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Sample records for gene ontology consortium

  1. Gene Ontology Consortium: going forward.

    Science.gov (United States)

    2015-01-01

    The Gene Ontology (GO; http://www.geneontology.org) is a community-based bioinformatics resource that supplies information about gene product function using ontologies to represent biological knowledge. Here we describe improvements and expansions to several branches of the ontology, as well as updates that have allowed us to more efficiently disseminate the GO and capture feedback from the research community. The Gene Ontology Consortium (GOC) has expanded areas of the ontology such as cilia-related terms, cell-cycle terms and multicellular organism processes. We have also implemented new tools for generating ontology terms based on a set of logical rules making use of templates, and we have made efforts to increase our use of logical definitions. The GOC has a new and improved web site summarizing new developments and documentation, serving as a portal to GO data. Users can perform GO enrichment analysis, and search the GO for terms, annotations to gene products, and associated metadata across multiple species using the all-new AmiGO 2 browser. We encourage and welcome the input of the research community in all biological areas in our continued effort to improve the Gene Ontology. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  2. Gene Ontology

    Directory of Open Access Journals (Sweden)

    Gaston K. Mazandu

    2012-01-01

    Full Text Available The wide coverage and biological relevance of the Gene Ontology (GO, confirmed through its successful use in protein function prediction, have led to the growth in its popularity. In order to exploit the extent of biological knowledge that GO offers in describing genes or groups of genes, there is a need for an efficient, scalable similarity measure for GO terms and GO-annotated proteins. While several GO similarity measures exist, none adequately addresses all issues surrounding the design and usage of the ontology. We introduce a new metric for measuring the distance between two GO terms using the intrinsic topology of the GO-DAG, thus enabling the measurement of functional similarities between proteins based on their GO annotations. We assess the performance of this metric using a ROC analysis on human protein-protein interaction datasets and correlation coefficient analysis on the selected set of protein pairs from the CESSM online tool. This metric achieves good performance compared to the existing annotation-based GO measures. We used this new metric to assess functional similarity between orthologues, and show that it is effective at determining whether orthologues are annotated with similar functions and identifying cases where annotation is inconsistent between orthologues.

  3. Gene Ontology-Based Analysis of Zebrafish Omics Data Using the Web Tool Comparative Gene Ontology.

    Science.gov (United States)

    Ebrahimie, Esmaeil; Fruzangohar, Mario; Moussavi Nik, Seyyed Hani; Newman, Morgan

    2017-10-01

    Gene Ontology (GO) analysis is a powerful tool in systems biology, which uses a defined nomenclature to annotate genes/proteins within three categories: "Molecular Function," "Biological Process," and "Cellular Component." GO analysis can assist in revealing functional mechanisms underlying observed patterns in transcriptomic, genomic, and proteomic data. The already extensive and increasing use of zebrafish for modeling genetic and other diseases highlights the need to develop a GO analytical tool for this organism. The web tool Comparative GO was originally developed for GO analysis of bacterial data in 2013 ( www.comparativego.com ). We have now upgraded and elaborated this web tool for analysis of zebrafish genetic data using GOs and annotations from the Gene Ontology Consortium.

  4. Exploring autophagy with Gene Ontology

    Science.gov (United States)

    2018-01-01

    ABSTRACT Autophagy is a fundamental cellular process that is well conserved among eukaryotes. It is one of the strategies that cells use to catabolize substances in a controlled way. Autophagy is used for recycling cellular components, responding to cellular stresses and ridding cells of foreign material. Perturbations in autophagy have been implicated in a number of pathological conditions such as neurodegeneration, cardiac disease and cancer. The growing knowledge about autophagic mechanisms needs to be collected in a computable and shareable format to allow its use in data representation and interpretation. The Gene Ontology (GO) is a freely available resource that describes how and where gene products function in biological systems. It consists of 3 interrelated structured vocabularies that outline what gene products do at the biochemical level, where they act in a cell and the overall biological objectives to which their actions contribute. It also consists of ‘annotations’ that associate gene products with the terms. Here we describe how we represent autophagy in GO, how we create and define terms relevant to autophagy researchers and how we interrelate those terms to generate a coherent view of the process, therefore allowing an interoperable description of its biological aspects. We also describe how annotation of gene products with GO terms improves data analysis and interpretation, hence bringing a significant benefit to this field of study. PMID:29455577

  5. Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology.

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    Lovering, Ruth C; Roncaglia, Paola; Howe, Douglas G; Laulederkind, Stanley J F; Khodiyar, Varsha K; Berardini, Tanya Z; Tweedie, Susan; Foulger, Rebecca E; Osumi-Sutherland, David; Campbell, Nancy H; Huntley, Rachael P; Talmud, Philippa J; Blake, Judith A; Breckenridge, Ross; Riley, Paul R; Lambiase, Pier D; Elliott, Perry M; Clapp, Lucie; Tinker, Andrew; Hill, David P

    2018-02-01

    A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products. In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci. We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects. © 2018 The Authors.

  6. Defining functional distances over Gene Ontology

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    del Pozo Angela

    2008-01-01

    Full Text Available Abstract Background A fundamental problem when trying to define the functional relationships between proteins is the difficulty in quantifying functional similarities, even when well-structured ontologies exist regarding the activity of proteins (i.e. 'gene ontology' -GO-. However, functional metrics can overcome the problems in the comparing and evaluating functional assignments and predictions. As a reference of proximity, previous approaches to compare GO terms considered linkage in terms of ontology weighted by a probability distribution that balances the non-uniform 'richness' of different parts of the Direct Acyclic Graph. Here, we have followed a different approach to quantify functional similarities between GO terms. Results We propose a new method to derive 'functional distances' between GO terms that is based on the simultaneous occurrence of terms in the same set of Interpro entries, instead of relying on the structure of the GO. The coincidence of GO terms reveals natural biological links between the GO functions and defines a distance model Df which fulfils the properties of a Metric Space. The distances obtained in this way can be represented as a hierarchical 'Functional Tree'. Conclusion The method proposed provides a new definition of distance that enables the similarity between GO terms to be quantified. Additionally, the 'Functional Tree' defines groups with biological meaning enhancing its utility for protein function comparison and prediction. Finally, this approach could be for function-based protein searches in databases, and for analysing the gene clusters produced by DNA array experiments.

  7. The Gene Ontology (GO) Cellular Component Ontology: integration with SAO (Subcellular Anatomy Ontology) and other recent developments

    Science.gov (United States)

    2013-01-01

    Background The Gene Ontology (GO) (http://www.geneontology.org/) contains a set of terms for describing the activity and actions of gene products across all kingdoms of life. Each of these activities is executed in a location within a cell or in the vicinity of a cell. In order to capture this context, the GO includes a sub-ontology called the Cellular Component (CC) ontology (GO-CCO). The primary use of this ontology is for GO annotation, but it has also been used for phenotype annotation, and for the annotation of images. Another ontology with similar scope to the GO-CCO is the Subcellular Anatomy Ontology (SAO), part of the Neuroscience Information Framework Standard (NIFSTD) suite of ontologies. The SAO also covers cell components, but in the domain of neuroscience. Description Recently, the GO-CCO was enriched in content and links to the Biological Process and Molecular Function branches of GO as well as to other ontologies. This was achieved in several ways. We carried out an amalgamation of SAO terms with GO-CCO ones; as a result, nearly 100 new neuroscience-related terms were added to the GO. The GO-CCO also contains relationships to GO Biological Process and Molecular Function terms, as well as connecting to external ontologies such as the Cell Ontology (CL). Terms representing protein complexes in the Protein Ontology (PRO) reference GO-CCO terms for their species-generic counterparts. GO-CCO terms can also be used to search a variety of databases. Conclusions In this publication we provide an overview of the GO-CCO, its overall design, and some recent extensions that make use of additional spatial information. One of the most recent developments of the GO-CCO was the merging in of the SAO, resulting in a single unified ontology designed to serve the needs of GO annotators as well as the specific needs of the neuroscience community. PMID:24093723

  8. The representation of heart development in the gene ontology.

    Science.gov (United States)

    Khodiyar, Varsha K; Hill, David P; Howe, Doug; Berardini, Tanya Z; Tweedie, Susan; Talmud, Philippa J; Breckenridge, Ross; Bhattarcharya, Shoumo; Riley, Paul; Scambler, Peter; Lovering, Ruth C

    2011-06-01

    An understanding of heart development is critical in any systems biology approach to cardiovascular disease. The interpretation of data generated from high-throughput technologies (such as microarray and proteomics) is also essential to this approach. However, characterizing the role of genes in the processes underlying heart development and cardiovascular disease involves the non-trivial task of data analysis and integration of previous knowledge. The Gene Ontology (GO) Consortium provides structured controlled biological vocabularies that are used to summarize previous functional knowledge for gene products across all species. One aspect of GO describes biological processes, such as development and signaling. In order to support high-throughput cardiovascular research, we have initiated an effort to fully describe heart development in GO; expanding the number of GO terms describing heart development from 12 to over 280. This new ontology describes heart morphogenesis, the differentiation of specific cardiac cell types, and the involvement of signaling pathways in heart development. This work also aligns GO with the current views of the heart development research community and its representation in the literature. This extension of GO allows gene product annotators to comprehensively capture the genetic program leading to the developmental progression of the heart. This will enable users to integrate heart development data across species, resulting in the comprehensive retrieval of information about this subject. The revised GO structure, combined with gene product annotations, should improve the interpretation of data from high-throughput methods in a variety of cardiovascular research areas, including heart development, congenital cardiac disease, and cardiac stem cell research. Additionally, we invite the heart development community to contribute to the expansion of this important dataset for the benefit of future research in this area. Copyright © 2011

  9. The Representation of Heart Development in the Gene Ontology

    Science.gov (United States)

    Khodiyar, Varsha K.; Hill, David P.; Howe, Doug; Berardini, Tanya Z.; Tweedie, Susan; Talmud, Philippa J.; Breckenridge, Ross; Bhattarcharya, Shoumo; Riley, Paul; Scambler, Peter; Lovering, Ruth C.

    2012-01-01

    An understanding of heart development is critical in any systems biology approach to cardiovascular disease. The interpretation of data generated from high-throughput technologies (such as microarray and proteomics) is also essential to this approach. However, characterizing the role of genes in the processes underlying heart development and cardiovascular disease involves the non-trivial task of data analysis and integration of previous knowledge. The Gene Ontology (GO) Consortium provides structured controlled biological vocabularies that are used to summarize previous functional knowledge for gene products across all species. One aspect of GO describes biological processes, such as development and signaling. In order to support high-throughput cardiovascular research, we have initiated an effort to fully describe heart development in GO; expanding the number of GO terms describing heart development from 12 to over 280. This new ontology describes heart morphogenesis, the differentiation of specific cardiac cell types, and the involvement of signaling pathways in heart development and aligns GO with the current views of the heart development research community and its representation in the literature. This extension of GO allows gene product annotators to comprehensively capture the genetic program leading to the developmental progression of the heart. This will enable users to integrate heart development data across species, resulting in the comprehensive retrieval of information about this subject. The revised GO structure, combined with gene product annotations, should improve the interpretation of data from high-throughput methods in a variety of cardiovascular research areas, including heart development, congenital cardiac disease, and cardiac stem cell research. Additionally, we invite the heart development community to contribute to the expansion of this important dataset for the benefit of future research in this area. PMID:21419760

  10. Gene function prediction based on Gene Ontology Hierarchy Preserving Hashing.

    Science.gov (United States)

    Zhao, Yingwen; Fu, Guangyuan; Wang, Jun; Guo, Maozu; Yu, Guoxian

    2018-02-23

    Gene Ontology (GO) uses structured vocabularies (or terms) to describe the molecular functions, biological roles, and cellular locations of gene products in a hierarchical ontology. GO annotations associate genes with GO terms and indicate the given gene products carrying out the biological functions described by the relevant terms. However, predicting correct GO annotations for genes from a massive set of GO terms as defined by GO is a difficult challenge. To combat with this challenge, we introduce a Gene Ontology Hierarchy Preserving Hashing (HPHash) based semantic method for gene function prediction. HPHash firstly measures the taxonomic similarity between GO terms. It then uses a hierarchy preserving hashing technique to keep the hierarchical order between GO terms, and to optimize a series of hashing functions to encode massive GO terms via compact binary codes. After that, HPHash utilizes these hashing functions to project the gene-term association matrix into a low-dimensional one and performs semantic similarity based gene function prediction in the low-dimensional space. Experimental results on three model species (Homo sapiens, Mus musculus and Rattus norvegicus) for interspecies gene function prediction show that HPHash performs better than other related approaches and it is robust to the number of hash functions. In addition, we also take HPHash as a plugin for BLAST based gene function prediction. From the experimental results, HPHash again significantly improves the prediction performance. The codes of HPHash are available at: http://mlda.swu.edu.cn/codes.php?name=HPHash. Copyright © 2018 Elsevier Inc. All rights reserved.

  11. Extracting Cross-Ontology Weighted Association Rules from Gene Ontology Annotations.

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    Agapito, Giuseppe; Milano, Marianna; Guzzi, Pietro Hiram; Cannataro, Mario

    2016-01-01

    Gene Ontology (GO) is a structured repository of concepts (GO Terms) that are associated to one or more gene products through a process referred to as annotation. The analysis of annotated data is an important opportunity for bioinformatics. There are different approaches of analysis, among those, the use of association rules (AR) which provides useful knowledge, discovering biologically relevant associations between terms of GO, not previously known. In a previous work, we introduced GO-WAR (Gene Ontology-based Weighted Association Rules), a methodology for extracting weighted association rules from ontology-based annotated datasets. We here adapt the GO-WAR algorithm to mine cross-ontology association rules, i.e., rules that involve GO terms present in the three sub-ontologies of GO. We conduct a deep performance evaluation of GO-WAR by mining publicly available GO annotated datasets, showing how GO-WAR outperforms current state of the art approaches.

  12. Approaching the axiomatic enrichment of the Gene Ontology from a lexical perspective.

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    Quesada-Martínez, Manuel; Mikroyannidi, Eleni; Fernández-Breis, Jesualdo Tomás; Stevens, Robert

    2015-09-01

    The main goal of this work is to measure how lexical regularities in biomedical ontology labels can be used for the automatic creation of formal relationships between classes, and to evaluate the results of applying our approach to the Gene Ontology (GO). In recent years, we have developed a method for the lexical analysis of regularities in biomedical ontology labels, and we showed that the labels can present a high degree of regularity. In this work, we extend our method with a cross-products extension (CPE) metric, which estimates the potential interest of a specific regularity for axiomatic enrichment in the lexical analysis, using information on exact matches in external ontologies. The GO consortium recently enriched the GO by using so-called cross-product extensions. Cross-products are generated by establishing axioms that relate a given GO class with classes from the GO or other biomedical ontologies. We apply our method to the GO and study how its lexical analysis can identify and reconstruct the cross-products that are defined by the GO consortium. The label of the classes of the GO are highly regular in lexical terms, and the exact matches with labels of external ontologies affect 80% of the GO classes. The CPE metric reveals that 31.48% of the classes that exhibit regularities have fragments that are classes into two external ontologies that are selected for our experiment, namely, the Cell Ontology and the Chemical Entities of Biological Interest ontology, and 18.90% of them are fully decomposable into smaller parts. Our results show that the CPE metric permits our method to detect GO cross-product extensions with a mean recall of 62% and a mean precision of 28%. The study is completed with an analysis of false positives to explain this precision value. We think that our results support the claim that our lexical approach can contribute to the axiomatic enrichment of biomedical ontologies and that it can provide new insights into the engineering of

  13. Muscle Research and Gene Ontology: New standards for improved data integration.

    Science.gov (United States)

    Feltrin, Erika; Campanaro, Stefano; Diehl, Alexander D; Ehler, Elisabeth; Faulkner, Georgine; Fordham, Jennifer; Gardin, Chiara; Harris, Midori; Hill, David; Knoell, Ralph; Laveder, Paolo; Mittempergher, Lorenza; Nori, Alessandra; Reggiani, Carlo; Sorrentino, Vincenzo; Volpe, Pompeo; Zara, Ivano; Valle, Giorgio; Deegan, Jennifer

    2009-01-29

    The Gene Ontology Project provides structured controlled vocabularies for molecular biology that can be used for the functional annotation of genes and gene products. In a collaboration between the Gene Ontology (GO) Consortium and the muscle biology community, we have made large-scale additions to the GO biological process and cellular component ontologies. The main focus of this ontology development work concerns skeletal muscle, with specific consideration given to the processes of muscle contraction, plasticity, development, and regeneration, and to the sarcomere and membrane-delimited compartments. Our aims were to update the existing structure to reflect current knowledge, and to resolve, in an accommodating manner, the ambiguity in the language used by the community. The updated muscle terminologies have been incorporated into the GO. There are now 159 new terms covering critical research areas, and 57 existing terms have been improved and reorganized to follow their usage in muscle literature. The revised GO structure should improve the interpretation of data from high-throughput (e.g. microarray and proteomic) experiments in the area of muscle science and muscle disease. We actively encourage community feedback on, and gene product annotation with these new terms. Please visit the Muscle Community Annotation Wiki http://wiki.geneontology.org/index.php/Muscle_Biology.

  14. Muscle Research and Gene Ontology: New standards for improved data integration

    Directory of Open Access Journals (Sweden)

    Nori Alessandra

    2009-01-01

    Full Text Available Abstract Background The Gene Ontology Project provides structured controlled vocabularies for molecular biology that can be used for the functional annotation of genes and gene products. In a collaboration between the Gene Ontology (GO Consortium and the muscle biology community, we have made large-scale additions to the GO biological process and cellular component ontologies. The main focus of this ontology development work concerns skeletal muscle, with specific consideration given to the processes of muscle contraction, plasticity, development, and regeneration, and to the sarcomere and membrane-delimited compartments. Our aims were to update the existing structure to reflect current knowledge, and to resolve, in an accommodating manner, the ambiguity in the language used by the community. Results The updated muscle terminologies have been incorporated into the GO. There are now 159 new terms covering critical research areas, and 57 existing terms have been improved and reorganized to follow their usage in muscle literature. Conclusion The revised GO structure should improve the interpretation of data from high-throughput (e.g. microarray and proteomic experiments in the area of muscle science and muscle disease. We actively encourage community feedback on, and gene product annotation with these new terms. Please visit the Muscle Community Annotation Wiki http://wiki.geneontology.org/index.php/Muscle_Biology.

  15. Fast gene ontology based clustering for microarray experiments.

    Science.gov (United States)

    Ovaska, Kristian; Laakso, Marko; Hautaniemi, Sampsa

    2008-11-21

    Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

  16. Integrating Ontological Knowledge and Textual Evidence in Estimating Gene and Gene Product Similarity

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Posse, Christian; Gopalan, Banu; Tratz, Stephen C.; Gregory, Michelle L.

    2006-06-08

    With the rising influence of the Gene On-tology, new approaches have emerged where the similarity between genes or gene products is obtained by comparing Gene Ontology code annotations associ-ated with them. So far, these approaches have solely relied on the knowledge en-coded in the Gene Ontology and the gene annotations associated with the Gene On-tology database. The goal of this paper is to demonstrate that improvements to these approaches can be obtained by integrating textual evidence extracted from relevant biomedical literature.

  17. Bayesian assignment of gene ontology terms to gene expression experiments.

    Science.gov (United States)

    Sykacek, P

    2012-09-15

    Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Source code under GPL license is available from the author. peter.sykacek@boku.ac.at.

  18. Bayesian assignment of gene ontology terms to gene expression experiments

    Science.gov (United States)

    Sykacek, P.

    2012-01-01

    Motivation: Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. Results: This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Availability: Source code under GPL license is available from the author. Contact: peter.sykacek@boku.ac.at PMID:22962488

  19. Fast Gene Ontology based clustering for microarray experiments

    Directory of Open Access Journals (Sweden)

    Ovaska Kristian

    2008-11-01

    Full Text Available Abstract Background Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. Results We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Conclusion Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

  20. Prediction of human protein function according to Gene Ontology categories

    DEFF Research Database (Denmark)

    Jensen, Lars Juhl; Gupta, Ramneek; Stærfeldt, Hans Henrik

    2003-01-01

    developed a method for prediction of protein function for a subset of classes from the Gene Ontology classification scheme. This subset includes several pharmaceutically interesting categories-transcription factors, receptors, ion channels, stress and immune response proteins, hormones and growth factors...

  1. Dovetailing biology and chemistry: integrating the Gene Ontology with the ChEBI chemical ontology

    Science.gov (United States)

    2013-01-01

    Background The Gene Ontology (GO) facilitates the description of the action of gene products in a biological context. Many GO terms refer to chemical entities that participate in biological processes. To facilitate accurate and consistent systems-wide biological representation, it is necessary to integrate the chemical view of these entities with the biological view of GO functions and processes. We describe a collaborative effort between the GO and the Chemical Entities of Biological Interest (ChEBI) ontology developers to ensure that the representation of chemicals in the GO is both internally consistent and in alignment with the chemical expertise captured in ChEBI. Results We have examined and integrated the ChEBI structural hierarchy into the GO resource through computationally-assisted manual curation of both GO and ChEBI. Our work has resulted in the creation of computable definitions of GO terms that contain fully defined semantic relationships to corresponding chemical terms in ChEBI. Conclusions The set of logical definitions using both the GO and ChEBI has already been used to automate aspects of GO development and has the potential to allow the integration of data across the domains of biology and chemistry. These logical definitions are available as an extended version of the ontology from http://purl.obolibrary.org/obo/go/extensions/go-plus.owl. PMID:23895341

  2. Classifying genes to the correct Gene Ontology Slim term in Saccharomyces cerevisiae using neighbouring genes with classification learning

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    Tsatsoulis Costas

    2010-05-01

    Full Text Available Abstract Background There is increasing evidence that gene location and surrounding genes influence the functionality of genes in the eukaryotic genome. Knowing the Gene Ontology Slim terms associated with a gene gives us insight into a gene's functionality by informing us how its gene product behaves in a cellular context using three different ontologies: molecular function, biological process, and cellular component. In this study, we analyzed if we could classify a gene in Saccharomyces cerevisiae to its correct Gene Ontology Slim term using information about its location in the genome and information from its nearest-neighbouring genes using classification learning. Results We performed experiments to establish that the MultiBoostAB algorithm using the J48 classifier could correctly classify Gene Ontology Slim terms of a gene given information regarding the gene's location and information from its nearest-neighbouring genes for training. Different neighbourhood sizes were examined to determine how many nearest neighbours should be included around each gene to provide better classification rules. Our results show that by just incorporating neighbour information from each gene's two-nearest neighbours, the percentage of correctly classified genes to their correct Gene Ontology Slim term for each ontology reaches over 80% with high accuracy (reflected in F-measures over 0.80 of the classification rules produced. Conclusions We confirmed that in classifying genes to their correct Gene Ontology Slim term, the inclusion of neighbour information from those genes is beneficial. Knowing the location of a gene and the Gene Ontology Slim information from neighbouring genes gives us insight into that gene's functionality. This benefit is seen by just including information from a gene's two-nearest neighbouring genes.

  3. Protein Annotation from Protein Interaction Networks and Gene Ontology

    OpenAIRE

    Nguyen, Cao D.; Gardiner, Katheleen J.; Cios, Krzysztof J.

    2011-01-01

    We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precis...

  4. [Key effect genes responding to nerve injury identified by gene ontology and computer pattern recognition].

    Science.gov (United States)

    Pan, Qian; Peng, Jin; Zhou, Xue; Yang, Hao; Zhang, Wei

    2012-07-01

    In order to screen out important genes from large gene data of gene microarray after nerve injury, we combine gene ontology (GO) method and computer pattern recognition technology to find key genes responding to nerve injury, and then verify one of these screened-out genes. Data mining and gene ontology analysis of gene chip data GSE26350 was carried out through MATLAB software. Cd44 was selected from screened-out key gene molecular spectrum by comparing genes' different GO terms and positions on score map of principal component. Function interferences were employed to influence the normal binding of Cd44 and one of its ligands, chondroitin sulfate C (CSC), to observe neurite extension. Gene ontology analysis showed that the first genes on score map (marked by red *) mainly distributed in molecular transducer activity, receptor activity, protein binding et al molecular function GO terms. Cd44 is one of six effector protein genes, and attracted us with its function diversity. After adding different reagents into the medium to interfere the normal binding of CSC and Cd44, varying-degree remissions of CSC's inhibition on neurite extension were observed. CSC can inhibit neurite extension through binding Cd44 on the neuron membrane. This verifies that important genes in given physiological processes can be identified by gene ontology analysis of gene chip data.

  5. GOseek: a gene ontology search engine using enhanced keywords.

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    Taha, Kamal

    2013-01-01

    We propose in this paper a biological search engine called GOseek, which overcomes the limitation of current gene similarity tools. Given a set of genes, GOseek returns the most significant genes that are semantically related to the given genes. These returned genes are usually annotated to one of the Lowest Common Ancestors (LCA) of the Gene Ontology (GO) terms annotating the given genes. Most genes have several annotation GO terms. Therefore, there may be more than one LCA for the GO terms annotating the given genes. The LCA annotating the genes that are most semantically related to the given gene is the one that receives the most aggregate semantic contribution from the GO terms annotating the given genes. To identify this LCA, GOseek quantifies the contribution of the GO terms annotating the given genes to the semantics of their LCAs. That is, it encodes the semantic contribution into a numeric format. GOseek uses microarray experiment data to rank result genes based on their significance. We evaluated GOseek experimentally and compared it with a comparable gene prediction tool. Results showed marked improvement over the tool.

