7py

HuPSON: the human physiology simulation ontology

Michaela Gündel, Erfan Younesi, Ashutosh Malhotra, Jiali Wang, Hui Li, Bijun Zhang, Bernard de Bono, Heinz-Theodor Mevissen, Martin Hofmann-Apitius
2013 Journal of Biomedical Semantics  
Large biomedical simulation initiatives, such as the Virtual Physiological Human (VPH), are substantially dependent on controlled vocabularies to facilitate the exchange of information, of data and of  ...  The ontology is based on the Basic Formal Ontology, and adheres to the MIREOT principles; the constructed ontology has been evaluated via structural features, competency questions and use case scenarios  ...  Acknowledgements This work was conducted using the Protégé resource, which is supported by grant LM007885 from the United States National Library of Medicine.  ... 
doi:10.1186/2041-1480-4-35 pmid:24267822 pmcid:PMC4177144 fatcat:zjjzvomhdvhlnpt3n4hrczcgvu

Beware of the hierarchy - An analysis of ontology evolution and the materialisation impact for biomedical ontologies

Romana Pernisch, Daniele Dell'Aglio, Abraham Bernstein
2021 Journal of Web Semantics  
To see these measures in action, we investigate the evolution and its impact on materialisation for nine open biomedical ontologies, most of which adhere to the EL ++ description logic.  ...  Investigating the impact of the evolution gives us insight into the editing behaviour but also signals ontology engineers and users how the ontology evolution is affecting other applications.  ...  Further, we find Table 1 Definitions of symbols used in Fig. 1 and in the definitions of metrics in Section 3.1.  ... 
doi:10.1016/j.websem.2021.100658 fatcat:epzlliglzbdwzcpfl4kqdgjoci

Exploring Word Embedding for Drug Name Recognition

Isabel Segura-Bedmar, Víctor Suárez-Paniagua, Paloma Martínez
2015 Proceedings of the Sixth International Workshop on Health Text Mining and Information Analysis  
This paper describes a machine learningbased approach that uses word embedding features to recognize drug names from biomedical texts.  ...  Our main goal is to study the effectiveness of using word embeddings as features to improve performance on our baseline system, as well as to analyze whether the DINTO ontology could be a valuable complementary  ...  CRF was the most used technique followed by Support Vector Machines (SVM) and logistic regression.  ... 
doi:10.18653/v1/w15-2608 dblp:conf/acl-louhi/Segura-BedmarSM15 fatcat:inleb6b2z5ed3e5wbhtstqi2uq

OmniSearch: a semantic search system based on the Ontology for MIcroRNA Target (OMIT) for microRNA-target gene interaction data

Jingshan Huang, Fernando Gutierrez, Harrison J. Strachan, Dejing Dou, Weili Huang, Barry Smith, Judith A. Blake, Karen Eilbeck, Darren A. Natale, Yu Lin, Bin Wu, Nisansa de Silva (+5 others)
2016 Journal of Biomedical Semantics  
The realization of miRNA functions depends largely on how miRNAs regulate specific target genes.  ...  In this paper we describe our continuing effort to develop the OMIT, and demonstrate its use within a semantic search system, OmniSearch, designed to facilitate knowledge capture of miRNA-target interaction  ...  Related work Related work in biomedical ontologies The use of ontologies to describe, define, and integrate biological entities has long been embraced by the biological, biomedical, and clinical research  ... 
doi:10.1186/s13326-016-0064-2 pmid:27175225 pmcid:PMC4863347 fatcat:wgowilvzsjcj7kvabm3wcrk6te

GeneAnalytics: An Integrative Gene Set Analysis Tool for Next Generation Sequencing, RNAseq and Microarray Data

Shani Ben-Ari Fuchs, Iris Lieder, Gil Stelzer, Yaron Mazor, Ella Buzhor, Sergey Kaplan, Yoel Bogoch, Inbar Plaschkes, Alina Shitrit, Noa Rappaport, Asher Kohn, Ron Edgar (+6 others)
2016 Omics  
Postgenomics data are produced in large volumes by life sciences and clinical applications of novel omics diagnostics and therapeutics for precision medicine.  ...  In conventional examples, the Gene Ontology database is used for the functional study of large scale genomics or transcriptomics data.  ...  Gene Ontology (GO) terms and phenotypes The matching algorithm for both GO terms and phenotypes is based on the binomial distribution and is identical to that used in the pathways category (see Supplementary  ... 
doi:10.1089/omi.2015.0168 pmid:26983021 pmcid:PMC4799705 fatcat:junnrkt4azhylnekrwj2rf6tem

Text2Node: a Cross-Domain System for Mapping Arbitrary Phrases to a Taxonomy [article]

Rohollah Soltani, Alexandre Tomberg
2019 arXiv   pre-print
Existing methods of mapping coding standards based on manual human experts mapping, dictionary mapping, symbolic NLP and classification are unscalable and cannot accommodate large scale EHR datasets.  ...  Electronic health record (EHR) systems are used extensively throughout the healthcare domain.  ...  To document the complex relationships, large databases have been built, including biomedical knowledge graphs (e.g. PharmGKB [16] , Drug-Bank [37] ), ontologies (e.g.  ... 
arXiv:1905.01958v1 fatcat:chrv7er4tbe53mk7tdikt4frqe

Wikidata as a FAIR knowledge graph for the life sciences [article]

Andra Waagmeester, Gregory Stupp, Sebastian Burgstaller-Muehlbacher, Benjamin M Good, Malachi Griffith, Obi Griffith, Kristina Hanspers, Henning Hermjakob, Kevin Hybiske, Sarah M. Keating, Magnus Manske, Michael Mayers (+12 others)
2019 bioRxiv   pre-print
Finally, we demonstrate how the continuously updated, crowd-contributed knowledge in Wikidata can be used to improve the representation, integration, and analysis of biomedical information.  ...  Wikidata is a well-suited infrastructure for creating, editing, integrating, and accessing biomedical knowledge.  ...  Rephetio uses 31 logistic regression, with features based on graph metapaths, to predict drug repurposing candidates. 32 33 Figure 5 . 5 Drug repurposing using the Wikidata knowledge graph.  ... 
doi:10.1101/799684 fatcat:inurqfmvv5cbxhoucg5grj6srm

An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition

George Tsatsaronis, Georgios Balikas, Prodromos Malakasiotis, Ioannis Partalas, Matthias Zschunke, Michael R Alvers, Dirk Weissenborn, Anastasia Krithara, Sergios Petridis, Dimitris Polychronopoulos, Yannis Almirantis, John Pavlopoulos (+10 others)
2015 BMC Bioinformatics  
unstructured data (e.g., biomedical articles), and none of them pushed at the same time towards matching questions to answers at the conceptual level, i.e., by using concepts from domain ontologies to  ...  Description of the BIOASQ Tasks Description of Task 1a Task 1a, titled "Large scale online biomedical semantic indexing", deals with large scale classification of biomedical documents into ontology concepts  ...  Additional file 3: Example of a PUBMED query that is used to generate a test dataset for BIOASQ Task 1a.  ... 
doi:10.1186/s12859-015-0564-6 pmid:25925131 pmcid:PMC4450488 fatcat:u5enfjjos5gv5k3wkjxxa5ebry
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