  6. Comparative GO: a web application for comparative gene ontology and gene ontology-based gene selection in bacteria.

    Directory of Open Access Journals (Sweden)

    Mario Fruzangohar

    Full Text Available The primary means of classifying new functions for genes and proteins relies on Gene Ontology (GO, which defines genes/proteins using a controlled vocabulary in terms of their Molecular Function, Biological Process and Cellular Component. The challenge is to present this information to researchers to compare and discover patterns in multiple datasets using visually comprehensible and user-friendly statistical reports. Importantly, while there are many GO resources available for eukaryotes, there are none suitable for simultaneous, graphical and statistical comparison between multiple datasets. In addition, none of them supports comprehensive resources for bacteria. By using Streptococcus pneumoniae as a model, we identified and collected GO resources including genes, proteins, taxonomy and GO relationships from NCBI, UniProt and GO organisations. Then, we designed database tables in PostgreSQL database server and developed a Java application to extract data from source files and loaded into database automatically. We developed a PHP web application based on Model-View-Control architecture, used a specific data structure as well as current and novel algorithms to estimate GO graphs parameters. We designed different navigation and visualization methods on the graphs and integrated these into graphical reports. This tool is particularly significant when comparing GO groups between multiple samples (including those of pathogenic bacteria from different sources simultaneously. Comparing GO protein distribution among up- or down-regulated genes from different samples can improve understanding of biological pathways, and mechanism(s of infection. It can also aid in the discovery of genes associated with specific function(s for investigation as a novel vaccine or therapeutic targets.http://turing.ersa.edu.au/BacteriaGO.

  7. Gene ontology based transfer learning for protein subcellular localization

    Directory of Open Access Journals (Sweden)

    Zhou Shuigeng

    2011-02-01

    Full Text Available Abstract Background Prediction of protein subcellular localization generally involves many complex factors, and using only one or two aspects of data information may not tell the true story. For this reason, some recent predictive models are deliberately designed to integrate multiple heterogeneous data sources for exploiting multi-aspect protein feature information. Gene ontology, hereinafter referred to as GO, uses a controlled vocabulary to depict biological molecules or gene products in terms of biological process, molecular function and cellular component. With the rapid expansion of annotated protein sequences, gene ontology has become a general protein feature that can be used to construct predictive models in computational biology. Existing models generally either concatenated the GO terms into a flat binary vector or applied majority-vote based ensemble learning for protein subcellular localization, both of which can not estimate the individual discriminative abilities of the three aspects of gene ontology. Results In this paper, we propose a Gene Ontology Based Transfer Learning Model (GO-TLM for large-scale protein subcellular localization. The model transfers the signature-based homologous GO terms to the target proteins, and further constructs a reliable learning system to reduce the adverse affect of the potential false GO terms that are resulted from evolutionary divergence. We derive three GO kernels from the three aspects of gene ontology to measure the GO similarity of two proteins, and derive two other spectrum kernels to measure the similarity of two protein sequences. We use simple non-parametric cross validation to explicitly weigh the discriminative abilities of the five kernels, such that the time & space computational complexities are greatly reduced when compared to the complicated semi-definite programming and semi-indefinite linear programming. The five kernels are then linearly merged into one single kernel for

  8. Correlating Information Contents of Gene Ontology Terms to Infer Semantic Similarity of Gene Products

    Directory of Open Access Journals (Sweden)

    Mingxin Gan

    2014-01-01

    Full Text Available Successful applications of the gene ontology to the inference of functional relationships between gene products in recent years have raised the need for computational methods to automatically calculate semantic similarity between gene products based on semantic similarity of gene ontology terms. Nevertheless, existing methods, though having been widely used in a variety of applications, may significantly overestimate semantic similarity between genes that are actually not functionally related, thereby yielding misleading results in applications. To overcome this limitation, we propose to represent a gene product as a vector that is composed of information contents of gene ontology terms annotated for the gene product, and we suggest calculating similarity between two gene products as the relatedness of their corresponding vectors using three measures: Pearson’s correlation coefficient, cosine similarity, and the Jaccard index. We focus on the biological process domain of the gene ontology and annotations of yeast proteins to study the effectiveness of the proposed measures. Results show that semantic similarity scores calculated using the proposed measures are more consistent with known biological knowledge than those derived using a list of existing methods, suggesting the effectiveness of our method in characterizing functional relationships between gene products.

  9. Protein annotation from protein interaction networks and Gene Ontology.

    Science.gov (United States)

    Nguyen, Cao D; Gardiner, Katheleen J; Cios, Krzysztof J

    2011-10-01

    We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precision and 60% recall versus 45% and 26% for Majority and 24% and 61% for χ²-statistics, respectively. Copyright © 2011 Elsevier Inc. All rights reserved.

  10. Text Mining to Support Gene Ontology Curation and Vice Versa.

    Science.gov (United States)

    Ruch, Patrick

    2017-01-01

    In this chapter, we explain how text mining can support the curation of molecular biology databases dealing with protein functions. We also show how curated data can play a disruptive role in the developments of text mining methods. We review a decade of efforts to improve the automatic assignment of Gene Ontology (GO) descriptors, the reference ontology for the characterization of genes and gene products. To illustrate the high potential of this approach, we compare the performances of an automatic text categorizer and show a large improvement of +225 % in both precision and recall on benchmarked data. We argue that automatic text categorization functions can ultimately be embedded into a Question-Answering (QA) system to answer questions related to protein functions. Because GO descriptors can be relatively long and specific, traditional QA systems cannot answer such questions. A new type of QA system, so-called Deep QA which uses machine learning methods trained with curated contents, is thus emerging. Finally, future advances of text mining instruments are directly dependent on the availability of high-quality annotated contents at every curation step. Databases workflows must start recording explicitly all the data they curate and ideally also some of the data they do not curate.

  11. Determining the semantic similarities among Gene Ontology terms.

    Science.gov (United States)

    Taha, Kamal

    2013-05-01

    We present in this paper novel techniques that determine the semantic relationships among GeneOntology (GO) terms. We implemented these techniques in a prototype system called GoSE, which resides between user application and GO database. Given a set S of GO terms, GoSE would return another set S' of GO terms, where each term in S' is semantically related to each term in S. Most current research is focused on determining the semantic similarities among GO ontology terms based solely on their IDs and proximity to one another in the GO graph structure, while overlooking the contexts of the terms, which may lead to erroneous results. The context of a GO term T is the set of other terms, whose existence in the GO graph structure is dependent on T. We propose novel techniques that determine the contexts of terms based on the concept of existence dependency. We present a stack-based sort-merge algorithm employing these techniques for determining the semantic similarities among GO terms.We evaluated GoSE experimentally and compared it with three existing methods. The results of measuring the semantic similarities among genes in KEGG and Pfam pathways retrieved from the DBGET and Sanger Pfam databases, respectively, have shown that our method outperforms the other three methods in recall and precision.

  12. GOPET: A tool for automated predictions of Gene Ontology terms

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    Glatting Karl-Heinz

    2006-03-01

    Full Text Available Abstract Background Vast progress in sequencing projects has called for annotation on a large scale. A Number of methods have been developed to address this challenging task. These methods, however, either apply to specific subsets, or their predictions are not formalised, or they do not provide precise confidence values for their predictions. Description We recently established a learning system for automated annotation, trained with a broad variety of different organisms to predict the standardised annotation terms from Gene Ontology (GO. Now, this method has been made available to the public via our web-service GOPET (Gene Ontology term Prediction and Evaluation Tool. It supplies annotation for sequences of any organism. For each predicted term an appropriate confidence value is provided. The basic method had been developed for predicting molecular function GO-terms. It is now expanded to predict biological process terms. This web service is available via http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar Conclusion Our web service gives experimental researchers as well as the bioinformatics community a valuable sequence annotation device. Additionally, GOPET also provides less significant annotation data which may serve as an extended discovery platform for the user.

  13. Interestingness measures and strategies for mining multi-ontology multi-level association rules from gene ontology annotations for the discovery of new GO relationships.

    Science.gov (United States)

    Manda, Prashanti; McCarthy, Fiona; Bridges, Susan M

    2013-10-01

    The Gene Ontology (GO), a set of three sub-ontologies, is one of the most popular bio-ontologies used for describing gene product characteristics. GO annotation data containing terms from multiple sub-ontologies and at different levels in the ontologies is an important source of implicit relationships between terms from the three sub-ontologies. Data mining techniques such as association rule mining that are tailored to mine from multiple ontologies at multiple levels of abstraction are required for effective knowledge discovery from GO annotation data. We present a data mining approach, Multi-ontology data mining at All Levels (MOAL) that uses the structure and relationships of the GO to mine multi-ontology multi-level association rules. We introduce two interestingness measures: Multi-ontology Support (MOSupport) and Multi-ontology Confidence (MOConfidence) customized to evaluate multi-ontology multi-level association rules. We also describe a variety of post-processing strategies for pruning uninteresting rules. We use publicly available GO annotation data to demonstrate our methods with respect to two applications (1) the discovery of co-annotation suggestions and (2) the discovery of new cross-ontology relationships. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

  14. Codon bias and gene ontology in holometabolous and hemimetabolous insects.

    Science.gov (United States)

    Carlini, David B; Makowski, Matthew

    2015-12-01

    The relationship between preferred codon use (PCU), developmental mode, and gene ontology (GO) was investigated in a sample of nine insect species with sequenced genomes. These species were selected to represent two distinct modes of insect development, holometabolism and hemimetabolism, with an aim toward determining whether the differences in developmental timing concomitant with developmental mode would be mirrored by differences in PCU in their developmental genes. We hypothesized that the developmental genes of holometabolous insects should be under greater selective pressure for efficient translation, manifest as increased PCU, than those of hemimetabolous insects because holometabolism requires abundant protein expression over shorter time intervals than hemimetabolism, where proteins are required more uniformly in time. Preferred codon sets were defined for each species, from which the frequency of PCU for each gene was obtained. Although there were substantial differences in the genomic base composition of holometabolous and hemimetabolous insects, both groups exhibited a general preference for GC-ending codons, with the former group having higher PCU averaged across all genes. For each species, the biological process GO term for each gene was assigned that of its Drosophila homolog(s), and PCU was calculated for each GO term category. The top two GO term categories for PCU enrichment in the holometabolous insects were anatomical structure development and cell differentiation. The increased PCU in the developmental genes of holometabolous insects may reflect a general strategy to maximize the protein production of genes expressed in bursts over short time periods, e.g., heat shock proteins. J. Exp. Zool. (Mol. Dev. Evol.) 324B: 686-698, 2015. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  15. Networks in biological systems: An investigation of the Gene Ontology as an evolving network

    International Nuclear Information System (INIS)

    Coronnello, C; Tumminello, M; Micciche, S; Mantegna, R.N.

    2009-01-01

    Many biological systems can be described as networks where different elements interact, in order to perform biological processes. We introduce a network associated with the Gene Ontology. Specifically, we construct a correlation-based network where the vertices are the terms of the Gene Ontology and the link between each two terms is weighted on the basis of the number of genes that they have in common. We analyze a filtered network obtained from the correlation-based network and we characterize its evolution over different releases of the Gene Ontology.

  16. Representing virus-host interactions and other multi-organism processes in the Gene Ontology.

    Science.gov (United States)

    Foulger, R E; Osumi-Sutherland, D; McIntosh, B K; Hulo, C; Masson, P; Poux, S; Le Mercier, P; Lomax, J

    2015-07-28

    The Gene Ontology project is a collaborative effort to provide descriptions of gene products in a consistent and computable language, and in a species-independent manner. The Gene Ontology is designed to be applicable to all organisms but up to now has been largely under-utilized for prokaryotes and viruses, in part because of a lack of appropriate ontology terms. To address this issue, we have developed a set of Gene Ontology classes that are applicable to microbes and their hosts, improving both coverage and quality in this area of the Gene Ontology. Describing microbial and viral gene products brings with it the additional challenge of capturing both the host and the microbe. Recognising this, we have worked closely with annotation groups to test and optimize the GO classes, and we describe here a set of annotation guidelines that allow the controlled description of two interacting organisms. Building on the microbial resources already in existence such as ViralZone, UniProtKB keywords and MeGO, this project provides an integrated ontology to describe interactions between microbial species and their hosts, with mappings to the external resources above. Housing this information within the freely-accessible Gene Ontology project allows the classes and annotation structure to be utilized by a large community of biologists and users.

  17. OAHG: an integrated resource for annotating human genes with multi-level ontologies.

    Science.gov (United States)

    Cheng, Liang; Sun, Jie; Xu, Wanying; Dong, Lixiang; Hu, Yang; Zhou, Meng

    2016-10-05

    OAHG, an integrated resource, aims to establish a comprehensive functional annotation resource for human protein-coding genes (PCGs), miRNAs, and lncRNAs by multi-level ontologies involving Gene Ontology (GO), Disease Ontology (DO), and Human Phenotype Ontology (HPO). Many previous studies have focused on inferring putative properties and biological functions of PCGs and non-coding RNA genes from different perspectives. During the past several decades, a few of databases have been designed to annotate the functions of PCGs, miRNAs, and lncRNAs, respectively. A part of functional descriptions in these databases were mapped to standardize terminologies, such as GO, which could be helpful to do further analysis. Despite these developments, there is no comprehensive resource recording the function of these three important types of genes. The current version of OAHG, release 1.0 (Jun 2016), integrates three ontologies involving GO, DO, and HPO, six gene functional databases and two interaction databases. Currently, OAHG contains 1,434,694 entries involving 16,929 PCGs, 637 miRNAs, 193 lncRNAs, and 24,894 terms of ontologies. During the performance evaluation, OAHG shows the consistencies with existing gene interactions and the structure of ontology. For example, terms with more similar structure could be associated with more associated genes (Pearson correlation γ 2  = 0.2428, p < 2.2e-16).

  18. Gene Ontology annotation of the rice blast fungus, Magnaporthe oryzae

    Directory of Open Access Journals (Sweden)

    Deng Jixin

    2009-02-01

    Full Text Available Abstract Background Magnaporthe oryzae, the causal agent of blast disease of rice, is the most destructive disease of rice worldwide. The genome of this fungal pathogen has been sequenced and an automated annotation has recently been updated to Version 6 http://www.broad.mit.edu/annotation/genome/magnaporthe_grisea/MultiDownloads.html. However, a comprehensive manual curation remains to be performed. Gene Ontology (GO annotation is a valuable means of assigning functional information using standardized vocabulary. We report an overview of the GO annotation for Version 5 of M. oryzae genome assembly. Methods A similarity-based (i.e., computational GO annotation with manual review was conducted, which was then integrated with a literature-based GO annotation with computational assistance. For similarity-based GO annotation a stringent reciprocal best hits method was used to identify similarity between predicted proteins of M. oryzae and GO proteins from multiple organisms with published associations to GO terms. Significant alignment pairs were manually reviewed. Functional assignments were further cross-validated with manually reviewed data, conserved domains, or data determined by wet lab experiments. Additionally, biological appropriateness of the functional assignments was manually checked. Results In total, 6,286 proteins received GO term assignment via the homology-based annotation, including 2,870 hypothetical proteins. Literature-based experimental evidence, such as microarray, MPSS, T-DNA insertion mutation, or gene knockout mutation, resulted in 2,810 proteins being annotated with GO terms. Of these, 1,673 proteins were annotated with new terms developed for Plant-Associated Microbe Gene Ontology (PAMGO. In addition, 67 experiment-determined secreted proteins were annotated with PAMGO terms. Integration of the two data sets resulted in 7,412 proteins (57% being annotated with 1,957 distinct and specific GO terms. Unannotated proteins

  19. A methodology to migrate the gene ontology to a description logic environment using DAML+OIL.

    Science.gov (United States)

    Wroe, C J; Stevens, R; Goble, C A; Ashburner, M

    2003-01-01

    The Gene Ontology Next Generation Project (GONG) is developing a staged methodology to evolve the current representation of the Gene Ontology into DAML+OIL in order to take advantage of the richer formal expressiveness and the reasoning capabilities of the underlying description logic. Each stage provides a step level increase in formal explicit semantic content with a view to supporting validation, extension and multiple classification of the Gene Ontology. The paper introduces DAML+OIL and demonstrates the activity within each stage of the methodology and the functionality gained.

  20. Evaluating Functional Annotations of Enzymes Using the Gene Ontology.

    Science.gov (United States)

    Holliday, Gemma L; Davidson, Rebecca; Akiva, Eyal; Babbitt, Patricia C

    2017-01-01

    The Gene Ontology (GO) (Ashburner et al., Nat Genet 25(1):25-29, 2000) is a powerful tool in the informatics arsenal of methods for evaluating annotations in a protein dataset. From identifying the nearest well annotated homologue of a protein of interest to predicting where misannotation has occurred to knowing how confident you can be in the annotations assigned to those proteins is critical. In this chapter we explore what makes an enzyme unique and how we can use GO to infer aspects of protein function based on sequence similarity. These can range from identification of misannotation or other errors in a predicted function to accurate function prediction for an enzyme of entirely unknown function. Although GO annotation applies to any gene products, we focus here a describing our approach for hierarchical classification of enzymes in the Structure-Function Linkage Database (SFLD) (Akiva et al., Nucleic Acids Res 42(Database issue):D521-530, 2014) as a guide for informed utilisation of annotation transfer based on GO terms.

  1. Prediction of regulatory gene pairs using dynamic time warping and gene ontology.

    Science.gov (United States)

    Yang, Andy C; Hsu, Hui-Huang; Lu, Ming-Da; Tseng, Vincent S; Shih, Timothy K

    2014-01-01

    Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.

  2. The prediction of candidate genes for cervix related cancer through gene ontology and graph theoretical approach.

    Science.gov (United States)

    Hindumathi, V; Kranthi, T; Rao, S B; Manimaran, P

    2014-06-01

    With rapidly changing technology, prediction of candidate genes has become an indispensable task in recent years mainly in the field of biological research. The empirical methods for candidate gene prioritization that succors to explore the potential pathway between genetic determinants and complex diseases are highly cumbersome and labor intensive. In such a scenario predicting potential targets for a disease state through in silico approaches are of researcher's interest. The prodigious availability of protein interaction data coupled with gene annotation renders an ease in the accurate determination of disease specific candidate genes. In our work we have prioritized the cervix related cancer candidate genes by employing Csaba Ortutay and his co-workers approach of identifying the candidate genes through graph theoretical centrality measures and gene ontology. With the advantage of the human protein interaction data, cervical cancer gene sets and the ontological terms, we were able to predict 15 novel candidates for cervical carcinogenesis. The disease relevance of the anticipated candidate genes was corroborated through a literature survey. Also the presence of the drugs for these candidates was detected through Therapeutic Target Database (TTD) and DrugMap Central (DMC) which affirms that they may be endowed as potential drug targets for cervical cancer.

  3. Multi-label literature classification based on the Gene Ontology graph

    Directory of Open Access Journals (Sweden)

    Lu Xinghua

    2008-12-01

    Full Text Available Abstract Background The Gene Ontology is a controlled vocabulary for representing knowledge related to genes and proteins in a computable form. The current effort of manually annotating proteins with the Gene Ontology is outpaced by the rate of accumulation of biomedical knowledge in literature, which urges the development of text mining approaches to facilitate the process by automatically extracting the Gene Ontology annotation from literature. The task is usually cast as a text classification problem, and contemporary methods are confronted with unbalanced training data and the difficulties associated with multi-label classification. Results In this research, we investigated the methods of enhancing automatic multi-label classification of biomedical literature by utilizing the structure of the Gene Ontology graph. We have studied three graph-based multi-label classification algorithms, including a novel stochastic algorithm and two top-down hierarchical classification methods for multi-label literature classification. We systematically evaluated and compared these graph-based classification algorithms to a conventional flat multi-label algorithm. The results indicate that, through utilizing the information from the structure of the Gene Ontology graph, the graph-based multi-label classification methods can significantly improve predictions of the Gene Ontology terms implied by the analyzed text. Furthermore, the graph-based multi-label classifiers are capable of suggesting Gene Ontology annotations (to curators that are closely related to the true annotations even if they fail to predict the true ones directly. A software package implementing the studied algorithms is available for the research community. Conclusion Through utilizing the information from the structure of the Gene Ontology graph, the graph-based multi-label classification methods have better potential than the conventional flat multi-label classification approach to facilitate

  4. Using the gene ontology to scan multilevel gene sets for associations in genome wide association studies.

    Science.gov (United States)

    Schaid, Daniel J; Sinnwell, Jason P; Jenkins, Gregory D; McDonnell, Shannon K; Ingle, James N; Kubo, Michiaki; Goss, Paul E; Costantino, Joseph P; Wickerham, D Lawrence; Weinshilboum, Richard M

    2012-01-01

    Gene-set analyses have been widely used in gene expression studies, and some of the developed methods have been extended to genome wide association studies (GWAS). Yet, complications due to linkage disequilibrium (LD) among single nucleotide polymorphisms (SNPs), and variable numbers of SNPs per gene and genes per gene-set, have plagued current approaches, often leading to ad hoc "fixes." To overcome some of the current limitations, we developed a general approach to scan GWAS SNP data for both gene-level and gene-set analyses, building on score statistics for generalized linear models, and taking advantage of the directed acyclic graph structure of the gene ontology when creating gene-sets. However, other types of gene-set structures can be used, such as the popular Kyoto Encyclopedia of Genes and Genomes (KEGG). Our approach combines SNPs into genes, and genes into gene-sets, but assures that positive and negative effects of genes on a trait do not cancel. To control for multiple testing of many gene-sets, we use an efficient computational strategy that accounts for LD and provides accurate step-down adjusted P-values for each gene-set. Application of our methods to two different GWAS provide guidance on the potential strengths and weaknesses of our proposed gene-set analyses. © 2011 Wiley Periodicals, Inc.

  5. Protein-Protein Interaction Network and Gene Ontology

    Science.gov (United States)

    Choi, Yunkyu; Kim, Seok; Yi, Gwan-Su; Park, Jinah

    Evolution of computer technologies makes it possible to access a large amount and various kinds of biological data via internet such as DNA sequences, proteomics data and information discovered about them. It is expected that the combination of various data could help researchers find further knowledge about them. Roles of a visualization system are to invoke human abilities to integrate information and to recognize certain patterns in the data. Thus, when the various kinds of data are examined and analyzed manually, an effective visualization system is an essential part. One instance of these integrated visualizations can be combination of protein-protein interaction (PPI) data and Gene Ontology (GO) which could help enhance the analysis of PPI network. We introduce a simple but comprehensive visualization system that integrates GO and PPI data where GO and PPI graphs are visualized side-by-side and supports quick reference functions between them. Furthermore, the proposed system provides several interactive visualization methods for efficiently analyzing the PPI network and GO directedacyclic- graph such as context-based browsing and common ancestors finding.

  6. Gene Ontology and KEGG Enrichment Analyses of Genes Related to Age-Related Macular Degeneration

    Directory of Open Access Journals (Sweden)

    Jian Zhang

    2014-01-01

    Full Text Available Identifying disease genes is one of the most important topics in biomedicine and may facilitate studies on the mechanisms underlying disease. Age-related macular degeneration (AMD is a serious eye disease; it typically affects older adults and results in a loss of vision due to retina damage. In this study, we attempt to develop an effective method for distinguishing AMD-related genes. Gene ontology and KEGG enrichment analyses of known AMD-related genes were performed, and a classification system was established. In detail, each gene was encoded into a vector by extracting enrichment scores of the gene set, including it and its direct neighbors in STRING, and gene ontology terms or KEGG pathways. Then certain feature-selection methods, including minimum redundancy maximum relevance and incremental feature selection, were adopted to extract key features for the classification system. As a result, 720 GO terms and 11 KEGG pathways were deemed the most important factors for predicting AMD-related genes.

  7. Automatic annotation of protein motif function with Gene Ontology terms

    Directory of Open Access Journals (Sweden)

    Gopalakrishnan Vanathi

    2004-09-01

    Full Text Available Abstract Background Conserved protein sequence motifs are short stretches of amino acid sequence patterns that potentially encode the function of proteins. Several sequence pattern searching algorithms and programs exist foridentifying candidate protein motifs at the whole genome level. However, amuch needed and importanttask is to determine the functions of the newly identified protein motifs. The Gene Ontology (GO project is an endeavor to annotate the function of genes or protein sequences with terms from a dynamic, controlled vocabulary and these annotations serve well as a knowledge base. Results This paperpresents methods to mine the GO knowledge base and use the association between the GO terms assigned to a sequence and the motifs matched by the same sequence as evidence for predicting the functions of novel protein motifs automatically. The task of assigning GO terms to protein motifsis viewed as both a binary classification and information retrieval problem, where PROSITE motifs are used as samples for mode training and functional prediction. The mutual information of a motif and aGO term association isfound to be a very useful feature. We take advantageof the known motifs to train a logistic regression classifier, which allows us to combine mutual information with other frequency-based features and obtain a probability of correctassociation. The trained logistic regression model has intuitively meaningful and logically plausible parameter values, and performs very well empirically according to our evaluation criteria. Conclusions In this research, different methods for automatic annotation of protein motifs have been investigated. Empirical result demonstrated that the methods have a great potential for detecting and augmenting information about thefunctions of newly discovered candidate protein motifs.

  8. A robust data-driven approach for gene ontology annotation.

    Science.gov (United States)

    Li, Yanpeng; Yu, Hong

    2014-01-01

    Gene ontology (GO) and GO annotation are important resources for biological information management and knowledge discovery, but the speed of manual annotation became a major bottleneck of database curation. BioCreative IV GO annotation task aims to evaluate the performance of system that automatically assigns GO terms to genes based on the narrative sentences in biomedical literature. This article presents our work in this task as well as the experimental results after the competition. For the evidence sentence extraction subtask, we built a binary classifier to identify evidence sentences using reference distance estimator (RDE), a recently proposed semi-supervised learning method that learns new features from around 10 million unlabeled sentences, achieving an F1 of 19.3% in exact match and 32.5% in relaxed match. In the post-submission experiment, we obtained 22.1% and 35.7% F1 performance by incorporating bigram features in RDE learning. In both development and test sets, RDE-based method achieved over 20% relative improvement on F1 and AUC performance against classical supervised learning methods, e.g. support vector machine and logistic regression. For the GO term prediction subtask, we developed an information retrieval-based method to retrieve the GO term most relevant to each evidence sentence using a ranking function that combined cosine similarity and the frequency of GO terms in documents, and a filtering method based on high-level GO classes. The best performance of our submitted runs was 7.8% F1 and 22.2% hierarchy F1. We found that the incorporation of frequency information and hierarchy filtering substantially improved the performance. In the post-submission evaluation, we obtained a 10.6% F1 using a simpler setting. Overall, the experimental analysis showed our approaches were robust in both the two tasks. © The Author(s) 2014. Published by Oxford University Press.

  9. Length bias correction in gene ontology enrichment analysis using logistic regression.

    Science.gov (United States)

    Mi, Gu; Di, Yanming; Emerson, Sarah; Cumbie, Jason S; Chang, Jeff H

    2012-01-01

    When assessing differential gene expression from RNA sequencing data, commonly used statistical tests tend to have greater power to detect differential expression of genes encoding longer transcripts. This phenomenon, called "length bias", will influence subsequent analyses such as Gene Ontology enrichment analysis. In the presence of length bias, Gene Ontology categories that include longer genes are more likely to be identified as enriched. These categories, however, are not necessarily biologically more relevant. We show that one can effectively adjust for length bias in Gene Ontology analysis by including transcript length as a covariate in a logistic regression model. The logistic regression model makes the statistical issue underlying length bias more transparent: transcript length becomes a confounding factor when it correlates with both the Gene Ontology membership and the significance of the differential expression test. The inclusion of the transcript length as a covariate allows one to investigate the direct correlation between the Gene Ontology membership and the significance of testing differential expression, conditional on the transcript length. We present both real and simulated data examples to show that the logistic regression approach is simple, effective, and flexible.

  10. Aspergillus flavus Blast2GO gene ontology database: elevated growth temperature alters amino acid metabolism

    Science.gov (United States)

    The availability of a representative gene ontology (GO) database is a prerequisite for a successful functional genomics study. Using online Blast2GO resources we constructed a GO database of Aspergillus flavus. Of the predicted total 13,485 A. flavus genes 8,987 were annotated with GO terms. The mea...

  11. Annotating the Function of the Human Genome with Gene Ontology and Disease Ontology.

    Science.gov (United States)

    Hu, Yang; Zhou, Wenyang; Ren, Jun; Dong, Lixiang; Wang, Yadong; Jin, Shuilin; Cheng, Liang

    2016-01-01

    Increasing evidences indicated that function annotation of human genome in molecular level and phenotype level is very important for systematic analysis of genes. In this study, we presented a framework named Gene2Function to annotate Gene Reference into Functions (GeneRIFs), in which each functional description of GeneRIFs could be annotated by a text mining tool Open Biomedical Annotator (OBA), and each Entrez gene could be mapped to Human Genome Organisation Gene Nomenclature Committee (HGNC) gene symbol. After annotating all the records about human genes of GeneRIFs, 288,869 associations between 13,148 mRNAs and 7,182 terms, 9,496 associations between 948 microRNAs and 533 terms, and 901 associations between 139 long noncoding RNAs (lncRNAs) and 297 terms were obtained as a comprehensive annotation resource of human genome. High consistency of term frequency of individual gene (Pearson correlation = 0.6401, p = 2.2e - 16) and gene frequency of individual term (Pearson correlation = 0.1298, p = 3.686e - 14) in GeneRIFs and GOA shows our annotation resource is very reliable.

  12. IGEMS: The Consortium on Interplay of Genes and Environment Across Multiple Studies

    DEFF Research Database (Denmark)

    Pedersen, Nancy L; Christensen, Kaare; Dahl, Anna K

    2013-01-01

    The Interplay of Genes and Environment across Multiple Studies (IGEMS) group is a consortium of eight longitudinal twin studies established to explore the nature of social context effects and gene-environment interplay in late-life functioning. The resulting analysis of the combined data from ove...

  13. Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions.

    Science.gov (United States)

    Hur, Junguk; Özgür, Arzucan; Xiang, Zuoshuang; He, Yongqun

    2015-01-01

    Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher's exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with 'INO_' prefix. A new annotation property, 'has literature mining keywords', was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher's exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these

  14. A new measure for functional similarity of gene products based on Gene Ontology

    Directory of Open Access Journals (Sweden)

    Lengauer Thomas

    2006-06-01

    Full Text Available Abstract Background Gene Ontology (GO is a standard vocabulary of functional terms and allows for coherent annotation of gene products. These annotations provide a basis for new methods that compare gene products regarding their molecular function and biological role. Results We present a new method for comparing sets of GO terms and for assessing the functional similarity of gene products. The method relies on two semantic similarity measures; simRel and funSim. One measure (simRel is applied in the comparison of the biological processes found in different groups of organisms. The other measure (funSim is used to find functionally related gene products within the same or between different genomes. Results indicate that the method, in addition to being in good agreement with established sequence similarity approaches, also provides a means for the identification of functionally related proteins independent of evolutionary relationships. The method is also applied to estimating functional similarity between all proteins in Saccharomyces cerevisiae and to visualizing the molecular function space of yeast in a map of the functional space. A similar approach is used to visualize the functional relationships between protein families. Conclusion The approach enables the comparison of the underlying molecular biology of different taxonomic groups and provides a new comparative genomics tool identifying functionally related gene products independent of homology. The proposed map of the functional space provides a new global view on the functional relationships between gene products or protein families.

  15. GO(vis), a gene ontology visualization tool based on multi-dimensional values.

    Science.gov (United States)

    Ning, Zi; Jiang, Zhenran

    2010-05-01

    Most of gene product similarity measurements concentrate on the information content of Gene Ontology (GO) terms or use a path-based similarity between GO terms, which may ignore other important information contained in the structure of the ontology. In our study, we integrate different GO similarity measure approaches to analyze the functional relationship of genes and gene products with a new triangle-based visualization tool called GO(Vis). The purpose of this tool is to demonstrate the effect of three important information factors when measuring the similarity between gene products. One advantage of this tool is that its important ratio can be adjusted to meet different measuring requirements according to the biological knowledge of each factor. The experimental results demonstrate that GO(Vis) can display diagrams of the functional relationship for gene products effectively.

  16. A multicolor panel of novel lentiviral "gene ontology" (LeGO) vectors for functional gene analysis.

    Science.gov (United States)

    Weber, Kristoffer; Bartsch, Udo; Stocking, Carol; Fehse, Boris

    2008-04-01

    Functional gene analysis requires the possibility of overexpression, as well as downregulation of one, or ideally several, potentially interacting genes. Lentiviral vectors are well suited for this purpose as they ensure stable expression of complementary DNAs (cDNAs), as well as short-hairpin RNAs (shRNAs), and can efficiently transduce a wide spectrum of cell targets when packaged within the coat proteins of other viruses. Here we introduce a multicolor panel of novel lentiviral "gene ontology" (LeGO) vectors designed according to the "building blocks" principle. Using a wide spectrum of different fluorescent markers, including drug-selectable enhanced green fluorescent protein (eGFP)- and dTomato-blasticidin-S resistance fusion proteins, LeGO vectors allow simultaneous analysis of multiple genes and shRNAs of interest within single, easily identifiable cells. Furthermore, each functional module is flanked by unique cloning sites, ensuring flexibility and individual optimization. The efficacy of these vectors for analyzing multiple genes in a single cell was demonstrated in several different cell types, including hematopoietic, endothelial, and neural stem and progenitor cells, as well as hepatocytes. LeGO vectors thus represent a valuable tool for investigating gene networks using conditional ectopic expression and knock-down approaches simultaneously.

  17. Ontology-based literature mining of E. coli vaccine-associated gene interaction networks.

    Science.gov (United States)

    Hur, Junguk; Özgür, Arzucan; He, Yongqun

    2017-03-14

    Pathogenic Escherichia coli infections cause various diseases in humans and many animal species. However, with extensive E. coli vaccine research, we are still unable to fully protect ourselves against E. coli infections. To more rational development of effective and safe E. coli vaccine, it is important to better understand E. coli vaccine-associated gene interaction networks. In this study, we first extended the Vaccine Ontology (VO) to semantically represent various E. coli vaccines and genes used in the vaccine development. We also normalized E. coli gene names compiled from the annotations of various E. coli strains using a pan-genome-based annotation strategy. The Interaction Network Ontology (INO) includes a hierarchy of various interaction-related keywords useful for literature mining. Using VO, INO, and normalized E. coli gene names, we applied an ontology-based SciMiner literature mining strategy to mine all PubMed abstracts and retrieve E. coli vaccine-associated E. coli gene interactions. Four centrality metrics (i.e., degree, eigenvector, closeness, and betweenness) were calculated for identifying highly ranked genes and interaction types. Using vaccine-related PubMed abstracts, our study identified 11,350 sentences that contain 88 unique INO interactions types and 1,781 unique E. coli genes. Each sentence contained at least one interaction type and two unique E. coli genes. An E. coli gene interaction network of genes and INO interaction types was created. From this big network, a sub-network consisting of 5 E. coli vaccine genes, including carA, carB, fimH, fepA, and vat, and 62 other E. coli genes, and 25 INO interaction types was identified. While many interaction types represent direct interactions between two indicated genes, our study has also shown that many of these retrieved interaction types are indirect in that the two genes participated in the specified interaction process in a required but indirect process. Our centrality analysis of

  18. Stable carbon isotope fractionation of chlorinated ethenes by a microbial consortium containing multiple dechlorinating genes.

    Science.gov (United States)

    Liu, Na; Ding, Longzhen; Li, Haijun; Zhang, Pengpeng; Zheng, Jixing; Weng, Chih-Huang

    2018-08-01

    The study aimed to determine the possible contribution of specific growth conditions and community structures to variable carbon enrichment factors (Ɛ- carbon ) values for the degradation of chlorinated ethenes (CEs) by a bacterial consortium with multiple dechlorinating genes. Ɛ- carbon values for trichloroethylene, cis-1,2-dichloroethylene, and vinyl chloride were -7.24% ± 0.59%, -14.6% ± 1.71%, and -21.1% ± 1.14%, respectively, during their degradation by a microbial consortium containing multiple dechlorinating genes including tceA and vcrA. The Ɛ- carbon values of all CEs were not greatly affected by changes in growth conditions and community structures, which directly or indirectly affected reductive dechlorination of CEs by this consortium. Stability analysis provided evidence that the presence of multiple dechlorinating genes within a microbial consortium had little effect on carbon isotope fractionation, as long as the genes have definite, non-overlapping functions. Copyright © 2018 Elsevier Ltd. All rights reserved.

  19. The mammalian adult neurogenesis gene ontology (MANGO provides a structural framework for published information on genes regulating adult hippocampal neurogenesis.

    Directory of Open Access Journals (Sweden)

    Rupert W Overall

    Full Text Available BACKGROUND: Adult hippocampal neurogenesis is not a single phenotype, but consists of a number of sub-processes, each of which is under complex genetic control. Interpretation of gene expression studies using existing resources often does not lead to results that address the interrelatedness of these processes. Formal structure, such as provided by ontologies, is essential in any field for comprehensive interpretation of existing knowledge but, until now, such a structure has been lacking for adult neurogenesis. METHODOLOGY/PRINCIPAL FINDINGS: We have created a resource with three components 1. A structured ontology describing the key stages in the development of adult hippocampal neural stem cells into functional granule cell neurons. 2. A comprehensive survey of the literature to annotate the results of all published reports on gene function in adult hippocampal neurogenesis (257 manuscripts covering 228 genes to the appropriate terms in our ontology. 3. An easy-to-use searchable interface to the resulting database made freely available online. The manuscript presents an overview of the database highlighting global trends such as the current bias towards research on early proliferative stages, and an example gene set enrichment analysis. A limitation of the resource is the current scope of the literature which, however, is growing by around 100 publications per year. With the ontology and database in place, new findings can be rapidly annotated and regular updates of the database will be made publicly available. CONCLUSIONS/SIGNIFICANCE: The resource we present allows relevant interpretation of gene expression screens in terms of defined stages of postnatal neuronal development. Annotation of genes by hand from the adult neurogenesis literature ensures the data are directly applicable to the system under study. We believe this approach could also serve as an example to other fields in a 'bottom-up' community effort complementing the already

  20. Mapping between the OBO and OWL ontology languages.

    Science.gov (United States)

    Tirmizi, Syed Hamid; Aitken, Stuart; Moreira, Dilvan A; Mungall, Chris; Sequeda, Juan; Shah, Nigam H; Miranker, Daniel P

    2011-03-07

    Ontologies are commonly used in biomedicine to organize concepts to describe domains such as anatomies, environments, experiment, taxonomies etc. NCBO BioPortal currently hosts about 180 different biomedical ontologies. These ontologies have been mainly expressed in either the Open Biomedical Ontology (OBO) format or the Web Ontology Language (OWL). OBO emerged from the Gene Ontology, and supports most of the biomedical ontology content. In comparison, OWL is a Semantic Web language, and is supported by the World Wide Web consortium together with integral query languages, rule languages and distributed infrastructure for information interchange. These features are highly desirable for the OBO content as well. A convenient method for leveraging these features for OBO ontologies is by transforming OBO ontologies to OWL. We have developed a methodology for translating OBO ontologies to OWL using the organization of the Semantic Web itself to guide the work. The approach reveals that the constructs of OBO can be grouped together to form a similar layer cake. Thus we were able to decompose the problem into two parts. Most OBO constructs have easy and obvious equivalence to a construct in OWL. A small subset of OBO constructs requires deeper consideration. We have defined transformations for all constructs in an effort to foster a standard common mapping between OBO and OWL. Our mapping produces OWL-DL, a Description Logics based subset of OWL with desirable computational properties for efficiency and correctness. Our Java implementation of the mapping is part of the official Gene Ontology project source. Our transformation system provides a lossless roundtrip mapping for OBO ontologies, i.e. an OBO ontology may be translated to OWL and back without loss of knowledge. In addition, it provides a roadmap for bridging the gap between the two ontology languages in order to enable the use of ontology content in a language independent manner.

  1. Systematically characterizing and prioritizing chemosensitivity related gene based on Gene Ontology and protein interaction network

    Directory of Open Access Journals (Sweden)

    Chen Xin

    2012-10-01

    Full Text Available Abstract Background The identification of genes that predict in vitro cellular chemosensitivity of cancer cells is of great importance. Chemosensitivity related genes (CRGs have been widely utilized to guide clinical and cancer chemotherapy decisions. In addition, CRGs potentially share functional characteristics and network features in protein interaction networks (PPIN. Methods In this study, we proposed a method to identify CRGs based on Gene Ontology (GO and PPIN. Firstly, we documented 150 pairs of drug-CCRG (curated chemosensitivity related gene from 492 published papers. Secondly, we characterized CCRGs from the perspective of GO and PPIN. Thirdly, we prioritized CRGs based on CCRGs’ GO and network characteristics. Lastly, we evaluated the performance of the proposed method. Results We found that CCRG enriched GO terms were most often related to chemosensitivity and exhibited higher similarity scores compared to randomly selected genes. Moreover, CCRGs played key roles in maintaining the connectivity and controlling the information flow of PPINs. We then prioritized CRGs using CCRG enriched GO terms and CCRG network characteristics in order to obtain a database of predicted drug-CRGs that included 53 CRGs, 32 of which have been reported to affect susceptibility to drugs. Our proposed method identifies a greater number of drug-CCRGs, and drug-CCRGs are much more significantly enriched in predicted drug-CRGs, compared to a method based on the correlation of gene expression and drug activity. The mean area under ROC curve (AUC for our method is 65.2%, whereas that for the traditional method is 55.2%. Conclusions Our method not only identifies CRGs with expression patterns strongly correlated with drug activity, but also identifies CRGs in which expression is weakly correlated with drug activity. This study provides the framework for the identification of signatures that predict in vitro cellular chemosensitivity and offers a valuable

  2. GOssTo: a stand-alone application and a web tool for calculating semantic similarities on the Gene Ontology

    OpenAIRE

    Caniza, Horacio; Romero, Alfonso E.; Heron, Samuel; Yang, Haixuan; Devoto, Alessandra; Frasca, Marco; Mesiti, Marco; Valentini, Giorgio; Paccanaro, Alberto

    2014-01-01

    Summary: We present GOssTo, the Gene Ontology semantic similarity Tool, a user-friendly software system for calculating semantic similarities between gene products according to the Gene Ontology. GOssTo is bundled with six semantic similarity measures, including both term- and graph-based measures, and has extension capabilities to allow the user to add new similarities. Importantly, for any measure, GOssTo can also calculate the Random Walk Contribution that has been shown to greatly improve...

  3. Gene Ontology Terms and Automated Annotation for Energy-Related Microbial Genomes

    Energy Technology Data Exchange (ETDEWEB)

    Mukhopadhyay, Biswarup [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Tyler, Brett M. [Oregon State Univ., Corvallis, OR (United States); Setubal, Joao [Univ. of Sao Paulo (Brazil); Murali, T. M. [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)

    2017-11-03

    Gene Ontology (GO) is one of the more widely used functional ontologies for describing gene functions at various levels. The project developed 660 GO terms for describing energy-related microbial processes and filled the known gaps in this area of the GO system, and then used these terms to describe functions of 179 genes to showcase the utilities of the new resources. It hosted a series of workshops and made presentations at key meetings to inform and train scientific community members on these terms and to receive inputs from them for the GO term generation efforts. The project has developed a website for storing and displaying the resources (http://www.mengo.biochem.vt.edu/). The outcome of the project was further disseminated through peer-reviewed publications and poster and seminar presentations.

  4. A UML profile for the OBO relation ontology

    Science.gov (United States)

    2012-01-01

    Background Ontologies have increasingly been used in the biomedical domain, which has prompted the emergence of different initiatives to facilitate their development and integration. The Open Biological and Biomedical Ontologies (OBO) Foundry consortium provides a repository of life-science ontologies, which are developed according to a set of shared principles. This consortium has developed an ontology called OBO Relation Ontology aiming at standardizing the different types of biological entity classes and associated relationships. Since ontologies are primarily intended to be used by humans, the use of graphical notations for ontology development facilitates the capture, comprehension and communication of knowledge between its users. However, OBO Foundry ontologies are captured and represented basically using text-based notations. The Unified Modeling Language (UML) provides a standard and widely-used graphical notation for modeling computer systems. UML provides a well-defined set of modeling elements, which can be extended using a built-in extension mechanism named Profile. Thus, this work aims at developing a UML profile for the OBO Relation Ontology to provide a domain-specific set of modeling elements that can be used to create standard UML-based ontologies in the biomedical domain. Results We have studied the OBO Relation Ontology, the UML metamodel and the UML profiling mechanism. Based on these studies, we have proposed an extension to the UML metamodel in conformance with the OBO Relation Ontology and we have defined a profile that implements the extended metamodel. Finally, we have applied the proposed UML profile in the development of a number of fragments from different ontologies. Particularly, we have considered the Gene Ontology (GO), the PRotein Ontology (PRO) and the Xenopus Anatomy and Development Ontology (XAO). Conclusions The use of an established and well-known graphical language in the development of biomedical ontologies provides a more

  5. Protein-protein interaction inference based on semantic similarity of Gene Ontology terms.

    Science.gov (United States)

    Zhang, Shu-Bo; Tang, Qiang-Rong

    2016-07-21

    Identifying protein-protein interactions is important in molecular biology. Experimental methods to this issue have their limitations, and computational approaches have attracted more and more attentions from the biological community. The semantic similarity derived from the Gene Ontology (GO) annotation has been regarded as one of the most powerful indicators for protein interaction. However, conventional methods based on GO similarity fail to take advantage of the specificity of GO terms in the ontology graph. We proposed a GO-based method to predict protein-protein interaction by integrating different kinds of similarity measures derived from the intrinsic structure of GO graph. We extended five existing methods to derive the semantic similarity measures from the descending part of two GO terms in the GO graph, then adopted a feature integration strategy to combines both the ascending and the descending similarity scores derived from the three sub-ontologies to construct various kinds of features to characterize each protein pair. Support vector machines (SVM) were employed as discriminate classifiers, and five-fold cross validation experiments were conducted on both human and yeast protein-protein interaction datasets to evaluate the performance of different kinds of integrated features, the experimental results suggest the best performance of the feature that combines information from both the ascending and the descending parts of the three ontologies. Our method is appealing for effective prediction of protein-protein interaction. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Is the crowd better as an assistant or a replacement in ontology engineering? An exploration through the lens of the Gene Ontology.

    Science.gov (United States)

    Mortensen, Jonathan M; Telis, Natalie; Hughey, Jacob J; Fan-Minogue, Hua; Van Auken, Kimberly; Dumontier, Michel; Musen, Mark A

    2016-04-01

    Biomedical ontologies contain errors. Crowdsourcing, defined as taking a job traditionally performed by a designated agent and outsourcing it to an undefined large group of people, provides scalable access to humans. Therefore, the crowd has the potential to overcome the limited accuracy and scalability found in current ontology quality assurance approaches. Crowd-based methods have identified errors in SNOMED CT, a large, clinical ontology, with an accuracy similar to that of experts, suggesting that crowdsourcing is indeed a feasible approach for identifying ontology errors. This work uses that same crowd-based methodology, as well as a panel of experts, to verify a subset of the Gene Ontology (200 relationships). Experts identified 16 errors, generally in relationships referencing acids and metals. The crowd performed poorly in identifying those errors, with an area under the receiver operating characteristic curve ranging from 0.44 to 0.73, depending on the methods configuration. However, when the crowd verified what experts considered to be easy relationships with useful definitions, they performed reasonably well. Notably, there are significantly fewer Google search results for Gene Ontology concepts than SNOMED CT concepts. This disparity may account for the difference in performance - fewer search results indicate a more difficult task for the worker. The number of Internet search results could serve as a method to assess which tasks are appropriate for the crowd. These results suggest that the crowd fits better as an expert assistant, helping experts with their verification by completing the easy tasks and allowing experts to focus on the difficult tasks, rather than an expert replacement. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. Genetic Resources for Advanced Biofuel Production Described with the Gene Ontology

    Directory of Open Access Journals (Sweden)

    Trudy eTorto-Alalibo

    2014-10-01

    Full Text Available Dramatic increases in research in the area of microbial biofuel production coupled with high-throughput data generation on bioenergy-related microbes has led to a deluge of information in the scientific literature and in databases. Consolidating this information and making it easily accessible requires a unified vocabulary. The Gene Ontology (GO fulfills that requirement, as it is a well-developed structured vocabulary that describes the activities and locations of gene products in a consistent manner across all kingdoms of life. The Microbial Energy Gene Ontology (MENGO: http://www.mengo.biochem.vt.edu project is extending the GO to include new terms to describe microbial processes of interest to bioenergy production. Our effort has added over 600 bioenergy related terms to the Gene Ontology. These terms will aid in the comprehensive annotation of gene products from diverse energy-related microbial genomes. An area of microbial energy research that has received a lot of attention is microbial production of advanced biofuels. These include alcohols such as butanol, isopropanol, isobutanol, and fuels derived from fatty acids, isoprenoids, and polyhydroxyalkanoates. These fuels are superior to first generation biofuels (ethanol and biodiesel esterified from vegetable oil or animal fat, can be generated from non-food feedstock sources, can be used as supplements or substitutes for gasoline, diesel and jet fuels, and can be stored and distributed using existing infrastructure. Here we review the roles of genes associated with synthesis of advanced biofuels, and at the same time introduce the use of the GO to describe the functions of these genes in a standardized way.

  8. Zebrafish Expression Ontology of Gene Sets (ZEOGS): a tool to analyze enrichment of zebrafish anatomical terms in large gene sets.

    Science.gov (United States)

    Prykhozhij, Sergey V; Marsico, Annalisa; Meijsing, Sebastiaan H

    2013-09-01

    The zebrafish (Danio rerio) is an established model organism for developmental and biomedical research. It is frequently used for high-throughput functional genomics experiments, such as genome-wide gene expression measurements, to systematically analyze molecular mechanisms. However, the use of whole embryos or larvae in such experiments leads to a loss of the spatial information. To address this problem, we have developed a tool called Zebrafish Expression Ontology of Gene Sets (ZEOGS) to assess the enrichment of anatomical terms in large gene sets. ZEOGS uses gene expression pattern data from several sources: first, in situ hybridization experiments from the Zebrafish Model Organism Database (ZFIN); second, it uses the Zebrafish Anatomical Ontology, a controlled vocabulary that describes connected anatomical structures; and third, the available connections between expression patterns and anatomical terms contained in ZFIN. Upon input of a gene set, ZEOGS determines which anatomical structures are overrepresented in the input gene set. ZEOGS allows one for the first time to look at groups of genes and to describe them in terms of shared anatomical structures. To establish ZEOGS, we first tested it on random gene selections and on two public microarray datasets with known tissue-specific gene expression changes. These tests showed that ZEOGS could reliably identify the tissues affected, whereas only very few enriched terms to none were found in the random gene sets. Next we applied ZEOGS to microarray datasets of 24 and 72 h postfertilization zebrafish embryos treated with beclomethasone, a potent glucocorticoid. This analysis resulted in the identification of several anatomical terms related to glucocorticoid-responsive tissues, some of which were stage-specific. Our studies highlight the ability of ZEOGS to extract spatial information from datasets derived from whole embryos, indicating that ZEOGS could be a useful tool to automatically analyze gene expression

  9. Zebrafish Expression Ontology of Gene Sets (ZEOGS): A Tool to Analyze Enrichment of Zebrafish Anatomical Terms in Large Gene Sets

    Science.gov (United States)

    Marsico, Annalisa

    2013-01-01

    Abstract The zebrafish (Danio rerio) is an established model organism for developmental and biomedical research. It is frequently used for high-throughput functional genomics experiments, such as genome-wide gene expression measurements, to systematically analyze molecular mechanisms. However, the use of whole embryos or larvae in such experiments leads to a loss of the spatial information. To address this problem, we have developed a tool called Zebrafish Expression Ontology of Gene Sets (ZEOGS) to assess the enrichment of anatomical terms in large gene sets. ZEOGS uses gene expression pattern data from several sources: first, in situ hybridization experiments from the Zebrafish Model Organism Database (ZFIN); second, it uses the Zebrafish Anatomical Ontology, a controlled vocabulary that describes connected anatomical structures; and third, the available connections between expression patterns and anatomical terms contained in ZFIN. Upon input of a gene set, ZEOGS determines which anatomical structures are overrepresented in the input gene set. ZEOGS allows one for the first time to look at groups of genes and to describe them in terms of shared anatomical structures. To establish ZEOGS, we first tested it on random gene selections and on two public microarray datasets with known tissue-specific gene expression changes. These tests showed that ZEOGS could reliably identify the tissues affected, whereas only very few enriched terms to none were found in the random gene sets. Next we applied ZEOGS to microarray datasets of 24 and 72 h postfertilization zebrafish embryos treated with beclomethasone, a potent glucocorticoid. This analysis resulted in the identification of several anatomical terms related to glucocorticoid-responsive tissues, some of which were stage-specific. Our studies highlight the ability of ZEOGS to extract spatial information from datasets derived from whole embryos, indicating that ZEOGS could be a useful tool to automatically analyze gene

  10. GOexpress: an R/Bioconductor package for the identification and visualisation of robust gene ontology signatures through supervised learning of gene expression data.

    Science.gov (United States)

    Rue-Albrecht, Kévin; McGettigan, Paul A; Hernández, Belinda; Nalpas, Nicolas C; Magee, David A; Parnell, Andrew C; Gordon, Stephen V; MacHugh, David E

    2016-03-11

    Identification of gene expression profiles that differentiate experimental groups is critical for discovery and analysis of key molecular pathways and also for selection of robust diagnostic or prognostic biomarkers. While integration of differential expression statistics has been used to refine gene set enrichment analyses, such approaches are typically limited to single gene lists resulting from simple two-group comparisons or time-series analyses. In contrast, functional class scoring and machine learning approaches provide powerful alternative methods to leverage molecular measurements for pathway analyses, and to compare continuous and multi-level categorical factors. We introduce GOexpress, a software package for scoring and summarising the capacity of gene ontology features to simultaneously classify samples from multiple experimental groups. GOexpress integrates normalised gene expression data (e.g., from microarray and RNA-seq experiments) and phenotypic information of individual samples with gene ontology annotations to derive a ranking of genes and gene ontology terms using a supervised learning approach. The default random forest algorithm allows interactions between all experimental factors, and competitive scoring of expressed genes to evaluate their relative importance in classifying predefined groups of samples. GOexpress enables rapid identification and visualisation of ontology-related gene panels that robustly classify groups of samples and supports both categorical (e.g., infection status, treatment) and continuous (e.g., time-series, drug concentrations) experimental factors. The use of standard Bioconductor extension packages and publicly available gene ontology annotations facilitates straightforward integration of GOexpress within existing computational biology pipelines.

  11. Analysis of mammalian gene function through broad based phenotypic screens across a consortium of mouse clinics

    Science.gov (United States)

    Adams, David J; Adams, Niels C; Adler, Thure; Aguilar-Pimentel, Antonio; Ali-Hadji, Dalila; Amann, Gregory; André, Philippe; Atkins, Sarah; Auburtin, Aurelie; Ayadi, Abdel; Becker, Julien; Becker, Lore; Bedu, Elodie; Bekeredjian, Raffi; Birling, Marie-Christine; Blake, Andrew; Bottomley, Joanna; Bowl, Mike; Brault, Véronique; Busch, Dirk H; Bussell, James N; Calzada-Wack, Julia; Cater, Heather; Champy, Marie-France; Charles, Philippe; Chevalier, Claire; Chiani, Francesco; Codner, Gemma F; Combe, Roy; Cox, Roger; Dalloneau, Emilie; Dierich, André; Di Fenza, Armida; Doe, Brendan; Duchon, Arnaud; Eickelberg, Oliver; Esapa, Chris T; El Fertak, Lahcen; Feigel, Tanja; Emelyanova, Irina; Estabel, Jeanne; Favor, Jack; Flenniken, Ann; Gambadoro, Alessia; Garrett, Lilian; Gates, Hilary; Gerdin, Anna-Karin; Gkoutos, George; Greenaway, Simon; Glasl, Lisa; Goetz, Patrice; Da Cruz, Isabelle Goncalves; Götz, Alexander; Graw, Jochen; Guimond, Alain; Hans, Wolfgang; Hicks, Geoff; Hölter, Sabine M; Höfler, Heinz; Hancock, John M; Hoehndorf, Robert; Hough, Tertius; Houghton, Richard; Hurt, Anja; Ivandic, Boris; Jacobs, Hughes; Jacquot, Sylvie; Jones, Nora; Karp, Natasha A; Katus, Hugo A; Kitchen, Sharon; Klein-Rodewald, Tanja; Klingenspor, Martin; Klopstock, Thomas; Lalanne, Valerie; Leblanc, Sophie; Lengger, Christoph; le Marchand, Elise; Ludwig, Tonia; Lux, Aline; McKerlie, Colin; Maier, Holger; Mandel, Jean-Louis; Marschall, Susan; Mark, Manuel; Melvin, David G; Meziane, Hamid; Micklich, Kateryna; Mittelhauser, Christophe; Monassier, Laurent; Moulaert, David; Muller, Stéphanie; Naton, Beatrix; Neff, Frauke; Nolan, Patrick M; Nutter, Lauryl MJ; Ollert, Markus; Pavlovic, Guillaume; Pellegata, Natalia S; Peter, Emilie; Petit-Demoulière, Benoit; Pickard, Amanda; Podrini, Christine; Potter, Paul; Pouilly, Laurent; Puk, Oliver; Richardson, David; Rousseau, Stephane; Quintanilla-Fend, Leticia; Quwailid, Mohamed M; Racz, Ildiko; Rathkolb, Birgit; Riet, Fabrice; Rossant, Janet; Roux, Michel; Rozman, Jan; Ryder, Ed; Salisbury, Jennifer; Santos, Luis; Schäble, Karl-Heinz; Schiller, Evelyn; Schrewe, Anja; Schulz, Holger; Steinkamp, Ralf; Simon, Michelle; Stewart, Michelle; Stöger, Claudia; Stöger, Tobias; Sun, Minxuan; Sunter, David; Teboul, Lydia; Tilly, Isabelle; Tocchini-Valentini, Glauco P; Tost, Monica; Treise, Irina; Vasseur, Laurent; Velot, Emilie; Vogt-Weisenhorn, Daniela; Wagner, Christelle; Walling, Alison; Weber, Bruno; Wendling, Olivia; Westerberg, Henrik; Willershäuser, Monja; Wolf, Eckhard; Wolter, Anne; Wood, Joe; Wurst, Wolfgang; Yildirim, Ali Önder; Zeh, Ramona; Zimmer, Andreas; Zimprich, Annemarie

    2015-01-01

    The function of the majority of genes in the mouse and human genomes remains unknown. The mouse ES cell knockout resource provides a basis for characterisation of relationships between gene and phenotype. The EUMODIC consortium developed and validated robust methodologies for broad-based phenotyping of knockouts through a pipeline comprising 20 disease-orientated platforms. We developed novel statistical methods for pipeline design and data analysis aimed at detecting reproducible phenotypes with high power. We acquired phenotype data from 449 mutant alleles, representing 320 unique genes, of which half had no prior functional annotation. We captured data from over 27,000 mice finding that 83% of the mutant lines are phenodeviant, with 65% demonstrating pleiotropy. Surprisingly, we found significant differences in phenotype annotation according to zygosity. Novel phenotypes were uncovered for many genes with unknown function providing a powerful basis for hypothesis generation and further investigation in diverse systems. PMID:26214591

  12. Disease Model Discovery from 3,328 Gene Knockouts by The International Mouse Phenotyping Consortium

    Science.gov (United States)

    Meehan, Terrence F.; Conte, Nathalie; West, David B.; Jacobsen, Julius O.; Mason, Jeremy; Warren, Jonathan; Chen, Chao-Kung; Tudose, Ilinca; Relac, Mike; Matthews, Peter; Karp, Natasha; Santos, Luis; Fiegel, Tanja; Ring, Natalie; Westerberg, Henrik; Greenaway, Simon; Sneddon, Duncan; Morgan, Hugh; Codner, Gemma F; Stewart, Michelle E; Brown, James; Horner, Neil; Haendel, Melissa; Washington, Nicole; Mungall, Christopher J.; Reynolds, Corey L; Gallegos, Juan; Gailus-Durner, Valerie; Sorg, Tania; Pavlovic, Guillaume; Bower, Lynette R; Moore, Mark; Morse, Iva; Gao, Xiang; Tocchini-Valentini, Glauco P; Obata, Yuichi; Cho, Soo Young; Seong, Je Kyung; Seavitt, John; Beaudet, Arthur L.; Dickinson, Mary E.; Herault, Yann; Wurst, Wolfgang; de Angelis, Martin Hrabe; Lloyd, K.C. Kent; Flenniken, Ann M; Nutter, Lauryl MJ; Newbigging, Susan; McKerlie, Colin; Justice, Monica J.; Murray, Stephen A.; Svenson, Karen L.; Braun, Robert E.; White, Jacqueline K.; Bradley, Allan; Flicek, Paul; Wells, Sara; Skarnes, William C.; Adams, David J.; Parkinson, Helen; Mallon, Ann-Marie; Brown, Steve D.M.; Smedley, Damian

    2017-01-01

    Although next generation sequencing has revolutionised the ability to associate variants with human diseases, diagnostic rates and development of new therapies are still limited by our lack of knowledge of function and pathobiological mechanism for most genes. To address this challenge, the International Mouse Phenotyping Consortium (IMPC) is creating a genome- and phenome-wide catalogue of gene function by characterizing new knockout mouse strains across diverse biological systems through a broad set of standardised phenotyping tests, with all mice made readily available to the biomedical community. Analysing the first 3328 genes reveals models for 360 diseases including the first for type C Bernard-Soulier, Bardet-Biedl-5 and Gordon Holmes syndromes. 90% of our phenotype annotations are novel, providing the first functional evidence for 1092 genes and candidates in unsolved diseases such as Arrhythmogenic Right Ventricular Dysplasia 3. Finally, we describe our role in variant functional validation with the 100,000 Genomes and other projects. PMID:28650483

  13. Integration of the Gene Ontology into an object-oriented architecture

    Directory of Open Access Journals (Sweden)

    Zheng W Jim

    2005-05-01

    Full Text Available Abstract Background To standardize gene product descriptions, a formal vocabulary defined as the Gene Ontology (GO has been developed. GO terms have been categorized into biological processes, molecular functions, and cellular components. However, there is no single representation that integrates all the terms into one cohesive model. Furthermore, GO definitions have little information explaining the underlying architecture that forms these terms, such as the dynamic and static events occurring in a process. In contrast, object-oriented models have been developed to show dynamic and static events. A portion of the TGF-beta signaling pathway, which is involved in numerous cellular events including cancer, differentiation and development, was used to demonstrate the feasibility of integrating the Gene Ontology into an object-oriented model. Results Using object-oriented models we have captured the static and dynamic events that occur during a representative GO process, "transforming growth factor-beta (TGF-beta receptor complex assembly" (GO:0007181. Conclusion We demonstrate that the utility of GO terms can be enhanced by object-oriented technology, and that the GO terms can be integrated into an object-oriented model by serving as a basis for the generation of object functions and attributes.

  14. MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction

    Directory of Open Access Journals (Sweden)

    Kohlbacher Oliver

    2009-09-01

    Full Text Available Abstract Background Knowledge of subcellular localization of proteins is crucial to proteomics, drug target discovery and systems biology since localization and biological function are highly correlated. In recent years, numerous computational prediction methods have been developed. Nevertheless, there is still a need for prediction methods that show more robustness and higher accuracy. Results We extended our previous MultiLoc predictor by incorporating phylogenetic profiles and Gene Ontology terms. Two different datasets were used for training the system, resulting in two versions of this high-accuracy prediction method. One version is specialized for globular proteins and predicts up to five localizations, whereas a second version covers all eleven main eukaryotic subcellular localizations. In a benchmark study with five localizations, MultiLoc2 performs considerably better than other methods for animal and plant proteins and comparably for fungal proteins. Furthermore, MultiLoc2 performs clearly better when using a second dataset that extends the benchmark study to all eleven main eukaryotic subcellular localizations. Conclusion MultiLoc2 is an extensive high-performance subcellular protein localization prediction system. By incorporating phylogenetic profiles and Gene Ontology terms MultiLoc2 yields higher accuracies compared to its previous version. Moreover, it outperforms other prediction systems in two benchmarks studies. MultiLoc2 is available as user-friendly and free web-service, available at: http://www-bs.informatik.uni-tuebingen.de/Services/MultiLoc2.

  15. A-DaGO-Fun: an adaptable Gene Ontology semantic similarity-based functional analysis tool.

    Science.gov (United States)

    Mazandu, Gaston K; Chimusa, Emile R; Mbiyavanga, Mamana; Mulder, Nicola J

    2016-02-01

    Gene Ontology (GO) semantic similarity measures are being used for biological knowledge discovery based on GO annotations by integrating biological information contained in the GO structure into data analyses. To empower users to quickly compute, manipulate and explore these measures, we introduce A-DaGO-Fun (ADaptable Gene Ontology semantic similarity-based Functional analysis). It is a portable software package integrating all known GO information content-based semantic similarity measures and relevant biological applications associated with these measures. A-DaGO-Fun has the advantage not only of handling datasets from the current high-throughput genome-wide applications, but also allowing users to choose the most relevant semantic similarity approach for their biological applications and to adapt a given module to their needs. A-DaGO-Fun is freely available to the research community at http://web.cbio.uct.ac.za/ITGOM/adagofun. It is implemented in Linux using Python under free software (GNU General Public Licence). gmazandu@cbio.uct.ac.za or Nicola.Mulder@uct.ac.za Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  16. Analysis of mammalian gene function through broad-based phenotypic screens across a consortium of mouse clinics

    DEFF Research Database (Denmark)

    de Angelis, Martin Hrabě; Nicholson, George; Selloum, Mohammed

    2015-01-01

    The function of the majority of genes in the mouse and human genomes remains unknown. The mouse embryonic stem cell knockout resource provides a basis for the characterization of relationships between genes and phenotypes. The EUMODIC consortium developed and validated robust methodologies...

  17. GO-Bayes: Gene Ontology-based overrepresentation analysis using a Bayesian approach.

    Science.gov (United States)

    Zhang, Song; Cao, Jing; Kong, Y Megan; Scheuermann, Richard H

    2010-04-01

    A typical approach for the interpretation of high-throughput experiments, such as gene expression microarrays, is to produce groups of genes based on certain criteria (e.g. genes that are differentially expressed). To gain more mechanistic insights into the underlying biology, overrepresentation analysis (ORA) is often conducted to investigate whether gene sets associated with particular biological functions, for example, as represented by Gene Ontology (GO) annotations, are statistically overrepresented in the identified gene groups. However, the standard ORA, which is based on the hypergeometric test, analyzes each GO term in isolation and does not take into account the dependence structure of the GO-term hierarchy. We have developed a Bayesian approach (GO-Bayes) to measure overrepresentation of GO terms that incorporates the GO dependence structure by taking into account evidence not only from individual GO terms, but also from their related terms (i.e. parents, children, siblings, etc.). The Bayesian framework borrows information across related GO terms to strengthen the detection of overrepresentation signals. As a result, this method tends to identify sets of closely related GO terms rather than individual isolated GO terms. The advantage of the GO-Bayes approach is demonstrated with a simulation study and an application example.

  18. Ontology-based Brucella vaccine literature indexing and systematic analysis of gene-vaccine association network

    Science.gov (United States)

    2011-01-01

    Background Vaccine literature indexing is poorly performed in PubMed due to limited hierarchy of Medical Subject Headings (MeSH) annotation in the vaccine field. Vaccine Ontology (VO) is a community-based biomedical ontology that represents various vaccines and their relations. SciMiner is an in-house literature mining system that supports literature indexing and gene name tagging. We hypothesize that application of VO in SciMiner will aid vaccine literature indexing and mining of vaccine-gene interaction networks. As a test case, we have examined vaccines for Brucella, the causative agent of brucellosis in humans and animals. Results The VO-based SciMiner (VO-SciMiner) was developed to incorporate a total of 67 Brucella vaccine terms. A set of rules for term expansion of VO terms were learned from training data, consisting of 90 biomedical articles related to Brucella vaccine terms. VO-SciMiner demonstrated high recall (91%) and precision (99%) from testing a separate set of 100 manually selected biomedical articles. VO-SciMiner indexing exhibited superior performance in retrieving Brucella vaccine-related papers over that obtained with MeSH-based PubMed literature search. For example, a VO-SciMiner search of "live attenuated Brucella vaccine" returned 922 hits as of April 20, 2011, while a PubMed search of the same query resulted in only 74 hits. Using the abstracts of 14,947 Brucella-related papers, VO-SciMiner identified 140 Brucella genes associated with Brucella vaccines. These genes included known protective antigens, virulence factors, and genes closely related to Brucella vaccines. These VO-interacting Brucella genes were significantly over-represented in biological functional categories, including metabolite transport and metabolism, replication and repair, cell wall biogenesis, intracellular trafficking and secretion, posttranslational modification, and chaperones. Furthermore, a comprehensive interaction network of Brucella vaccines and genes were

  19. SoFoCles: feature filtering for microarray classification based on gene ontology.

    Science.gov (United States)

    Papachristoudis, Georgios; Diplaris, Sotiris; Mitkas, Pericles A

    2010-02-01

    Marker gene selection has been an important research topic in the classification analysis of gene expression data. Current methods try to reduce the "curse of dimensionality" by using statistical intra-feature set calculations, or classifiers that are based on the given dataset. In this paper, we present SoFoCles, an interactive tool that enables semantic feature filtering in microarray classification problems with the use of external, well-defined knowledge retrieved from the Gene Ontology. The notion of semantic similarity is used to derive genes that are involved in the same biological path during the microarray experiment, by enriching a feature set that has been initially produced with legacy methods. Among its other functionalities, SoFoCles offers a large repository of semantic similarity methods that are used in order to derive feature sets and marker genes. The structure and functionality of the tool are discussed in detail, as well as its ability to improve classification accuracy. Through experimental evaluation, SoFoCles is shown to outperform other classification schemes in terms of classification accuracy in two real datasets using different semantic similarity computation approaches.

  20. Gene dosage, expression, and ontology analysis identifies driver genes in the carcinogenesis and chemoradioresistance of cervical cancer.

    Directory of Open Access Journals (Sweden)

    Malin Lando

    2009-11-01

    Full Text Available Integrative analysis of gene dosage, expression, and ontology (GO data was performed to discover driver genes in the carcinogenesis and chemoradioresistance of cervical cancers. Gene dosage and expression profiles of 102 locally advanced cervical cancers were generated by microarray techniques. Fifty-two of these patients were also analyzed with the Illumina expression method to confirm the gene expression results. An independent cohort of 41 patients was used for validation of gene expressions associated with clinical outcome. Statistical analysis identified 29 recurrent gains and losses and 3 losses (on 3p, 13q, 21q associated with poor outcome after chemoradiotherapy. The intratumor heterogeneity, assessed from the gene dosage profiles, was low for these alterations, showing that they had emerged prior to many other alterations and probably were early events in carcinogenesis. Integration of the alterations with gene expression and GO data identified genes that were regulated by the alterations and revealed five biological processes that were significantly overrepresented among the affected genes: apoptosis, metabolism, macromolecule localization, translation, and transcription. Four genes on 3p (RYBP, GBE1 and 13q (FAM48A, MED4 correlated with outcome at both the gene dosage and expression level and were satisfactorily validated in the independent cohort. These integrated analyses yielded 57 candidate drivers of 24 genetic events, including novel loci responsible for chemoradioresistance. Further mapping of the connections among genetic events, drivers, and biological processes suggested that each individual event stimulates specific processes in carcinogenesis through the coordinated control of multiple genes. The present results may provide novel therapeutic opportunities of both early and advanced stage cervical cancers.

  1. Human microRNA target analysis and gene ontology clustering by GOmir, a novel stand-alone application.

    Science.gov (United States)

    Roubelakis, Maria G; Zotos, Pantelis; Papachristoudis, Georgios; Michalopoulos, Ioannis; Pappa, Kalliopi I; Anagnou, Nicholas P; Kossida, Sophia

    2009-06-16

    microRNAs (miRNAs) are single-stranded RNA molecules of about 20-23 nucleotides length found in a wide variety of organisms. miRNAs regulate gene expression, by interacting with target mRNAs at specific sites in order to induce cleavage of the message or inhibit translation. Predicting or verifying mRNA targets of specific miRNAs is a difficult process of great importance. GOmir is a novel stand-alone application consisting of two separate tools: JTarget and TAGGO. JTarget integrates miRNA target prediction and functional analysis by combining the predicted target genes from TargetScan, miRanda, RNAhybrid and PicTar computational tools as well as the experimentally supported targets from TarBase and also providing a full gene description and functional analysis for each target gene. On the other hand, TAGGO application is designed to automatically group gene ontology annotations, taking advantage of the Gene Ontology (GO), in order to extract the main attributes of sets of proteins. GOmir represents a new tool incorporating two separate Java applications integrated into one stand-alone Java application. GOmir (by using up to five different databases) introduces miRNA predicted targets accompanied by (a) full gene description, (b) functional analysis and (c) detailed gene ontology clustering. Additionally, a reverse search initiated by a potential target can also be conducted. GOmir can freely be downloaded BRFAA.

  2. An ontology-driven semantic mashup of gene and biological pathway information: application to the domain of nicotine dependence.

    Science.gov (United States)

    Sahoo, Satya S; Bodenreider, Olivier; Rutter, Joni L; Skinner, Karen J; Sheth, Amit P

    2008-10-01

    This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. RESOURCE PAGE: http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/

  3. False positive reduction in protein-protein interaction predictions using gene ontology annotations

    Directory of Open Access Journals (Sweden)

    Lin Yen-Han

    2007-07-01

    Full Text Available Abstract Background Many crucial cellular operations such as metabolism, signalling, and regulations are based on protein-protein interactions. However, the lack of robust protein-protein interaction information is a challenge. One reason for the lack of solid protein-protein interaction information is poor agreement between experimental findings and computational sets that, in turn, comes from huge false positive predictions in computational approaches. Reduction of false positive predictions and enhancing true positive fraction of computationally predicted protein-protein interaction datasets based on highly confident experimental results has not been adequately investigated. Results Gene Ontology (GO annotations were used to reduce false positive protein-protein interactions (PPI pairs resulting from computational predictions. Using experimentally obtained PPI pairs as a training dataset, eight top-ranking keywords were extracted from GO molecular function annotations. The sensitivity of these keywords is 64.21% in the yeast experimental dataset and 80.83% in the worm experimental dataset. The specificities, a measure of recovery power, of these keywords applied to four predicted PPI datasets for each studied organisms, are 48.32% and 46.49% (by average of four datasets in yeast and worm, respectively. Based on eight top-ranking keywords and co-localization of interacting proteins a set of two knowledge rules were deduced and applied to remove false positive protein pairs. The 'strength', a measure of improvement provided by the rules was defined based on the signal-to-noise ratio and implemented to measure the applicability of knowledge rules applying to the predicted PPI datasets. Depending on the employed PPI-predicting methods, the strength varies between two and ten-fold of randomly removing protein pairs from the datasets. Conclusion Gene Ontology annotations along with the deduced knowledge rules could be implemented to partially

  4. Gene ontology analysis of pairwise genetic associations in two genome-wide studies of sporadic ALS

    Directory of Open Access Journals (Sweden)

    Kim Nora

    2012-07-01

    Full Text Available Abstract Background It is increasingly clear that common human diseases have a complex genetic architecture characterized by both additive and nonadditive genetic effects. The goal of the present study was to determine whether patterns of both additive and nonadditive genetic associations aggregate in specific functional groups as defined by the Gene Ontology (GO. Results We first estimated all pairwise additive and nonadditive genetic effects using the multifactor dimensionality reduction (MDR method that makes few assumptions about the underlying genetic model. Statistical significance was evaluated using permutation testing in two genome-wide association studies of ALS. The detection data consisted of 276 subjects with ALS and 271 healthy controls while the replication data consisted of 221 subjects with ALS and 211 healthy controls. Both studies included genotypes from approximately 550,000 single-nucleotide polymorphisms (SNPs. Each SNP was mapped to a gene if it was within 500 kb of the start or end. Each SNP was assigned a p-value based on its strongest joint effect with the other SNPs. We then used the Exploratory Visual Analysis (EVA method and software to assign a p-value to each gene based on the overabundance of significant SNPs at the α = 0.05 level in the gene. We also used EVA to assign p-values to each GO group based on the overabundance of significant genes at the α = 0.05 level. A GO category was determined to replicate if that category was significant at the α = 0.05 level in both studies. We found two GO categories that replicated in both studies. The first, ‘Regulation of Cellular Component Organization and Biogenesis’, a GO Biological Process, had p-values of 0.010 and 0.014 in the detection and replication studies, respectively. The second, ‘Actin Cytoskeleton’, a GO Cellular Component, had p-values of 0.040 and 0.046 in the detection and replication studies, respectively. Conclusions Pathway

  5. Mining and gene ontology based annotation of SSR markers from expressed sequence tags of Humulus lupulus

    Science.gov (United States)

    Singh, Swati; Gupta, Sanchita; Mani, Ashutosh; Chaturvedi, Anoop

    2012-01-01

    Humulus lupulus is commonly known as hops, a member of the family moraceae. Currently many projects are underway leading to the accumulation of voluminous genomic and expressed sequence tag sequences in public databases. The genetically characterized domains in these databases are limited due to non-availability of reliable molecular markers. The large data of EST sequences are available in hops. The simple sequence repeat markers extracted from EST data are used as molecular markers for genetic characterization, in the present study. 25,495 EST sequences were examined and assembled to get full-length sequences. Maximum frequency distribution was shown by mononucleotide SSR motifs i.e. 60.44% in contig and 62.16% in singleton where as minimum frequency are observed for hexanucleotide SSR in contig (0.09%) and pentanucleotide SSR in singletons (0.12%). Maximum trinucleotide motifs code for Glutamic acid (GAA) while AT/TA were the most frequent repeat of dinucleotide SSRs. Flanking primer pairs were designed in-silico for the SSR containing sequences. Functional categorization of SSRs containing sequences was done through gene ontology terms like biological process, cellular component and molecular function. PMID:22368382

  6. Protein-Protein Interactions Prediction Based on Iterative Clique Extension with Gene Ontology Filtering

    Directory of Open Access Journals (Sweden)

    Lei Yang

    2014-01-01

    Full Text Available Cliques (maximal complete subnets in protein-protein interaction (PPI network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based method of prediction and gene ontology (GO annotations to overcome the shortcoming and improve the accuracy of predictions. According to different GO correcting rules, we generate two predicted interaction sets which guarantee the quality and quantity of predicted protein interactions. The proposed method is applied to the PPI network from the Database of Interacting Proteins (DIP and most of the predicted interactions are verified by another biological database, BioGRID. The predicted protein interactions are appended to the original protein network, which leads to clique extension and shows the significance of biological meaning.

  7. GO Explorer: A gene-ontology tool to aid in the interpretation of shotgun proteomics data

    Directory of Open Access Journals (Sweden)

    Domont Gilberto B

    2009-02-01

    Full Text Available Abstract Background Spectral counting is a shotgun proteomics approach comprising the identification and relative quantitation of thousands of proteins in complex mixtures. However, this strategy generates bewildering amounts of data whose biological interpretation is a challenge. Results Here we present a new algorithm, termed GO Explorer (GOEx, that leverages the gene ontology (GO to aid in the interpretation of proteomic data. GOEx stands out because it combines data from protein fold changes with GO over-representation statistics to help draw conclusions. Moreover, it is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. Its usefulness is demonstrated by applying it to help interpret the effects of perillyl alcohol, a natural chemotherapeutic agent, on glioblastoma multiform cell lines (A172. We used a new multi-surfactant shotgun proteomic strategy and identified more than 2600 proteins; GOEx pinpointed key sets of differentially expressed proteins related to cell cycle, alcohol catabolism, the Ras pathway, apoptosis, and stress response, to name a few. Conclusion GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics. GOEx is available at http://pcarvalho.com/patternlab.

  8. GO Explorer: A gene-ontology tool to aid in the interpretation of shotgun proteomics data.

    Science.gov (United States)

    Carvalho, Paulo C; Fischer, Juliana Sg; Chen, Emily I; Domont, Gilberto B; Carvalho, Maria Gc; Degrave, Wim M; Yates, John R; Barbosa, Valmir C

    2009-02-24

    Spectral counting is a shotgun proteomics approach comprising the identification and relative quantitation of thousands of proteins in complex mixtures. However, this strategy generates bewildering amounts of data whose biological interpretation is a challenge. Here we present a new algorithm, termed GO Explorer (GOEx), that leverages the gene ontology (GO) to aid in the interpretation of proteomic data. GOEx stands out because it combines data from protein fold changes with GO over-representation statistics to help draw conclusions. Moreover, it is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. Its usefulness is demonstrated by applying it to help interpret the effects of perillyl alcohol, a natural chemotherapeutic agent, on glioblastoma multiform cell lines (A172). We used a new multi-surfactant shotgun proteomic strategy and identified more than 2600 proteins; GOEx pinpointed key sets of differentially expressed proteins related to cell cycle, alcohol catabolism, the Ras pathway, apoptosis, and stress response, to name a few. GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics. GOEx is available at http://pcarvalho.com/patternlab.

  9. Annotating activation/inhibition relationships to protein-protein interactions using gene ontology relations.

    Science.gov (United States)

    Yim, Soorin; Yu, Hasun; Jang, Dongjin; Lee, Doheon

    2018-04-11

    Signaling pathways can be reconstructed by identifying 'effect types' (i.e. activation/inhibition) of protein-protein interactions (PPIs). Effect types are composed of 'directions' (i.e. upstream/downstream) and 'signs' (i.e. positive/negative), thereby requiring directions as well as signs of PPIs to predict signaling events from PPI networks. Here, we propose a computational method for systemically annotating effect types to PPIs using relations between functional information of proteins. We used regulates, positively regulates, and negatively regulates relations in Gene Ontology (GO) to predict directions and signs of PPIs. These relations indicate both directions and signs between GO terms so that we can project directions and signs between relevant GO terms to PPIs. Independent test results showed that our method is effective for predicting both directions and signs of PPIs. Moreover, our method outperformed a previous GO-based method that did not consider the relations between GO terms. We annotated effect types to human PPIs and validated several highly confident effect types against literature. The annotated human PPIs are available in Additional file 2 to aid signaling pathway reconstruction and network biology research. We annotated effect types to PPIs by using regulates, positively regulates, and negatively regulates relations in GO. We demonstrated that those relations are effective for predicting not only signs, but also directions of PPIs. The usefulness of those relations suggests their potential applications to other types of interactions such as protein-DNA interactions.

  10. Closing the loop: from paper to protein annotation using supervised Gene Ontology classification.

    Science.gov (United States)

    Gobeill, Julien; Pasche, Emilie; Vishnyakova, Dina; Ruch, Patrick

    2014-01-01

    Gene function curation of the literature with Gene Ontology (GO) concepts is one particularly time-consuming task in genomics, and the help from bioinformatics is highly requested to keep up with the flow of publications. In 2004, the first BioCreative challenge already designed a task of automatic GO concepts assignment from a full text. At this time, results were judged far from reaching the performances required by real curation workflows. In particular, supervised approaches produced the most disappointing results because of lack of training data. Ten years later, the available curation data have massively grown. In 2013, the BioCreative IV GO task revisited the automatic GO assignment task. For this issue, we investigated the power of our supervised classifier, GOCat. GOCat computes similarities between an input text and already curated instances contained in a knowledge base to infer GO concepts. The subtask A consisted in selecting GO evidence sentences for a relevant gene in a full text. For this, we designed a state-of-the-art supervised statistical approach, using a naïve Bayes classifier and the official training set, and obtained fair results. The subtask B consisted in predicting GO concepts from the previous output. For this, we applied GOCat and reached leading results, up to 65% for hierarchical recall in the top 20 outputted concepts. Contrary to previous competitions, machine learning has this time outperformed standard dictionary-based approaches. Thanks to BioCreative IV, we were able to design a complete workflow for curation: given a gene name and a full text, this system is able to select evidence sentences for curation and to deliver highly relevant GO concepts. Contrary to previous competitions, machine learning this time outperformed dictionary-based systems. Observed performances are sufficient for being used in a real semiautomatic curation workflow. GOCat is available at http://eagl.unige.ch/GOCat/. http://eagl.unige.ch/GOCat4FT/.

  11. PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements.

    Science.gov (United States)

    Mi, Huaiyu; Huang, Xiaosong; Muruganujan, Anushya; Tang, Haiming; Mills, Caitlin; Kang, Diane; Thomas, Paul D

    2017-01-04

    The PANTHER database (Protein ANalysis THrough Evolutionary Relationships, http://pantherdb.org) contains comprehensive information on the evolution and function of protein-coding genes from 104 completely sequenced genomes. PANTHER software tools allow users to classify new protein sequences, and to analyze gene lists obtained from large-scale genomics experiments. In the past year, major improvements include a large expansion of classification information available in PANTHER, as well as significant enhancements to the analysis tools. Protein subfamily functional classifications have more than doubled due to progress of the Gene Ontology Phylogenetic Annotation Project. For human genes (as well as a few other organisms), PANTHER now also supports enrichment analysis using pathway classifications from the Reactome resource. The gene list enrichment tools include a new 'hierarchical view' of results, enabling users to leverage the structure of the classifications/ontologies; the tools also allow users to upload genetic variant data directly, rather than requiring prior conversion to a gene list. The updated coding single-nucleotide polymorphisms (SNP) scoring tool uses an improved algorithm. The hidden Markov model (HMM) search tools now use HMMER3, dramatically reducing search times and improving accuracy of E-value statistics. Finally, the PANTHER Tree-Attribute Viewer has been implemented in JavaScript, with new views for exploring protein sequence evolution. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  12. The Proteasix Ontology.

    Science.gov (United States)

    Arguello Casteleiro, Mercedes; Klein, Julie; Stevens, Robert

    2016-06-04

    The Proteasix Ontology (PxO) is an ontology that supports the Proteasix tool; an open-source peptide-centric tool that can be used to predict automatically and in a large-scale fashion in silico the proteases involved in the generation of proteolytic cleavage fragments (peptides) The PxO re-uses parts of the Protein Ontology, the three Gene Ontology sub-ontologies, the Chemical Entities of Biological Interest Ontology, the Sequence Ontology and bespoke extensions to the PxO in support of a series of roles: 1. To describe the known proteases and their target cleaveage sites. 2. To enable the description of proteolytic cleaveage fragments as the outputs of observed and predicted proteolysis. 3. To use knowledge about the function, species and cellular location of a protease and protein substrate to support the prioritisation of proteases in observed and predicted proteolysis. The PxO is designed to describe the biological underpinnings of the generation of peptides. The peptide-centric PxO seeks to support the Proteasix tool by separating domain knowledge from the operational knowledge used in protease prediction by Proteasix and to support the confirmation of its analyses and results. The Proteasix Ontology may be found at: http://bioportal.bioontology.org/ontologies/PXO . This ontology is free and open for use by everyone.

  13. Gene-ontology enrichment analysis in two independent family-based samples highlights biologically plausible processes for autism spectrum disorders.

    LENUS (Irish Health Repository)

    Anney, Richard J L

    2012-02-01

    Recent genome-wide association studies (GWAS) have implicated a range of genes from discrete biological pathways in the aetiology of autism. However, despite the strong influence of genetic factors, association studies have yet to identify statistically robust, replicated major effect genes or SNPs. We apply the principle of the SNP ratio test methodology described by O\\'Dushlaine et al to over 2100 families from the Autism Genome Project (AGP). Using a two-stage design we examine association enrichment in 5955 unique gene-ontology classifications across four groupings based on two phenotypic and two ancestral classifications. Based on estimates from simulation we identify excess of association enrichment across all analyses. We observe enrichment in association for sets of genes involved in diverse biological processes, including pyruvate metabolism, transcription factor activation, cell-signalling and cell-cycle regulation. Both genes and processes that show enrichment have previously been examined in autistic disorders and offer biologically plausibility to these findings.

  14. PFP: Automated prediction of gene ontology functional annotations with confidence scores using protein sequence data.

    Science.gov (United States)

    Hawkins, Troy; Chitale, Meghana; Luban, Stanislav; Kihara, Daisuke

    2009-02-15

    Protein function prediction is a central problem in bioinformatics, increasing in importance recently due to the rapid accumulation of biological data awaiting interpretation. Sequence data represents the bulk of this new stock and is the obvious target for consideration as input, as newly sequenced organisms often lack any other type of biological characterization. We have previously introduced PFP (Protein Function Prediction) as our sequence-based predictor of Gene Ontology (GO) functional terms. PFP interprets the results of a PSI-BLAST search by extracting and scoring individual functional attributes, searching a wide range of E-value sequence matches, and utilizing conventional data mining techniques to fill in missing information. We have shown it to be effective in predicting both specific and low-resolution functional attributes when sufficient data is unavailable. Here we describe (1) significant improvements to the PFP infrastructure, including the addition of prediction significance and confidence scores, (2) a thorough benchmark of performance and comparisons to other related prediction methods, and (3) applications of PFP predictions to genome-scale data. We applied PFP predictions to uncharacterized protein sequences from 15 organisms. Among these sequences, 60-90% could be annotated with a GO molecular function term at high confidence (>or=80%). We also applied our predictions to the protein-protein interaction network of the Malaria plasmodium (Plasmodium falciparum). High confidence GO biological process predictions (>or=90%) from PFP increased the number of fully enriched interactions in this dataset from 23% of interactions to 94%. Our benchmark comparison shows significant performance improvement of PFP relative to GOtcha, InterProScan, and PSI-BLAST predictions. This is consistent with the performance of PFP as the overall best predictor in both the AFP-SIG '05 and CASP7 function (FN) assessments. PFP is available as a web service at http

  15. Adult onset asthma and interaction between genes and active tobacco smoking: The GABRIEL consortium.

    Directory of Open Access Journals (Sweden)

    J M Vonk

    Full Text Available Genome-wide association studies have identified novel genetic associations for asthma, but without taking into account the role of active tobacco smoking. This study aimed to identify novel genes that interact with ever active tobacco smoking in adult onset asthma.We performed a genome-wide interaction analysis in six studies participating in the GABRIEL consortium following two meta-analyses approaches based on 1 the overall interaction effect and 2 the genetic effect in subjects with and without smoking exposure. We performed a discovery meta-analysis including 4,057 subjects of European descent and replicated our findings in an independent cohort (LifeLines Cohort Study, including 12,475 subjects.First approach: 50 SNPs were selected based on an overall interaction effect at p<10-4. The most pronounced interaction effect was observed for rs9969775 on chromosome 9 (discovery meta-analysis: ORint = 0.50, p = 7.63*10-5, replication: ORint = 0.65, p = 0.02. Second approach: 35 SNPs were selected based on the overall genetic effect in exposed subjects (p <10-4. The most pronounced genetic effect was observed for rs5011804 on chromosome 12 (discovery meta-analysis ORint = 1.50, p = 1.21*10-4; replication: ORint = 1.40, p = 0.03.Using two genome-wide interaction approaches, we identified novel polymorphisms in non-annotated intergenic regions on chromosomes 9 and 12, that showed suggestive evidence for interaction with active tobacco smoking in the onset of adult asthma.

  16. DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures.

    Science.gov (United States)

    Mazandu, Gaston K; Mulder, Nicola J

    2013-09-25

    The use of Gene Ontology (GO) data in protein analyses have largely contributed to the improved outcomes of these analyses. Several GO semantic similarity measures have been proposed in recent years and provide tools that allow the integration of biological knowledge embedded in the GO structure into different biological analyses. There is a need for a unified tool that provides the scientific community with the opportunity to explore these different GO similarity measure approaches and their biological applications. We have developed DaGO-Fun, an online tool available at http://web.cbio.uct.ac.za/ITGOM, which incorporates many different GO similarity measures for exploring, analyzing and comparing GO terms and proteins within the context of GO. It uses GO data and UniProt proteins with their GO annotations as provided by the Gene Ontology Annotation (GOA) project to precompute GO term information content (IC), enabling rapid response to user queries. The DaGO-Fun online tool presents the advantage of integrating all the relevant IC-based GO similarity measures, including topology- and annotation-based approaches to facilitate effective exploration of these measures, thus enabling users to choose the most relevant approach for their application. Furthermore, this tool includes several biological applications related to GO semantic similarity scores, including the retrieval of genes based on their GO annotations, the clustering of functionally related genes within a set, and term enrichment analysis.

  17. Analysis of mammalian gene function through broad-based phenotypic screens across a consortium of mouse clinics.

    Science.gov (United States)

    de Angelis, Martin Hrabě; Nicholson, George; Selloum, Mohammed; White, Jacqui; Morgan, Hugh; Ramirez-Solis, Ramiro; Sorg, Tania; Wells, Sara; Fuchs, Helmut; Fray, Martin; Adams, David J; Adams, Niels C; Adler, Thure; Aguilar-Pimentel, Antonio; Ali-Hadji, Dalila; Amann, Gregory; André, Philippe; Atkins, Sarah; Auburtin, Aurelie; Ayadi, Abdel; Becker, Julien; Becker, Lore; Bedu, Elodie; Bekeredjian, Raffi; Birling, Marie-Christine; Blake, Andrew; Bottomley, Joanna; Bowl, Mike; Brault, Véronique; Busch, Dirk H; Bussell, James N; Calzada-Wack, Julia; Cater, Heather; Champy, Marie-France; Charles, Philippe; Chevalier, Claire; Chiani, Francesco; Codner, Gemma F; Combe, Roy; Cox, Roger; Dalloneau, Emilie; Dierich, André; Di Fenza, Armida; Doe, Brendan; Duchon, Arnaud; Eickelberg, Oliver; Esapa, Chris T; El Fertak, Lahcen; Feigel, Tanja; Emelyanova, Irina; Estabel, Jeanne; Favor, Jack; Flenniken, Ann; Gambadoro, Alessia; Garrett, Lilian; Gates, Hilary; Gerdin, Anna-Karin; Gkoutos, George; Greenaway, Simon; Glasl, Lisa; Goetz, Patrice; Da Cruz, Isabelle Goncalves; Götz, Alexander; Graw, Jochen; Guimond, Alain; Hans, Wolfgang; Hicks, Geoff; Hölter, Sabine M; Höfler, Heinz; Hancock, John M; Hoehndorf, Robert; Hough, Tertius; Houghton, Richard; Hurt, Anja; Ivandic, Boris; Jacobs, Hughes; Jacquot, Sylvie; Jones, Nora; Karp, Natasha A; Katus, Hugo A; Kitchen, Sharon; Klein-Rodewald, Tanja; Klingenspor, Martin; Klopstock, Thomas; Lalanne, Valerie; Leblanc, Sophie; Lengger, Christoph; le Marchand, Elise; Ludwig, Tonia; Lux, Aline; McKerlie, Colin; Maier, Holger; Mandel, Jean-Louis; Marschall, Susan; Mark, Manuel; Melvin, David G; Meziane, Hamid; Micklich, Kateryna; Mittelhauser, Christophe; Monassier, Laurent; Moulaert, David; Muller, Stéphanie; Naton, Beatrix; Neff, Frauke; Nolan, Patrick M; Nutter, Lauryl Mj; Ollert, Markus; Pavlovic, Guillaume; Pellegata, Natalia S; Peter, Emilie; Petit-Demoulière, Benoit; Pickard, Amanda; Podrini, Christine; Potter, Paul; Pouilly, Laurent; Puk, Oliver; Richardson, David; Rousseau, Stephane; Quintanilla-Fend, Leticia; Quwailid, Mohamed M; Racz, Ildiko; Rathkolb, Birgit; Riet, Fabrice; Rossant, Janet; Roux, Michel; Rozman, Jan; Ryder, Ed; Salisbury, Jennifer; Santos, Luis; Schäble, Karl-Heinz; Schiller, Evelyn; Schrewe, Anja; Schulz, Holger; Steinkamp, Ralf; Simon, Michelle; Stewart, Michelle; Stöger, Claudia; Stöger, Tobias; Sun, Minxuan; Sunter, David; Teboul, Lydia; Tilly, Isabelle; Tocchini-Valentini, Glauco P; Tost, Monica; Treise, Irina; Vasseur, Laurent; Velot, Emilie; Vogt-Weisenhorn, Daniela; Wagner, Christelle; Walling, Alison; Weber, Bruno; Wendling, Olivia; Westerberg, Henrik; Willershäuser, Monja; Wolf, Eckhard; Wolter, Anne; Wood, Joe; Wurst, Wolfgang; Yildirim, Ali Önder; Zeh, Ramona; Zimmer, Andreas; Zimprich, Annemarie; Holmes, Chris; Steel, Karen P; Herault, Yann; Gailus-Durner, Valérie; Mallon, Ann-Marie; Brown, Steve Dm

    2015-09-01

    The function of the majority of genes in the mouse and human genomes remains unknown. The mouse embryonic stem cell knockout resource provides a basis for the characterization of relationships between genes and phenotypes. The EUMODIC consortium developed and validated robust methodologies for the broad-based phenotyping of knockouts through a pipeline comprising 20 disease-oriented platforms. We developed new statistical methods for pipeline design and data analysis aimed at detecting reproducible phenotypes with high power. We acquired phenotype data from 449 mutant alleles, representing 320 unique genes, of which half had no previous functional annotation. We captured data from over 27,000 mice, finding that 83% of the mutant lines are phenodeviant, with 65% demonstrating pleiotropy. Surprisingly, we found significant differences in phenotype annotation according to zygosity. New phenotypes were uncovered for many genes with previously unknown function, providing a powerful basis for hypothesis generation and further investigation in diverse systems.

  18. GGDonto ontology as a knowledge-base for genetic diseases and disorders of glycan metabolism and their causative genes.

    Science.gov (United States)

    Solovieva, Elena; Shikanai, Toshihide; Fujita, Noriaki; Narimatsu, Hisashi

    2018-04-18

    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. Many biomedical resources provide information about genetic disorders and genes involved in their pathogenesis, but resources focused on genetic disorders known to be related to glycan metabolism are lacking. With the aim of providing more comprehensive knowledge on genetic diseases and disorders of glycan biosynthesis and degradation, we enriched the content of the GDGDB database and improved the methods for data representation. We developed the Genetic Glyco-Diseases Ontology (GGDonto) and a RDF/SPARQL-based user interface using Semantic Web technologies. In particular, we represented the GGDonto content using Semantic Web languages, such as RDF, RDFS, SKOS, and OWL, and created an interactive user interface based on SPARQL queries. This user interface provides features to browse the hierarchy of the ontology, view detailed information on diseases and related genes, and find relevant background information. Moreover, it provides the ability to filter and search information by faceted and keyword searches. Focused on the molecular etiology, pathogenesis, and clinical manifestations of genetic diseases and disorders of glycan metabolism and developed as a knowledge-base for this scientific field, GGDonto provides comprehensive information on various topics, including links to aid the integration with other scientific resources. The availability and accessibility of this knowledge will help users better understand how genetic defects impact the

  19. Automatic extraction of gene ontology annotation and its correlation with clusters in protein networks

    Directory of Open Access Journals (Sweden)

    Mazo Ilya

    2007-07-01

    Full Text Available Abstract Background Uncovering cellular roles of a protein is a task of tremendous importance and complexity that requires dedicated experimental work as well as often sophisticated data mining and processing tools. Protein functions, often referred to as its annotations, are believed to manifest themselves through topology of the networks of inter-proteins interactions. In particular, there is a growing body of evidence that proteins performing the same function are more likely to interact with each other than with proteins with other functions. However, since functional annotation and protein network topology are often studied separately, the direct relationship between them has not been comprehensively demonstrated. In addition to having the general biological significance, such demonstration would further validate the data extraction and processing methods used to compose protein annotation and protein-protein interactions datasets. Results We developed a method for automatic extraction of protein functional annotation from scientific text based on the Natural Language Processing (NLP technology. For the protein annotation extracted from the entire PubMed, we evaluated the precision and recall rates, and compared the performance of the automatic extraction technology to that of manual curation used in public Gene Ontology (GO annotation. In the second part of our presentation, we reported a large-scale investigation into the correspondence between communities in the literature-based protein networks and GO annotation groups of functionally related proteins. We found a comprehensive two-way match: proteins within biological annotation groups form significantly denser linked network clusters than expected by chance and, conversely, densely linked network communities exhibit a pronounced non-random overlap with GO groups. We also expanded the publicly available GO biological process annotation using the relations extracted by our NLP technology

  20. GOssTo: a stand-alone application and a web tool for calculating semantic similarities on the Gene Ontology.

    Science.gov (United States)

    Caniza, Horacio; Romero, Alfonso E; Heron, Samuel; Yang, Haixuan; Devoto, Alessandra; Frasca, Marco; Mesiti, Marco; Valentini, Giorgio; Paccanaro, Alberto

    2014-08-01

    We present GOssTo, the Gene Ontology semantic similarity Tool, a user-friendly software system for calculating semantic similarities between gene products according to the Gene Ontology. GOssTo is bundled with six semantic similarity measures, including both term- and graph-based measures, and has extension capabilities to allow the user to add new similarities. Importantly, for any measure, GOssTo can also calculate the Random Walk Contribution that has been shown to greatly improve the accuracy of similarity measures. GOssTo is very fast, easy to use, and it allows the calculation of similarities on a genomic scale in a few minutes on a regular desktop machine. alberto@cs.rhul.ac.uk GOssTo is available both as a stand-alone application running on GNU/Linux, Windows and MacOS from www.paccanarolab.org/gossto and as a web application from www.paccanarolab.org/gosstoweb. The stand-alone application features a simple and concise command line interface for easy integration into high-throughput data processing pipelines. © The Author 2014. Published by Oxford University Press.

  1. Signalign: An Ontology of DNA as Signal for Comparative Gene Structure Prediction Using Information-Coding-and-Processing Techniques.

    Science.gov (United States)

    Yu, Ning; Guo, Xuan; Gu, Feng; Pan, Yi

    2016-03-01

    Conventional character-analysis-based techniques in genome analysis manifest three main shortcomings-inefficiency, inflexibility, and incompatibility. In our previous research, a general framework, called DNA As X was proposed for character-analysis-free techniques to overcome these shortcomings, where X is the intermediates, such as digit, code, signal, vector, tree, graph network, and so on. In this paper, we further implement an ontology of DNA As Signal, by designing a tool named Signalign for comparative gene structure analysis, in which DNA sequences are converted into signal series, processed by modified method of dynamic time warping and measured by signal-to-noise ratio (SNR). The ontology of DNA As Signal integrates the principles and concepts of other disciplines including information coding theory and signal processing into sequence analysis and processing. Comparing with conventional character-analysis-based methods, Signalign can not only have the equivalent or superior performance, but also enrich the tools and the knowledge library of computational biology by extending the domain from character/string to diverse areas. The evaluation results validate the success of the character-analysis-free technique for improved performances in comparative gene structure prediction.

  2. Expression profiling and gene ontology analysis in fathead minnow (Pimephales promelas) liver following exposure to pulp and paper mill effluents

    Energy Technology Data Exchange (ETDEWEB)

    Costigan, Shannon L.; Werner, Julieta; Ouellet, Jacob D.; Hill, Lauren G. [Department of Biology, Lakehead University, 955 Oliver Road, Ontario P7B 5E1, (Canada); Law, R. David, E-mail: dlaw@lakeheadu.ca [Department of Biology, Lakehead University, 955 Oliver Road, Ontario P7B 5E1, (Canada)

    2012-10-15

    Many studies link pulp and paper mill effluent (PPME) exposure to adverse effects in fish populations present in the mill receiving environments. These impacts are often characteristic of endocrine disruption and may include impaired reproduction, development and survival. While these physiological endpoints are well-characterized, the molecular mechanisms causing them are not yet understood. To investigate changes in gene transcription induced by exposure to a PPME at several stages of treatment, male and female fathead minnows (FHMs) were exposed for 6 days to 25% (v/v) secondary (biologically) treated kraft effluent (TK) or 100% (v/v) combined mill outfall (CMO) from a mill producing both kraft pulp and newsprint. The gene expression changes in the livers of these fish were analyzed using a 22 K oligonucleotide microarray. Exposure to TK or CMO resulted in significant changes in the expression levels of 105 and 238 targets in male FHMs and 296 and 133 targets in females, respectively. Targets were then functionally analyzed using gene ontology tools to identify the biological processes in fish hepatocytes that were affected by exposure to PPME after its secondary treatment. Proteolysis was affected in female FHMs exposed to both TK and CMO. In male FHMs, no processes were affected by TK exposure, while sterol, isoprenoid, steroid and cholesterol biosynthesis and electron transport were up-regulated by CMO exposure. The results presented in this study indicate that short-term exposure to PPMEs affects the expression of reproduction-related genes in the livers of both male and female FHMs, and that secondary treatment of PPMEs may not neutralize all of their metabolic effects in fish. Gene ontology analysis of microarray data may enable identification of biological processes altered by toxicant exposure and thus provide an additional tool for monitoring the impact of PPMEs on fish populations.

  3. Expression profiling and gene ontology analysis in fathead minnow (Pimephales promelas) liver following exposure to pulp and paper mill effluents

    International Nuclear Information System (INIS)

    Costigan, Shannon L.; Werner, Julieta; Ouellet, Jacob D.; Hill, Lauren G.; Law, R. David

    2012-01-01

    Many studies link pulp and paper mill effluent (PPME) exposure to adverse effects in fish populations present in the mill receiving environments. These impacts are often characteristic of endocrine disruption and may include impaired reproduction, development and survival. While these physiological endpoints are well-characterized, the molecular mechanisms causing them are not yet understood. To investigate changes in gene transcription induced by exposure to a PPME at several stages of treatment, male and female fathead minnows (FHMs) were exposed for 6 days to 25% (v/v) secondary (biologically) treated kraft effluent (TK) or 100% (v/v) combined mill outfall (CMO) from a mill producing both kraft pulp and newsprint. The gene expression changes in the livers of these fish were analyzed using a 22 K oligonucleotide microarray. Exposure to TK or CMO resulted in significant changes in the expression levels of 105 and 238 targets in male FHMs and 296 and 133 targets in females, respectively. Targets were then functionally analyzed using gene ontology tools to identify the biological processes in fish hepatocytes that were affected by exposure to PPME after its secondary treatment. Proteolysis was affected in female FHMs exposed to both TK and CMO. In male FHMs, no processes were affected by TK exposure, while sterol, isoprenoid, steroid and cholesterol biosynthesis and electron transport were up-regulated by CMO exposure. The results presented in this study indicate that short-term exposure to PPMEs affects the expression of reproduction-related genes in the livers of both male and female FHMs, and that secondary treatment of PPMEs may not neutralize all of their metabolic effects in fish. Gene ontology analysis of microarray data may enable identification of biological processes altered by toxicant exposure and thus provide an additional tool for monitoring the impact of PPMEs on fish populations.

  4. Quantum ontologies

    International Nuclear Information System (INIS)

    Stapp, H.P.

    1988-12-01

    Quantum ontologies are conceptions of the constitution of the universe that are compatible with quantum theory. The ontological orientation is contrasted to the pragmatic orientation of science, and reasons are given for considering quantum ontologies both within science, and in broader contexts. The principal quantum ontologies are described and evaluated. Invited paper at conference: Bell's Theorem, Quantum Theory, and Conceptions of the Universe, George Mason University, October 20-21, 1988. 16 refs

  5. Clinical phenotype-based gene prioritization: an initial study using semantic similarity and the human phenotype ontology.

    Science.gov (United States)

    Masino, Aaron J; Dechene, Elizabeth T; Dulik, Matthew C; Wilkens, Alisha; Spinner, Nancy B; Krantz, Ian D; Pennington, Jeffrey W; Robinson, Peter N; White, Peter S

    2014-07-21

    Exome sequencing is a promising method for diagnosing patients with a complex phenotype. However, variant interpretation relative to patient phenotype can be challenging in some scenarios, particularly clinical assessment of rare complex phenotypes. Each patient's sequence reveals many possibly damaging variants that must be individually assessed to establish clear association with patient phenotype. To assist interpretation, we implemented an algorithm that ranks a given set of genes relative to patient phenotype. The algorithm orders genes by the semantic similarity computed between phenotypic descriptors associated with each gene and those describing the patient. Phenotypic descriptor terms are taken from the Human Phenotype Ontology (HPO) and semantic similarity is derived from each term's information content. Model validation was performed via simulation and with clinical data. We simulated 33 Mendelian diseases with 100 patients per disease. We modeled clinical conditions by adding noise and imprecision, i.e. phenotypic terms unrelated to the disease and terms less specific than the actual disease terms. We ranked the causative gene against all 2488 HPO annotated genes. The median causative gene rank was 1 for the optimal and noise cases, 12 for the imprecision case, and 60 for the imprecision with noise case. Additionally, we examined a clinical cohort of subjects with hearing impairment. The disease gene median rank was 22. However, when also considering the patient's exome data and filtering non-exomic and common variants, the median rank improved to 3. Semantic similarity can rank a causative gene highly within a gene list relative to patient phenotype characteristics, provided that imprecision is mitigated. The clinical case results suggest that phenotype rank combined with variant analysis provides significant improvement over the individual approaches. We expect that this combined prioritization approach may increase accuracy and decrease effort for

  6. Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database.

    Directory of Open Access Journals (Sweden)

    Allan Peter Davis

    Full Text Available Strategies for discovering common molecular events among disparate diseases hold promise for improving understanding of disease etiology and expanding treatment options. One technique is to leverage curated datasets found in the public domain. The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/ manually curates chemical-gene, chemical-disease, and gene-disease interactions from the scientific literature. The use of official gene symbols in CTD interactions enables this information to be combined with the Gene Ontology (GO file from NCBI Gene. By integrating these GO-gene annotations with CTD's gene-disease dataset, we produce 753,000 inferences between 15,700 GO terms and 4,200 diseases, providing opportunities to explore presumptive molecular underpinnings of diseases and identify biological similarities. Through a variety of applications, we demonstrate the utility of this novel resource. As a proof-of-concept, we first analyze known repositioned drugs (e.g., raloxifene and sildenafil and see that their target diseases have a greater degree of similarity when comparing GO terms vs. genes. Next, a computational analysis predicts seemingly non-intuitive diseases (e.g., stomach ulcers and atherosclerosis as being similar to bipolar disorder, and these are validated in the literature as reported co-diseases. Additionally, we leverage other CTD content to develop testable hypotheses about thalidomide-gene networks to treat seemingly disparate diseases. Finally, we illustrate how CTD tools can rank a series of drugs as potential candidates for repositioning against B-cell chronic lymphocytic leukemia and predict cisplatin and the small molecule inhibitor JQ1 as lead compounds. The CTD dataset is freely available for users to navigate pathologies within the context of extensive biological processes, molecular functions, and cellular components conferred by GO. This inference set should aid researchers, bioinformaticists, and

  7. The Ontology for Biomedical Investigations.

    Science.gov (United States)

    Bandrowski, Anita; Brinkman, Ryan; Brochhausen, Mathias; Brush, Matthew H; Bug, Bill; Chibucos, Marcus C; Clancy, Kevin; Courtot, Mélanie; Derom, Dirk; Dumontier, Michel; Fan, Liju; Fostel, Jennifer; Fragoso, Gilberto; Gibson, Frank; Gonzalez-Beltran, Alejandra; Haendel, Melissa A; He, Yongqun; Heiskanen, Mervi; Hernandez-Boussard, Tina; Jensen, Mark; Lin, Yu; Lister, Allyson L; Lord, Phillip; Malone, James; Manduchi, Elisabetta; McGee, Monnie; Morrison, Norman; Overton, James A; Parkinson, Helen; Peters, Bjoern; Rocca-Serra, Philippe; Ruttenberg, Alan; Sansone, Susanna-Assunta; Scheuermann, Richard H; Schober, Daniel; Smith, Barry; Soldatova, Larisa N; Stoeckert, Christian J; Taylor, Chris F; Torniai, Carlo; Turner, Jessica A; Vita, Randi; Whetzel, Patricia L; Zheng, Jie

    2016-01-01

    The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed

  8. DOSE RESPONSE FROM HIGH THROUGHPUT GENE EXPRESSION STUDIES AND THE INFLUENCE OF TIME AND CELL LINE ON INFERRED MODE OF ACTION BY ONTOLOGIC ENRICHMENT (SOT)

    Science.gov (United States)

    Gene expression with ontologic enrichment and connectivity mapping tools is widely used to infer modes of action (MOA) for therapeutic drugs. Despite progress in high-throughput (HT) genomic systems, strategies suitable to identify industrial chemical MOA are needed. The L1000 is...

  9. HybridGO-Loc: mining hybrid features on gene ontology for predicting subcellular localization of multi-location proteins.

    Science.gov (United States)

    Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

    2014-01-01

    Protein subcellular localization prediction, as an essential step to elucidate the functions in vivo of proteins and identify drugs targets, has been extensively studied in previous decades. Instead of only determining subcellular localization of single-label proteins, recent studies have focused on predicting both single- and multi-location proteins. Computational methods based on Gene Ontology (GO) have been demonstrated to be superior to methods based on other features. However, existing GO-based methods focus on the occurrences of GO terms and disregard their relationships. This paper proposes a multi-label subcellular-localization predictor, namely HybridGO-Loc, that leverages not only the GO term occurrences but also the inter-term relationships. This is achieved by hybridizing the GO frequencies of occurrences and the semantic similarity between GO terms. Given a protein, a set of GO terms are retrieved by searching against the gene ontology database, using the accession numbers of homologous proteins obtained via BLAST search as the keys. The frequency of GO occurrences and semantic similarity (SS) between GO terms are used to formulate frequency vectors and semantic similarity vectors, respectively, which are subsequently hybridized to construct fusion vectors. An adaptive-decision based multi-label support vector machine (SVM) classifier is proposed to classify the fusion vectors. Experimental results based on recent benchmark datasets and a new dataset containing novel proteins show that the proposed hybrid-feature predictor significantly outperforms predictors based on individual GO features as well as other state-of-the-art predictors. For readers' convenience, the HybridGO-Loc server, which is for predicting virus or plant proteins, is available online at http://bioinfo.eie.polyu.edu.hk/HybridGoServer/.

  10. Argot2: a large scale function prediction tool relying on semantic similarity of weighted Gene Ontology terms.

    Science.gov (United States)

    Falda, Marco; Toppo, Stefano; Pescarolo, Alessandro; Lavezzo, Enrico; Di Camillo, Barbara; Facchinetti, Andrea; Cilia, Elisa; Velasco, Riccardo; Fontana, Paolo

    2012-03-28

    Predicting protein function has become increasingly demanding in the era of next generation sequencing technology. The task to assign a curator-reviewed function to every single sequence is impracticable. Bioinformatics tools, easy to use and able to provide automatic and reliable annotations at a genomic scale, are necessary and urgent. In this scenario, the Gene Ontology has provided the means to standardize the annotation classification with a structured vocabulary which can be easily exploited by computational methods. Argot2 is a web-based function prediction tool able to annotate nucleic or protein sequences from small datasets up to entire genomes. It accepts as input a list of sequences in FASTA format, which are processed using BLAST and HMMER searches vs UniProKB and Pfam databases respectively; these sequences are then annotated with GO terms retrieved from the UniProtKB-GOA database and the terms are weighted using the e-values from BLAST and HMMER. The weighted GO terms are processed according to both their semantic similarity relations described by the Gene Ontology and their associated score. The algorithm is based on the original idea developed in a previous tool called Argot. The entire engine has been completely rewritten to improve both accuracy and computational efficiency, thus allowing for the annotation of complete genomes. The revised algorithm has been already employed and successfully tested during in-house genome projects of grape and apple, and has proven to have a high precision and recall in all our benchmark conditions. It has also been successfully compared with Blast2GO, one of the methods most commonly employed for sequence annotation. The server is freely accessible at http://www.medcomp.medicina.unipd.it/Argot2.

  11. On the Use of Gene Ontology Annotations to Assess Functional Similarity among Orthologs and Paralogs: A Short Report.

    Directory of Open Access Journals (Sweden)

    Paul D Thomas

    Full Text Available A recent paper (Nehrt et al., PLoS Comput. Biol. 7:e1002073, 2011 has proposed a metric for the "functional similarity" between two genes that uses only the Gene Ontology (GO annotations directly derived from published experimental results. Applying this metric, the authors concluded that paralogous genes within the mouse genome or the human genome are more functionally similar on average than orthologous genes between these genomes, an unexpected result with broad implications if true. We suggest, based on both theoretical and empirical considerations, that this proposed metric should not be interpreted as a functional similarity, and therefore cannot be used to support any conclusions about the "ortholog conjecture" (or, more properly, the "ortholog functional conservation hypothesis". First, we reexamine the case studies presented by Nehrt et al. as examples of orthologs with divergent functions, and come to a very different conclusion: they actually exemplify how GO annotations for orthologous genes provide complementary information about conserved biological functions. We then show that there is a global ascertainment bias in the experiment-based GO annotations for human and mouse genes: particular types of experiments tend to be performed in different model organisms. We conclude that the reported statistical differences in annotations between pairs of orthologous genes do not reflect differences in biological function, but rather complementarity in experimental approaches. Our results underscore two general considerations for researchers proposing novel types of analysis based on the GO: 1 that GO annotations are often incomplete, potentially in a biased manner, and subject to an "open world assumption" (absence of an annotation does not imply absence of a function, and 2 that conclusions drawn from a novel, large-scale GO analysis should whenever possible be supported by careful, in-depth examination of examples, to help ensure the

  12. The National NeuroAIDS Tissue Consortium brain gene array: two types of HIV-associated neurocognitive impairment.

    Directory of Open Access Journals (Sweden)

    Benjamin B Gelman

    Full Text Available The National NeuroAIDS Tissue Consortium (NNTC performed a brain gene expression array to elucidate pathophysiologies of Human Immunodeficiency Virus type 1 (HIV-1-associated neurocognitive disorders.Twenty-four human subjects in four groups were examined A Uninfected controls; B HIV-1 infected subjects with no substantial neurocognitive impairment (NCI; C Infected with substantial NCI without HIV encephalitis (HIVE; D Infected with substantial NCI and HIVE. RNA from neocortex, white matter, and neostriatum was processed with the Affymetrix® array platform.With HIVE the HIV-1 RNA load in brain tissue was three log(10 units higher than other groups and over 1,900 gene probes were regulated. Interferon response genes (IFRGs, antigen presentation, complement components and CD163 antigen were strongly upregulated. In frontal neocortex downregulated neuronal pathways strongly dominated in HIVE, including GABA receptors, glutamate signaling, synaptic potentiation, axon guidance, clathrin-mediated endocytosis and 14-3-3 protein. Expression was completely different in neuropsychologically impaired subjects without HIVE. They had low brain HIV-1 loads, weak brain immune responses, lacked neuronally expressed changes in neocortex and exhibited upregulation of endothelial cell type transcripts. HIV-1-infected subjects with normal neuropsychological test results had upregulation of neuronal transcripts involved in synaptic transmission of neostriatal circuits.Two patterns of brain gene expression suggest that more than one pathophysiological process occurs in HIV-1-associated neurocognitive impairment. Expression in HIVE suggests that lowering brain HIV-1 replication might improve NCI, whereas NCI without HIVE may not respond in kind; array results suggest that modulation of transvascular signaling is a potentially promising approach. Striking brain regional differences highlighted the likely importance of circuit level disturbances in HIV/AIDS. In

  13. Transcriptome and Gene Ontology (GO) Enrichment Analysis Reveals Genes Involved in Biotin Metabolism That Affect L-Lysine Production in Corynebacterium glutamicum.

    Science.gov (United States)

    Kim, Hong-Il; Kim, Jong-Hyeon; Park, Young-Jin

    2016-03-09

    Corynebacterium glutamicum is widely used for amino acid production. In the present study, 543 genes showed a significant change in their mRNA expression levels in L-lysine-producing C. glutamicum ATCC21300 than that in the wild-type C. glutamicum ATCC13032. Among these 543 differentially expressed genes (DEGs), 28 genes were up- or downregulated. In addition, 454 DEGs were functionally enriched and categorized based on BLAST sequence homologies and gene ontology (GO) annotations using the Blast2GO software. Interestingly, NCgl0071 (bioB, encoding biotin synthase) was expressed at levels ~20-fold higher in the L-lysine-producing ATCC21300 strain than that in the wild-type ATCC13032 strain. Five other genes involved in biotin metabolism or transport--NCgl2515 (bioA, encoding adenosylmethionine-8-amino-7-oxononanoate aminotransferase), NCgl2516 (bioD, encoding dithiobiotin synthetase), NCgl1883, NCgl1884, and NCgl1885--were also expressed at significantly higher levels in the L-lysine-producing ATCC21300 strain than that in the wild-type ATCC13032 strain, which we determined using both next-generation RNA sequencing and quantitative real-time PCR analysis. When we disrupted the bioB gene in C. glutamicum ATCC21300, L-lysine production decreased by approximately 76%, and the three genes involved in biotin transport (NCgl1883, NCgl1884, and NCgl1885) were significantly downregulated. These results will be helpful to improve our understanding of C. glutamicum for industrial amino acid production.

  14. Investigating Correlation between Protein Sequence Similarity and Semantic Similarity Using Gene Ontology Annotations.

    Science.gov (United States)

    Ikram, Najmul; Qadir, Muhammad Abdul; Afzal, Muhammad Tanvir

    2018-01-01

    Sequence similarity is a commonly used measure to compare proteins. With the increasing use of ontologies, semantic (function) similarity is getting importance. The correlation between these measures has been applied in the evaluation of new semantic similarity methods, and in protein function prediction. In this research, we investigate the relationship between the two similarity methods. The results suggest absence of a strong correlation between sequence and semantic similarities. There is a large number of proteins with low sequence similarity and high semantic similarity. We observe that Pearson's correlation coefficient is not sufficient to explain the nature of this relationship. Interestingly, the term semantic similarity values above 0 and below 1 do not seem to play a role in improving the correlation. That is, the correlation coefficient depends only on the number of common GO terms in proteins under comparison, and the semantic similarity measurement method does not influence it. Semantic similarity and sequence similarity have a distinct behavior. These findings are of significant effect for future works on protein comparison, and will help understand the semantic similarity between proteins in a better way.

  15. An ontology-driven semantic mash-up of gene and biological pathway information: Application to the domain of nicotine dependence

    Science.gov (United States)

    Sahoo, Satya S.; Bodenreider, Olivier; Rutter, Joni L.; Skinner, Karen J.; Sheth, Amit P.

    2008-01-01

    Objectives This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. Methods We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Results Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Conclusion Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. Resource page http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/ PMID:18395495

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

    Science.gov (United States)

    Huang, Jingshan; Gutierrez, Fernando; Strachan, Harrison J; Dou, Dejing; Huang, Weili; Smith, Barry; Blake, Judith A; Eilbeck, Karen; Natale, Darren A; Lin, Yu; Wu, Bin; Silva, Nisansa de; Wang, Xiaowei; Liu, Zixing; Borchert, Glen M; Tan, Ming; Ruttenberg, Alan

    2016-01-01

    As a special class of non-coding RNAs (ncRNAs), microRNAs (miRNAs) perform important roles in numerous biological and pathological processes. The realization of miRNA functions depends largely on how miRNAs regulate specific target genes. It is therefore critical to identify, analyze, and cross-reference miRNA-target interactions to better explore and delineate miRNA functions. Semantic technologies can help in this regard. We previously developed a miRNA domain-specific application ontology, Ontology for MIcroRNA Target (OMIT), whose goal was to serve as a foundation for semantic annotation, data integration, and semantic search in the miRNA field. 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 data. Important changes in the current version OMIT are summarized as: (1) following a modularized ontology design (with 2559 terms imported from the NCRO ontology); (2) encoding all 1884 human miRNAs (vs. 300 in previous versions); and (3) setting up a GitHub project site along with an issue tracker for more effective community collaboration on the ontology development. The OMIT ontology is free and open to all users, accessible at: http://purl.obolibrary.org/obo/omit.owl. The OmniSearch system is also free and open to all users, accessible at: http://omnisearch.soc.southalabama.edu/index.php/Software.

  17. Ontological Planning

    Directory of Open Access Journals (Sweden)

    Ahmet Alkan

    2017-12-01

    • Is it possible to redefine ontology within the hierarchical structure of planning? We are going to seek answers to some of these questions within the limited scope of this paper and we are going to offer the rest for discussion by just asking them. In light of these assessments, drawing attention, based on ontological knowledge relying on the wholeness of universe, to the question, on macro level planning, of whether or not the ontological realities of man, energy and movements of thinking can provide macro data for planning on a universal level as important factors affecting mankind will be one of the limited objectives of the paper.

  18. Large-scale inference of gene function through phylogenetic annotation of Gene Ontology terms: case study of the apoptosis and autophagy cellular processes.

    Science.gov (United States)

    Feuermann, Marc; Gaudet, Pascale; Mi, Huaiyu; Lewis, Suzanna E; Thomas, Paul D

    2016-01-01

    We previously reported a paradigm for large-scale phylogenomic analysis of gene families that takes advantage of the large corpus of experimentally supported Gene Ontology (GO) annotations. This 'GO Phylogenetic Annotation' approach integrates GO annotations from evolutionarily related genes across ∼100 different organisms in the context of a gene family tree, in which curators build an explicit model of the evolution of gene functions. GO Phylogenetic Annotation models the gain and loss of functions in a gene family tree, which is used to infer the functions of uncharacterized (or incompletely characterized) gene products, even for human proteins that are relatively well studied. Here, we report our results from applying this paradigm to two well-characterized cellular processes, apoptosis and autophagy. This revealed several important observations with respect to GO annotations and how they can be used for function inference. Notably, we applied only a small fraction of the experimentally supported GO annotations to infer function in other family members. The majority of other annotations describe indirect effects, phenotypes or results from high throughput experiments. In addition, we show here how feedback from phylogenetic annotation leads to significant improvements in the PANTHER trees, the GO annotations and GO itself. Thus GO phylogenetic annotation both increases the quantity and improves the accuracy of the GO annotations provided to the research community. We expect these phylogenetically based annotations to be of broad use in gene enrichment analysis as well as other applications of GO annotations.Database URL: http://amigo.geneontology.org/amigo. © The Author(s) 2016. Published by Oxford University Press.

  19. The Use of Gene Ontology Term and KEGG Pathway Enrichment for Analysis of Drug Half-Life.

    Directory of Open Access Journals (Sweden)

    Yu-Hang Zhang

    Full Text Available A drug's biological half-life is defined as the time required for the human body to metabolize or eliminate 50% of the initial drug dosage. Correctly measuring the half-life of a given drug is helpful for the safe and accurate usage of the drug. In this study, we investigated which gene ontology (GO terms and biological pathways were highly related to the determination of drug half-life. The investigated drugs, with known half-lives, were analyzed based on their enrichment scores for associated GO terms and KEGG pathways. These scores indicate which GO terms or KEGG pathways the drug targets. The feature selection method, minimum redundancy maximum relevance, was used to analyze these GO terms and KEGG pathways and to identify important GO terms and pathways, such as sodium-independent organic anion transmembrane transporter activity (GO:0015347, monoamine transmembrane transporter activity (GO:0008504, negative regulation of synaptic transmission (GO:0050805, neuroactive ligand-receptor interaction (hsa04080, serotonergic synapse (hsa04726, and linoleic acid metabolism (hsa00591, among others. This analysis confirmed our results and may show evidence for a new method in studying drug half-lives and building effective computational methods for the prediction of drug half-lives.

  20. Lentiviral gene ontology (LeGO) vectors equipped with novel drug-selectable fluorescent proteins: new building blocks for cell marking and multi-gene analysis.

    Science.gov (United States)

    Weber, K; Mock, U; Petrowitz, B; Bartsch, U; Fehse, B

    2010-04-01

    Vector-encoded fluorescent proteins (FPs) facilitate unambiguous identification or sorting of gene-modified cells by fluorescence-activated cell sorting (FACS). Exploiting this feature, we have recently developed lentiviral gene ontology (LeGO) vectors (www.LentiGO-Vectors.de) for multi-gene analysis in different target cells. In this study, we extend the LeGO principle by introducing 10 different drug-selectable FPs created by fusing one of the five selection marker (protecting against blasticidin, hygromycin, neomycin, puromycin and zeocin) and one of the five FP genes (Cerulean, eGFP, Venus, dTomato and mCherry). All tested fusion proteins allowed both fluorescence-mediated detection and drug-mediated selection of LeGO-transduced cells. Newly generated codon-optimized hygromycin- and neomycin-resistance genes showed improved expression as compared with their ancestors. New LeGO constructs were produced at titers >10(6) per ml (for non-concentrated supernatants). We show efficient combinatorial marking and selection of various cells, including mesenchymal stem cells, simultaneously transduced with different LeGO constructs. Inclusion of the cytomegalovirus early enhancer/chicken beta-actin promoter into LeGO vectors facilitated robust transgene expression in and selection of neural stem cells and their differentiated progeny. We suppose that the new drug-selectable markers combining advantages of FACS and drug selection are well suited for numerous applications and vector systems. Their inclusion into LeGO vectors opens new possibilities for (stem) cell tracking and functional multi-gene analysis.

  1. The Gene Ontology Differs in Bursa of Fabricius Between Two Breeds of Ducks Post Hatching by Enriching the Differentially Expressed Genes

    Directory of Open Access Journals (Sweden)

    H Liu

    Full Text Available ABSTRACT The bursa of Fabricius (BF is the central humoral immune organ unique to birds. The present study investigated the possible difference on a molecular level between two duck breeds. The digital gene expression profiling (DGE technology was used to enrich the differentially expressed genes (DEGs in BF between the Jianchang and Nonghua-P strains of ducks. DGE data identified 195 DEGs in the bursa. Gene Ontology (GO analysis suggested that DEGs were mainly enriched in the metabolic pathways and ribosome components. Pathways analysis identified the spliceosome, RNA transport, RNA degradation process, Jak-STAT signaling pathway, TNF signaling pathway and B cell receptor signaling pathway. The results indicated that the main difference in the BF between the two duck strains was in the capabilities of protein formation and B cell development. These data have revealed the main divergence in the BF on a molecular level between genetically different duck breeds and may help to perform molecular breeding programs in poultry in the future.

  2. The use of semantic similarity measures for optimally integrating heterogeneous Gene Ontology data from large scale annotation pipelines

    Directory of Open Access Journals (Sweden)

    Gaston K Mazandu

    2014-08-01

    Full Text Available With the advancement of new high throughput sequencing technologies, there has been an increase in the number of genome sequencing projects worldwide, which has yielded complete genome sequences of human, animals and plants. Subsequently, several labs have focused on genome annotation, consisting of assigning functions to gene products, mostly using Gene Ontology (GO terms. As a consequence, there is an increased heterogeneity in annotations across genomes due to different approaches used by different pipelines to infer these annotations and also due to the nature of the GO structure itself. This makes a curator's task difficult, even if they adhere to the established guidelines for assessing these protein annotations. Here we develop a genome-scale approach for integrating GO annotations from different pipelines using semantic similarity measures. We used this approach to identify inconsistencies and similarities in functional annotations between orthologs of human and Drosophila melanogaster, to assess the quality of GO annotations derived from InterPro2GO mappings compared to manually annotated GO annotations for the Drosophila melanogaster proteome from a FlyBase dataset and human, and to filter GO annotation data for these proteomes. Results obtained indicate that an efficient integration of GO annotations eliminates redundancy up to 27.08 and 22.32% in the Drosophila melanogaster and human GO annotation datasets, respectively. Furthermore, we identified lack of and missing annotations for some orthologs, and annotation mismatches between InterPro2GO and manual pipelines in these two proteomes, thus requiring further curation. This simplifies and facilitates tasks of curators in assessing protein annotations, reduces redundancy and eliminates inconsistencies in large annotation datasets for ease of comparative functional genomics.

  3. [Using (1)H-nuclear magnetic resonance metabolomics and gene ontology to establish pathological staging model for esophageal cancer patients].

    Science.gov (United States)

    Chen, X; Wang, K; Chen, W; Jiang, H; Deng, P C; Li, Z J; Peng, J; Zhou, Z Y; Yang, H; Huang, G X; Zeng, J

    2016-07-01

    (ethanol amine, hydroxy-propionic acid, homocysteine and estriol) were eventually selected. gene ontology analysis showed that 54 enzymes and genes regulated the 4 key metabolic markers. The quantitative prediction model of esophageal cancer staging based on esophageal cancer NMR spectrum were established. Cross-validation results showed that the predicted effect was good (root mean square error=5.3, R(2)=0.47, P=0.036). The systems biology approaches based on metabolomics and enzyme-gene regulatory network analysis can be used to quantify the metabolic network disturbance of patients with advanced esophageal cancer, and to predict preoperative clinical staging of esophageal cancer patients by plasma NMR metabolomics.

  4. Delineation and interpretation of gene networks towards their effect in cellular physiology- a reverse engineering approach for the identification of critical molecular players, through the use of ontologies.

    Science.gov (United States)

    Moutselos, K; Maglogiannis, I; Chatziioannou, A

    2010-01-01

    Exploiting ontologies, provides clues regarding the involvement of certain molecular processes in the cellular phenotypic manifestation. However, identifying individual molecular actors (genes, proteins, etc.) for targeted biological validation in a generic, prioritized, fashion, based in objective measures of their effects in the cellular physiology, remains a challenge. In this work, a new meta-analysis algorithm is proposed for the holistic interpretation of the information captured in -omic experiments, that is showcased in a transcriptomic, dynamic, DNA microarray dataset, which examines the effect of mastic oil treatment in Lewis lung carcinoma cells. Through the use of the Gene Ontology this algorithm relates genes to specific cellular pathways and vice versa in order to further reverse engineer the critical role of specific genes, starting from the results of various statistical enrichment analyses. The algorithm is able to discriminate candidate hub-genes, implying critical biochemical cross-talk. Moreover, performance measures of the algorithm are derived, when evaluated with respect to the differential expression gene list of the dataset.

  5. SUGOI: automated ontology interchangeability

    CSIR Research Space (South Africa)

    Khan, ZC

    2015-04-01

    Full Text Available A foundational ontology can solve interoperability issues among the domain ontologies aligned to it. However, several foundational ontologies have been developed, hence such interoperability issues exist among domain ontologies. The novel SUGOI tool...

  6. Inferring ontology graph structures using OWL reasoning

    KAUST Repository

    Rodriguez-Garcia, Miguel Angel

    2018-01-05

    Ontologies are representations of a conceptualization of a domain. Traditionally, ontologies in biology were represented as directed acyclic graphs (DAG) which represent the backbone taxonomy and additional relations between classes. These graphs are widely exploited for data analysis in the form of ontology enrichment or computation of semantic similarity. More recently, ontologies are developed in a formal language such as the Web Ontology Language (OWL) and consist of a set of axioms through which classes are defined or constrained. While the taxonomy of an ontology can be inferred directly from the axioms of an ontology as one of the standard OWL reasoning tasks, creating general graph structures from OWL ontologies that exploit the ontologies\\' semantic content remains a challenge.We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies, we can identify relations between classes that are implied but not asserted and generate graph structures that encode for a large part of the ontologies\\' semantic content. We demonstrate the advantages of our method by applying it to inference of protein-protein interactions through semantic similarity over the Gene Ontology and demonstrate that performance is increased when graph structures are inferred using deductive inference according to our method. Our software and experiment results are available at http://github.com/bio-ontology-research-group/Onto2Graph .Onto2Graph is a method to generate graph structures from OWL ontologies using automated reasoning. The resulting graphs can be used for improved ontology visualization and ontology-based data analysis.

  7. Inferring ontology graph structures using OWL reasoning.

    Science.gov (United States)

    Rodríguez-García, Miguel Ángel; Hoehndorf, Robert

    2018-01-05

    Ontologies are representations of a conceptualization of a domain. Traditionally, ontologies in biology were represented as directed acyclic graphs (DAG) which represent the backbone taxonomy and additional relations between classes. These graphs are widely exploited for data analysis in the form of ontology enrichment or computation of semantic similarity. More recently, ontologies are developed in a formal language such as the Web Ontology Language (OWL) and consist of a set of axioms through which classes are defined or constrained. While the taxonomy of an ontology can be inferred directly from the axioms of an ontology as one of the standard OWL reasoning tasks, creating general graph structures from OWL ontologies that exploit the ontologies' semantic content remains a challenge. We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies, we can identify relations between classes that are implied but not asserted and generate graph structures that encode for a large part of the ontologies' semantic content. We demonstrate the advantages of our method by applying it to inference of protein-protein interactions through semantic similarity over the Gene Ontology and demonstrate that performance is increased when graph structures are inferred using deductive inference according to our method. Our software and experiment results are available at http://github.com/bio-ontology-research-group/Onto2Graph . Onto2Graph is a method to generate graph structures from OWL ontologies using automated reasoning. The resulting graphs can be used for improved ontology visualization and ontology-based data analysis.

  8. Polymorphisms in stromal genes and susceptibility to serous epithelial ovarian cancer: a report from the Ovarian Cancer Association Consortium.

    Directory of Open Access Journals (Sweden)

    Ernest K Amankwah

    Full Text Available Alterations in stromal tissue components can inhibit or promote epithelial tumorigenesis. Decorin (DCN and lumican (LUM show reduced stromal expression in serous epithelial ovarian cancer (sEOC. We hypothesized that common variants in these genes associate with risk. Associations with sEOC among Caucasians were estimated with odds ratios (OR among 397 cases and 920 controls in two U.S.-based studies (discovery set, 436 cases and 1,098 controls in Australia (replication set 1 and a consortium of 15 studies comprising 1,668 cases and 4,249 controls (replication set 2. The discovery set and replication set 1 (833 cases and 2,013 controls showed statistically homogeneous (P(heterogeneity≥0.48 decreased risks of sEOC at four variants: DCN rs3138165, rs13312816 and rs516115, and LUM rs17018765 (OR = 0.6 to 0.9; P(trend = 0.001 to 0.03. Results from replication set 2 were statistically homogeneous (P(heterogeneity≥0.13 and associated with increased risks at DCN rs3138165 and rs13312816, and LUM rs17018765: all ORs = 1.2; P(trend≤0.02. The ORs at the four variants were statistically heterogeneous across all 18 studies (P(heterogeneity≤0.03, which precluded combining. In post-hoc analyses, interactions were observed between each variant and recruitment period (P(interaction≤0.003, age at diagnosis (P(interaction = 0.04, and year of diagnosis (P(interaction = 0.05 in the five studies with available information (1,044 cases, 2,469 controls. We conclude that variants in DCN and LUM are not directly associated with sEOC, and that confirmation of possible effect modification of the variants by non-genetic factors is required.

  9. Ontology evolution in physics

    OpenAIRE

    Chan, Michael

    2013-01-01

    With the advent of reasoning problems in dynamic environments, there is an increasing need for automated reasoning systems to automatically adapt to unexpected changes in representations. In particular, the automation of the evolution of their ontologies needs to be enhanced without substantially sacrificing expressivity in the underlying representation. Revision of beliefs is not enough, as adding to or removing from beliefs does not change the underlying formal language. Gene...

  10. Drug-Gene Interactions of Antihypertensive Medications and Risk of Incident Cardiovascular Disease: A Pharmacogenomics Study from the CHARGE Consortium.

    Directory of Open Access Journals (Sweden)

    Joshua C Bis

    Full Text Available Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD, including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals.Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases.Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four

  11. BACTERIAL CONSORTIUM

    Directory of Open Access Journals (Sweden)

    Payel Sarkar

    2013-01-01

    Full Text Available Petroleum aromatic hydrocarbons like benzen e, toluene, ethyl benzene and xylene, together known as BTEX, has almost the same chemical structure. These aromatic hydrocarbons are released as pollutants in th e environment. This work was taken up to develop a solvent tolerant bacterial cons ortium that could degrade BTEX compounds as they all share a common chemical structure. We have isolated almost 60 different types of bacterial strains from different petroleum contaminated sites. Of these 60 bacterial strains almost 20 microorganisms were screene d on the basis of capability to tolerate high concentration of BTEX. Ten differe nt consortia were prepared and the compatibility of the bacterial strains within the consortia was checked by gram staining and BTEX tolerance level. Four successful mi crobial consortia were selected in which all the bacterial strains concomitantly grew in presence of high concentration of BTEX (10% of toluene, 10% of benzene 5% ethyl benzene and 1% xylene. Consortium #2 showed the highest growth rate in pr esence of BTEX. Degradation of BTEX by consortium #2 was monitored for 5 days by gradual decrease in the volume of the solvents. The maximum reduction observed wa s 85% in 5 days. Gas chromatography results also reveal that could completely degrade benzene and ethyl benzene within 48 hours. Almost 90% degradation of toluene and xylene in 48 hours was exhibited by consortium #2. It could also tolerate and degrade many industrial solvents such as chloroform, DMSO, acetonitrile having a wide range of log P values (0.03–3.1. Degradation of aromatic hydrocarbon like BTEX by a solvent tolerant bacterial consortium is greatly significant as it could degrade high concentration of pollutants compared to a bacterium and also reduces the time span of degradation.

  12. Building ontologies with basic formal ontology

    CERN Document Server

    Arp, Robert; Spear, Andrew D.

    2015-01-01

    In the era of "big data," science is increasingly information driven, and the potential for computers to store, manage, and integrate massive amounts of data has given rise to such new disciplinary fields as biomedical informatics. Applied ontology offers a strategy for the organization of scientific information in computer-tractable form, drawing on concepts not only from computer and information science but also from linguistics, logic, and philosophy. This book provides an introduction to the field of applied ontology that is of particular relevance to biomedicine, covering theoretical components of ontologies, best practices for ontology design, and examples of biomedical ontologies in use. After defining an ontology as a representation of the types of entities in a given domain, the book distinguishes between different kinds of ontologies and taxonomies, and shows how applied ontology draws on more traditional ideas from metaphysics. It presents the core features of the Basic Formal Ontology (BFO), now u...

  13. The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability.

    Science.gov (United States)

    Diehl, Alexander D; Meehan, Terrence F; Bradford, Yvonne M; Brush, Matthew H; Dahdul, Wasila M; Dougall, David S; He, Yongqun; Osumi-Sutherland, David; Ruttenberg, Alan; Sarntivijai, Sirarat; Van Slyke, Ceri E; Vasilevsky, Nicole A; Haendel, Melissa A; Blake, Judith A; Mungall, Christopher J

    2016-07-04

    The Cell Ontology (CL) is an OBO Foundry candidate ontology covering the domain of canonical, natural biological cell types. Since its inception in 2005, the CL has undergone multiple rounds of revision and expansion, most notably in its representation of hematopoietic cells. For in vivo cells, the CL focuses on vertebrates but provides general classes that can be used for other metazoans, which can be subtyped in species-specific ontologies. Recent work on the CL has focused on extending the representation of various cell types, and developing new modules in the CL itself, and in related ontologies in coordination with the CL. For example, the Kidney and Urinary Pathway Ontology was used as a template to populate the CL with additional cell types. In addition, subtypes of the class 'cell in vitro' have received improved definitions and labels to provide for modularity with the representation of cells in the Cell Line Ontology and Reagent Ontology. Recent changes in the ontology development methodology for CL include a switch from OBO to OWL for the primary encoding of the ontology, and an increasing reliance on logical definitions for improved reasoning. The CL is now mandated as a metadata standard for large functional genomics and transcriptomics projects, and is used extensively for annotation, querying, and analyses of cell type specific data in sequencing consortia such as FANTOM5 and ENCODE, as well as for the NIAID ImmPort database and the Cell Image Library. The CL is also a vital component used in the modular construction of other biomedical ontologies-for example, the Gene Ontology and the cross-species anatomy ontology, Uberon, use CL to support the consistent representation of cell types across different levels of anatomical granularity, such as tissues and organs. The ongoing improvements to the CL make it a valuable resource to both the OBO Foundry community and the wider scientific community, and we continue to experience increased interest in the

  14. GOASVM: a subcellular location predictor by incorporating term-frequency gene ontology into the general form of Chou's pseudo-amino acid composition.

    Science.gov (United States)

    Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

    2013-04-21

    Prediction of protein subcellular localization is an important yet challenging problem. Recently, several computational methods based on Gene Ontology (GO) have been proposed to tackle this problem and have demonstrated superiority over methods based on other features. Existing GO-based methods, however, do not fully use the GO information. This paper proposes an efficient GO method called GOASVM that exploits the information from the GO term frequencies and distant homologs to represent a protein in the general form of Chou's pseudo-amino acid composition. The method first selects a subset of relevant GO terms to form a GO vector space. Then for each protein, the method uses the accession number (AC) of the protein or the ACs of its homologs to find the number of occurrences of the selected GO terms in the Gene Ontology annotation (GOA) database as a means to construct GO vectors for support vector machines (SVMs) classification. With the advantages of GO term frequencies and a new strategy to incorporate useful homologous information, GOASVM can achieve a prediction accuracy of 72.2% on a new independent test set comprising novel proteins that were added to Swiss-Prot six years later than the creation date of the training set. GOASVM and Supplementary materials are available online at http://bioinfo.eie.polyu.edu.hk/mGoaSvmServer/GOASVM.html. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Ontology authoring with Forza

    CSIR Research Space (South Africa)

    Keet, CM

    2014-11-01

    Full Text Available Generic, reusable ontology elements, such as a foundational ontology's categories and part-whole relations, are essential for good and interoperable knowledge representation. Ontology developers, which include domain experts and novices, face...

  16. Ontological Surprises

    DEFF Research Database (Denmark)

    Leahu, Lucian

    2016-01-01

    a hybrid approach where machine learning algorithms are used to identify objects as well as connections between them; finally, it argues for remaining open to ontological surprises in machine learning as they may enable the crafting of different relations with and through technologies.......This paper investigates how we might rethink design as the technological crafting of human-machine relations in the context of a machine learning technique called neural networks. It analyzes Google’s Inceptionism project, which uses neural networks for image recognition. The surprising output...

  17. Anatomy Ontology Matching Using Markov Logic Networks

    Directory of Open Access Journals (Sweden)

    Chunhua Li

    2016-01-01

    Full Text Available The anatomy of model species is described in ontologies, which are used to standardize the annotations of experimental data, such as gene expression patterns. To compare such data between species, we need to establish relationships between ontologies describing different species. Ontology matching is a kind of solutions to find semantic correspondences between entities of different ontologies. Markov logic networks which unify probabilistic graphical model and first-order logic provide an excellent framework for ontology matching. We combine several different matching strategies through first-order logic formulas according to the structure of anatomy ontologies. Experiments on the adult mouse anatomy and the human anatomy have demonstrated the effectiveness of proposed approach in terms of the quality of result alignment.

  18. InfAcrOnt: calculating cross-ontology term similarities using information flow by a random walk

    OpenAIRE

    Cheng, Liang; Jiang, Yue; Ju, Hong; Sun, Jie; Peng, Jiajie; Zhou, Meng; Hu, Yang

    2018-01-01

    Background Since the establishment of the first biomedical ontology Gene Ontology (GO), the number of biomedical ontology has increased dramatically. Nowadays over 300 ontologies have been built including extensively used Disease Ontology (DO) and Human Phenotype Ontology (HPO). Because of the advantage of identifying novel relationships between terms, calculating similarity between ontology terms is one of the major tasks in this research area. Though similarities between terms within each o...

  19. Using Gene Ontology to describe the role of the neurexin-neuroligin-SHANK complex in human, mouse and rat and its relevance to autism.

    Science.gov (United States)

    Patel, Sejal; Roncaglia, Paola; Lovering, Ruth C

    2015-06-06

    People with an autistic spectrum disorder (ASD) display a variety of characteristic behavioral traits, including impaired social interaction, communication difficulties and repetitive behavior. This complex neurodevelopment disorder is known to be associated with a combination of genetic and environmental factors. Neurexins and neuroligins play a key role in synaptogenesis and neurexin-neuroligin adhesion is one of several processes that have been implicated in autism spectrum disorders. In this report we describe the manual annotation of a selection of gene products known to be associated with autism and/or the neurexin-neuroligin-SHANK complex and demonstrate how a focused annotation approach leads to the creation of more descriptive Gene Ontology (GO) terms, as well as an increase in both the number of gene product annotations and their granularity, thus improving the data available in the GO database. The manual annotations we describe will impact on the functional analysis of a variety of future autism-relevant datasets. Comprehensive gene annotation is an essential aspect of genomic and proteomic studies, as the quality of gene annotations incorporated into statistical analysis tools affects the effective interpretation of data obtained through genome wide association studies, next generation sequencing, proteomic and transcriptomic datasets.

  20. Didactical Ontologies

    Directory of Open Access Journals (Sweden)

    Steffen Mencke, Reiner Dumke

    2008-03-01

    Full Text Available Ontologies are a fundamental concept of theSemantic Web envisioned by Tim Berners-Lee [1]. Togetherwith explicit representation of the semantics of data formachine-accessibility such domain theories are the basis forintelligent next generation applications for the web andother areas of interest [2]. Their application for specialaspects within the domain of e-learning is often proposed tosupport the increasing complexity ([3], [4], [5], [6]. So theycan provide a better support for course generation orlearning scenario description [7]. By the modeling ofdidactics-related expertise and their provision for thecreators of courses many improvements like reuse, rapiddevelopment and of course increased learning performancebecome possible due to the separation from other aspects ofe-learning platforms as already proposed in [8].

  1. Gene expression profiling in susceptible interaction of grapevine with its fungal pathogen Eutypa lata: Extending MapMan ontology for grapevine

    Directory of Open Access Journals (Sweden)

    Usadel Björn

    2009-08-01

    Full Text Available Abstract Background Whole genome transcriptomics analysis is a very powerful approach because it gives an overview of the activity of genes in certain cells or tissue types. However, biological interpretation of such results can be rather tedious. MapMan is a software tool that displays large datasets (e.g. gene expression data onto diagrams of metabolic pathways or other processes and thus enables easier interpretation of results. The grapevine (Vitis vinifera genome sequence has recently become available bringing a new dimension into associated research. Two microarray platforms were designed based on the TIGR Gene Index database and used in several physiological studies. Results To enable easy and effective visualization of those and further experiments, annotation of Vitis vinifera Gene Index (VvGI version 5 to MapMan ontology was set up. Due to specificities of grape physiology, we have created new pictorial representations focusing on three selected pathways: carotenoid pathway, terpenoid pathway and phenylpropanoid pathway, the products of these pathways being important for wine aroma, flavour and colour, as well as plant defence against pathogens. This new tool was validated on Affymetrix microarrays data obtained during berry ripening and it allowed the discovery of new aspects in process regulation. We here also present results on transcriptional profiling of grape plantlets after exposal to the fungal pathogen Eutypa lata using Operon microarrays including visualization of results with MapMan. The data show that the genes induced in infected plants, encode pathogenesis related proteins and enzymes of the flavonoid metabolism, which are well known as being responsive to fungal infection. Conclusion The extension of MapMan ontology to grapevine together with the newly constructed pictorial representations for carotenoid, terpenoid and phenylpropanoid metabolism provide an alternative approach to the analysis of grapevine gene expression

  2. Markov Chain Ontology Analysis (MCOA).

    Science.gov (United States)

    Frost, H Robert; McCray, Alexa T

    2012-02-03

    Biomedical ontologies have become an increasingly critical lens through which researchers analyze the genomic, clinical and bibliographic data that fuels scientific research. Of particular relevance are methods, such as enrichment analysis, that quantify the importance of ontology classes relative to a collection of domain data. Current analytical techniques, however, remain limited in their ability to handle many important types of structural complexity encountered in real biological systems including class overlaps, continuously valued data, inter-instance relationships, non-hierarchical relationships between classes, semantic distance and sparse data. In this paper, we describe a methodology called Markov Chain Ontology Analysis (MCOA) and illustrate its use through a MCOA-based enrichment analysis application based on a generative model of gene activation. MCOA models the classes in an ontology, the instances from an associated dataset and all directional inter-class, class-to-instance and inter-instance relationships as a single finite ergodic Markov chain. The adjusted transition probability matrix for this Markov chain enables the calculation of eigenvector values that quantify the importance of each ontology class relative to other classes and the associated data set members. On both controlled Gene Ontology (GO) data sets created with Escherichia coli, Drosophila melanogaster and Homo sapiens annotations and real gene expression data extracted from the Gene Expression Omnibus (GEO), the MCOA enrichment analysis approach provides the best performance of comparable state-of-the-art methods. A methodology based on Markov chain models and network analytic metrics can help detect the relevant signal within large, highly interdependent and noisy data sets and, for applications such as enrichment analysis, has been shown to generate superior performance on both real and simulated data relative to existing state-of-the-art approaches.

  3. The MMI Device Ontology: Enabling Sensor Integration

    Science.gov (United States)

    Rueda, C.; Galbraith, N.; Morris, R. A.; Bermudez, L. E.; Graybeal, J.; Arko, R. A.; Mmi Device Ontology Working Group

    2010-12-01

    The Marine Metadata Interoperability (MMI) project has developed an ontology for devices to describe sensors and sensor networks. This ontology is implemented in the W3C Web Ontology Language (OWL) and provides an extensible conceptual model and controlled vocabularies for describing heterogeneous instrument types, with different data characteristics, and their attributes. It can help users populate metadata records for sensors; associate devices with their platforms, deployments, measurement capabilities and restrictions; aid in discovery of sensor data, both historic and real-time; and improve the interoperability of observational oceanographic data sets. We developed the MMI Device Ontology following a community-based approach. By building on and integrating other models and ontologies from related disciplines, we sought to facilitate semantic interoperability while avoiding duplication. Key concepts and insights from various communities, including the Open Geospatial Consortium (eg., SensorML and Observations and Measurements specifications), Semantic Web for Earth and Environmental Terminology (SWEET), and W3C Semantic Sensor Network Incubator Group, have significantly enriched the development of the ontology. Individuals ranging from instrument designers, science data producers and consumers to ontology specialists and other technologists contributed to the work. Applications of the MMI Device Ontology are underway for several community use cases. These include vessel-mounted multibeam mapping sonars for the Rolling Deck to Repository (R2R) program and description of diverse instruments on deepwater Ocean Reference Stations for the OceanSITES program. These trials involve creation of records completely describing instruments, either by individual instances or by manufacturer and model. Individual terms in the MMI Device Ontology can be referenced with their corresponding Uniform Resource Identifiers (URIs) in sensor-related metadata specifications (e

  4. Genetic polymorphisms of the GNRH1 and GNRHR genes and risk of breast cancer in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3

    Directory of Open Access Journals (Sweden)

    Lund Eiliv

    2009-07-01

    Full Text Available Abstract Background Gonadotropin releasing hormone (GNRH1 triggers the release of follicle stimulating hormone and luteinizing hormone from the pituitary. Genetic variants in the gene encoding GNRH1 or its receptor may influence breast cancer risk by modulating production of ovarian steroid hormones. We studied the association between breast cancer risk and polymorphisms in genes that code for GNRH1 and its receptor (GNRHR in the large National Cancer Institute Breast and Prostate Cancer Cohort Consortium (NCI-BPC3. Methods We sequenced exons of GNRH1 and GNRHR in 95 invasive breast cancer cases. Resulting single nucleotide polymorphisms (SNPs were genotyped and used to identify haplotype-tagging SNPs (htSNPS in a panel of 349 healthy women. The htSNPs were genotyped in 5,603 invasive breast cancer cases and 7,480 controls from the Cancer Prevention Study-II (CPS-II, European Prospective Investigation on Cancer and Nutrition (EPIC, Multiethnic Cohort (MEC, Nurses' Health Study (NHS, and Women's Health Study (WHS. Circulating levels of sex steroids (androstenedione, estradiol, estrone and testosterone were also measured in 4713 study subjects. Results Breast cancer risk was not associated with any polymorphism or haplotype in the GNRH1 and GNRHR genes, nor were there any statistically significant interactions with known breast cancer risk factors. Polymorphisms in these two genes were not strongly associated with circulating hormone levels. Conclusion Common variants of the GNRH1 and GNRHR genes are not associated with risk of invasive breast cancer in Caucasians.

  5. Genetic polymorphisms of the GNRH1 and GNRHR genes and risk of breast cancer in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3)

    International Nuclear Information System (INIS)

    Canzian, Federico; Calle, Eugenia E; Chanock, Stephen; Clavel-Chapelon, Francoise; Dossus, Laure; Feigelson, Heather Spencer; Haiman, Christopher A; Hankinson, Susan E; Hoover, Robert; Hunter, David J; Isaacs, Claudine; Kaaks, Rudolf; Lenner, Per; Lund, Eiliv; Overvad, Kim; Palli, Domenico; Pearce, Celeste Leigh; Quiros, Jose R; Riboli, Elio; Stram, Daniel O; Thomas, Gilles; Thun, Michael J; Cox, David G; Trichopoulos, Dimitrios; Gils, Carla H van; Ziegler, Regina G; Henderson, Katherine D; Henderson, Brian E; Berg, Christine; Bingham, Sheila; Boeing, Heiner; Buring, Julie

    2009-01-01

    Gonadotropin releasing hormone (GNRH1) triggers the release of follicle stimulating hormone and luteinizing hormone from the pituitary. Genetic variants in the gene encoding GNRH1 or its receptor may influence breast cancer risk by modulating production of ovarian steroid hormones. We studied the association between breast cancer risk and polymorphisms in genes that code for GNRH1 and its receptor (GNRHR) in the large National Cancer Institute Breast and Prostate Cancer Cohort Consortium (NCI-BPC3). We sequenced exons of GNRH1 and GNRHR in 95 invasive breast cancer cases. Resulting single nucleotide polymorphisms (SNPs) were genotyped and used to identify haplotype-tagging SNPs (htSNPS) in a panel of 349 healthy women. The htSNPs were genotyped in 5,603 invasive breast cancer cases and 7,480 controls from the Cancer Prevention Study-II (CPS-II), European Prospective Investigation on Cancer and Nutrition (EPIC), Multiethnic Cohort (MEC), Nurses' Health Study (NHS), and Women's Health Study (WHS). Circulating levels of sex steroids (androstenedione, estradiol, estrone and testosterone) were also measured in 4713 study subjects. Breast cancer risk was not associated with any polymorphism or haplotype in the GNRH1 and GNRHR genes, nor were there any statistically significant interactions with known breast cancer risk factors. Polymorphisms in these two genes were not strongly associated with circulating hormone levels. Common variants of the GNRH1 and GNRHR genes are not associated with risk of invasive breast cancer in Caucasians

  6. Hum-mPLoc 3.0: prediction enhancement of human protein subcellular localization through modeling the hidden correlations of gene ontology and functional domain features.

    Science.gov (United States)

    Zhou, Hang; Yang, Yang; Shen, Hong-Bin

    2017-03-15

    Protein subcellular localization prediction has been an important research topic in computational biology over the last decade. Various automatic methods have been proposed to predict locations for large scale protein datasets, where statistical machine learning algorithms are widely used for model construction. A key step in these predictors is encoding the amino acid sequences into feature vectors. Many studies have shown that features extracted from biological domains, such as gene ontology and functional domains, can be very useful for improving the prediction accuracy. However, domain knowledge usually results in redundant features and high-dimensional feature spaces, which may degenerate the performance of machine learning models. In this paper, we propose a new amino acid sequence-based human protein subcellular location prediction approach Hum-mPLoc 3.0, which covers 12 human subcellular localizations. The sequences are represented by multi-view complementary features, i.e. context vocabulary annotation-based gene ontology (GO) terms, peptide-based functional domains, and residue-based statistical features. To systematically reflect the structural hierarchy of the domain knowledge bases, we propose a novel feature representation protocol denoted as HCM (Hidden Correlation Modeling), which will create more compact and discriminative feature vectors by modeling the hidden correlations between annotation terms. Experimental results on four benchmark datasets show that HCM improves prediction accuracy by 5-11% and F 1 by 8-19% compared with conventional GO-based methods. A large-scale application of Hum-mPLoc 3.0 on the whole human proteome reveals proteins co-localization preferences in the cell. www.csbio.sjtu.edu.cn/bioinf/Hum-mPLoc3/. hbshen@sjtu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  7. Transcriptome Analysis of Porcine PBMCs Reveals the Immune Cascade Response and Gene Ontology Terms Related to Cell Death and Fibrosis in the Progression of Liver Failure

    Directory of Open Access Journals (Sweden)

    YiMin Zhang

    2018-01-01

    Full Text Available Background. The key gene sets involved in the progression of acute liver failure (ALF, which has a high mortality rate, remain unclear. This study aims to gain a deeper understanding of the transcriptional response of peripheral blood mononuclear cells (PBMCs following ALF. Methods. ALF was induced by D-galactosamine (D-gal in a porcine model. PBMCs were separated at time zero (baseline group, 36 h (failure group, and 60 h (dying group after D-gal injection. Transcriptional profiling was performed using RNA sequencing and analysed using DAVID bioinformatics resources. Results. Compared with the baseline group, 816 and 1,845 differentially expressed genes (DEGs were identified in the failure and dying groups, respectively. A total of five and two gene ontology (GO term clusters were enriched in 107 GO terms in the failure group and 154 GO terms in the dying group. These GO clusters were primarily immune-related, including genes regulating the inflammasome complex and toll-like receptor signalling pathways. Specifically, GO terms related to cell death, including apoptosis, pyroptosis, and autophagy, and those related to fibrosis, coagulation dysfunction, and hepatic encephalopathy were enriched. Seven Kyoto Encyclopedia of Genes and Genomes (KEGG pathways, cytokine-cytokine receptor interaction, hematopoietic cell lineage, lysosome, rheumatoid arthritis, malaria, and phagosome and pertussis pathways were mapped for DEGs in the failure group. All of these seven KEGG pathways were involved in the 19 KEGG pathways mapped in the dying group. Conclusion. We found that the dramatic PBMC transcriptome changes triggered by ALF progression was predominantly related to immune responses. The enriched GO terms related to cell death, fibrosis, and so on, as indicated by PBMC transcriptome analysis, seem to be useful in elucidating potential key gene sets in the progression of ALF. A better understanding of these gene sets might be of preventive or

  8. Polymorphism in the GALNT1 gene and epithelial ovarian cancer in non-Hispanic white women: the Ovarian Cancer Association Consortium

    DEFF Research Database (Denmark)

    Phelan, Catherine M; Tsai, Ya-Yu; Goode, Ellen L

    2010-01-01

    Aberrant glycosylation is a well-described hallmark of cancer. In a previous ovarian cancer case control study that examined polymorphisms in 26 glycosylation-associated genes, we found strong statistical evidence (P = 0.00017) that women who inherited two copies of a single-nucleotide polymorphism...... in the UDP-N-acetylgalactosamine:polypeptide N-acetylgalactosaminyltransferase, GALNT1, had decreased ovarian cancer risk. The current study attempted to replicate this observation. The GALNT1 single-nucleotide polymorphism rs17647532 was genotyped in 6,965 cases and 8,377 controls from 14 studies forming...... the Ovarian Cancer Association Consortium. The fixed effects estimate per rs17647532 allele was null (odds ratio, 0.99; 95% confidence interval, 0.92-1.07). When a recessive model was fit, the results were unchanged. Test for heterogeneity of the odds ratios revealed consistency across the 14 replication...

  9. Witnessing stressful events induces glutamatergic synapse pathway alterations and gene set enrichment of positive EPSP regulation within the VTA of adult mice: An ontology based approach

    Science.gov (United States)

    Brewer, Jacob S.

    It is well known that exposure to severe stress increases the risk for developing mood disorders. Currently, the neurobiological and genetic mechanisms underlying the functional effects of psychological stress are poorly understood. Presenting a major obstacle to the study of psychological stress is the inability of current animal models of stress to distinguish between physical and psychological stressors. A novel paradigm recently developed by Warren et al., is able to tease apart the effects of physical and psychological stress in adult mice by allowing these mice to "witness," the social defeat of another mouse thus removing confounding variables associated with physical stressors. Using this 'witness' model of stress and RNA-Seq technology, the current study aims to study the genetic effects of psychological stress. After, witnessing the social defeat of another mouse, VTA tissue was extracted, sequenced, and analyzed for differential expression. Since genes often work together in complex networks, a pathway and gene ontology (GO) analysis was performed using data from the differential expression analysis. The pathway and GO analyzes revealed a perturbation of the glutamatergic synapse pathway and an enrichment of positive excitatory post-synaptic potential regulation. This is consistent with the excitatory synapse theory of depression. Together these findings demonstrate a dysregulation of the mesolimbic reward pathway at the gene level as a result of psychological stress potentially contributing to depressive like behaviors.

  10. Comparing Relational and Ontological Triple Stores in Healthcare Domain

    Directory of Open Access Journals (Sweden)

    Ozgu Can

    2017-01-01

    Full Text Available Today’s technological improvements have made ubiquitous healthcare systems that converge into smart healthcare applications in order to solve patients’ problems, to communicate effectively with patients, and to improve healthcare service quality. The first step of building a smart healthcare information system is representing the healthcare data as connected, reachable, and sharable. In order to achieve this representation, ontologies are used to describe the healthcare data. Combining ontological healthcare data with the used and obtained data can be maintained by storing the entire health domain data inside big data stores that support both relational and graph-based ontological data. There are several big data stores and different types of big data sets in the healthcare domain. The goal of this paper is to determine the most applicable ontology data store for storing the big healthcare data. For this purpose, AllegroGraph and Oracle 12c data stores are compared based on their infrastructural capacity, loading time, and query response times. Hence, healthcare ontologies (GENE Ontology, Gene Expression Ontology (GEXO, Regulation of Transcription Ontology (RETO, Regulation of Gene Expression Ontology (REXO are used to measure the ontology loading time. Thereafter, various queries are constructed and executed for GENE ontology in order to measure the capacity and query response times for the performance comparison between AllegroGraph and Oracle 12c triple stores.

  11. Construction of ontology augmented networks for protein complex prediction.

    Science.gov (United States)

    Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian

    2013-01-01

    Protein complexes are of great importance in understanding the principles of cellular organization and function. The increase in available protein-protein interaction data, gene ontology and other resources make it possible to develop computational methods for protein complex prediction. Most existing methods focus mainly on the topological structure of protein-protein interaction networks, and largely ignore the gene ontology annotation information. In this article, we constructed ontology augmented networks with protein-protein interaction data and gene ontology, which effectively unified the topological structure of protein-protein interaction networks and the similarity of gene ontology annotations into unified distance measures. After constructing ontology augmented networks, a novel method (clustering based on ontology augmented networks) was proposed to predict protein complexes, which was capable of taking into account the topological structure of the protein-protein interaction network, as well as the similarity of gene ontology annotations. Our method was applied to two different yeast protein-protein interaction datasets and predicted many well-known complexes. The experimental results showed that (i) ontology augmented networks and the unified distance measure can effectively combine the structure closeness and gene ontology annotation similarity; (ii) our method is valuable in predicting protein complexes and has higher F1 and accuracy compared to other competing methods.

  12. XML, Ontologies, and Their Clinical Applications.

    Science.gov (United States)

    Yu, Chunjiang; Shen, Bairong

    2016-01-01

    The development of information technology has resulted in its penetration into every area of clinical research. Various clinical systems have been developed, which produce increasing volumes of clinical data. However, saving, exchanging, querying, and exploiting these data are challenging issues. The development of Extensible Markup Language (XML) has allowed the generation of flexible information formats to facilitate the electronic sharing of structured data via networks, and it has been used widely for clinical data processing. In particular, XML is very useful in the fields of data standardization, data exchange, and data integration. Moreover, ontologies have been attracting increased attention in various clinical fields in recent years. An ontology is the basic level of a knowledge representation scheme, and various ontology repositories have been developed, such as Gene Ontology and BioPortal. The creation of these standardized repositories greatly facilitates clinical research in related fields. In this chapter, we discuss the basic concepts of XML and ontologies, as well as their clinical applications.

  13. Semantic similarity between ontologies at different scales

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Qingpeng; Haglin, David J.

    2016-04-01

    In the past decade, existing and new knowledge and datasets has been encoded in different ontologies for semantic web and biomedical research. The size of ontologies is often very large in terms of number of concepts and relationships, which makes the analysis of ontologies and the represented knowledge graph computational and time consuming. As the ontologies of various semantic web and biomedical applications usually show explicit hierarchical structures, it is interesting to explore the trade-offs between ontological scales and preservation/precision of results when we analyze ontologies. This paper presents the first effort of examining the capability of this idea via studying the relationship between scaling biomedical ontologies at different levels and the semantic similarity values. We evaluate the semantic similarity between three Gene Ontology slims (Plant, Yeast, and Candida, among which the latter two belong to the same kingdom—Fungi) using four popular measures commonly applied to biomedical ontologies (Resnik, Lin, Jiang-Conrath, and SimRel). The results of this study demonstrate that with proper selection of scaling levels and similarity measures, we can significantly reduce the size of ontologies without losing substantial detail. In particular, the performance of Jiang-Conrath and Lin are more reliable and stable than that of the other two in this experiment, as proven by (a) consistently showing that Yeast and Candida are more similar (as compared to Plant) at different scales, and (b) small deviations of the similarity values after excluding a majority of nodes from several lower scales. This study provides a deeper understanding of the application of semantic similarity to biomedical ontologies, and shed light on how to choose appropriate semantic similarity measures for biomedical engineering.

  14. Assessment Applications of Ontologies.

    Science.gov (United States)

    Chung, Gregory K. W. K.; Niemi, David; Bewley, William L.

    This paper discusses the use of ontologies and their applications to assessment. An ontology provides a shared and common understanding of a domain that can be communicated among people and computational systems. The ontology captures one or more experts' conceptual representation of a domain expressed in terms of concepts and the relationships…

  15. International Lymphoma Epidemiology Consortium

    Science.gov (United States)

    The InterLymph Consortium, or formally the International Consortium of Investigators Working on Non-Hodgkin's Lymphoma Epidemiologic Studies, is an open scientific forum for epidemiologic research in non-Hodgkin's lymphoma.

  16. Ontologies vs. Classification Systems

    DEFF Research Database (Denmark)

    Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

    2009-01-01

    What is an ontology compared to a classification system? Is a taxonomy a kind of classification system or a kind of ontology? These are questions that we meet when working with people from industry and public authorities, who need methods and tools for concept clarification, for developing meta...... data sets or for obtaining advanced search facilities. In this paper we will present an attempt at answering these questions. We will give a presentation of various types of ontologies and briefly introduce terminological ontologies. Furthermore we will argue that classification systems, e.g. product...... classification systems and meta data taxonomies, should be based on ontologies....

  17. Toxicology ontology perspectives.

    Science.gov (United States)

    Hardy, Barry; Apic, Gordana; Carthew, Philip; Clark, Dominic; Cook, David; Dix, Ian; Escher, Sylvia; Hastings, Janna; Heard, David J; Jeliazkova, Nina; Judson, Philip; Matis-Mitchell, Sherri; Mitic, Dragana; Myatt, Glenn; Shah, Imran; Spjuth, Ola; Tcheremenskaia, Olga; Toldo, Luca; Watson, David; White, Andrew; Yang, Chihae

    2012-01-01

    The field of predictive toxicology requires the development of open, public, computable, standardized toxicology vocabularies and ontologies to support the applications required by in silico, in vitro, and in vivo toxicology methods and related analysis and reporting activities. In this article we review ontology developments based on a set of perspectives showing how ontologies are being used in predictive toxicology initiatives and applications. Perspectives on resources and initiatives reviewed include OpenTox, eTOX, Pistoia Alliance, ToxWiz, Virtual Liver, EU-ADR, BEL, ToxML, and Bioclipse. We also review existing ontology developments in neighboring fields that can contribute to establishing an ontological framework for predictive toxicology. A significant set of resources is already available to provide a foundation for an ontological framework for 21st century mechanistic-based toxicology research. Ontologies such as ToxWiz provide a basis for application to toxicology investigations, whereas other ontologies under development in the biological, chemical, and biomedical communities could be incorporated in an extended future framework. OpenTox has provided a semantic web framework for the implementation of such ontologies into software applications and linked data resources. Bioclipse developers have shown the benefit of interoperability obtained through ontology by being able to link their workbench application with remote OpenTox web services. Although these developments are promising, an increased international coordination of efforts is greatly needed to develop a more unified, standardized, and open toxicology ontology framework.

  18. Polymorphisms in stromal genes and susceptibility to serous epithelial ovarian cancer: a report from the Ovarian Cancer Association Consortium

    DEFF Research Database (Denmark)

    Amankwah, Ernest K; Wang, Qinggang; Schildkraut, Joellen M

    2011-01-01

    Alterations in stromal tissue components can inhibit or promote epithelial tumorigenesis. Decorin (DCN) and lumican (LUM) show reduced stromal expression in serous epithelial ovarian cancer (sEOC). We hypothesized that common variants in these genes associate with risk. Associations with sEOC among...

  19. Consortium analysis of gene and gene–folate interactions in purine and pyrimidine metabolism pathways with ovarian carcinoma risk

    DEFF Research Database (Denmark)

    Kelemen, Linda E; Terry, Kathryn L; Goodman, Marc T

    2014-01-01

    SCOPE: We reevaluated previously reported associations between variants in pathways of one-carbon (1-C) (folate) transfer genes and ovarian carcinoma (OC) risk, and in related pathways of purine and pyrimidine metabolism, and assessed interactions with folate intake. METHODS AND RESULTS: Odds rat...

  20. Lipids, lipid genes, and incident age-related macular degeneration: the three continent age-related macular degeneration consortium

    NARCIS (Netherlands)

    Klein, Ronald; Myers, Chelsea E.; Buitendijk, Gabriëlle H. S.; Rochtchina, Elena; Gao, Xiaoyi; de Jong, Paulus T. V. M.; Sivakumaran, Theru A.; Burlutsky, George; McKean-Cowdin, Roberta; Hofman, Albert; Iyengar, Sudha K.; Lee, Kristine E.; Stricker, Bruno H.; Vingerling, Johannes R.; Mitchell, Paul; Klein, Barbara E. K.; Klaver, Caroline C. W.; Wang, Jie Jin

    2014-01-01

    To describe associations of serum lipid levels and lipid pathway genes to the incidence of age-related macular degeneration (AMD). Meta-analysis. setting: Three population-based cohorts. population: A total of 6950 participants from the Beaver Dam Eye Study (BDES), Blue Mountains Eye Study (BMES),

  1. The International Mouse Phenotyping Consortium Web Portal, a unified point of access for knockout mice and related phenotyping data

    Science.gov (United States)

    Koscielny, Gautier; Yaikhom, Gagarine; Iyer, Vivek; Meehan, Terrence F.; Morgan, Hugh; Atienza-Herrero, Julian; Blake, Andrew; Chen, Chao-Kung; Easty, Richard; Di Fenza, Armida; Fiegel, Tanja; Grifiths, Mark; Horne, Alan; Karp, Natasha A.; Kurbatova, Natalja; Mason, Jeremy C.; Matthews, Peter; Oakley, Darren J.; Qazi, Asfand; Regnart, Jack; Retha, Ahmad; Santos, Luis A.; Sneddon, Duncan J.; Warren, Jonathan; Westerberg, Henrik; Wilson, Robert J.; Melvin, David G.; Smedley, Damian; Brown, Steve D. M.; Flicek, Paul; Skarnes, William C.; Mallon, Ann-Marie; Parkinson, Helen

    2014-01-01

    The International Mouse Phenotyping Consortium (IMPC) web portal (http://www.mousephenotype.org) provides the biomedical community with a unified point of access to mutant mice and rich collection of related emerging and existing mouse phenotype data. IMPC mouse clinics worldwide follow rigorous highly structured and standardized protocols for the experimentation, collection and dissemination of data. Dedicated ‘data wranglers’ work with each phenotyping center to collate data and perform quality control of data. An automated statistical analysis pipeline has been developed to identify knockout strains with a significant change in the phenotype parameters. Annotation with biomedical ontologies allows biologists and clinicians to easily find mouse strains with phenotypic traits relevant to their research. Data integration with other resources will provide insights into mammalian gene function and human disease. As phenotype data become available for every gene in the mouse, the IMPC web portal will become an invaluable tool for researchers studying the genetic contributions of genes to human diseases. PMID:24194600

  2. Integrating phenotype ontologies with PhenomeNET

    KAUST Repository

    Rodriguez-Garcia, Miguel Angel

    2017-12-19

    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. While not applicable to matching arbitrary ontologies, PhenomeNET can be used to identify related phenotypes in different species, including human, mouse, zebrafish, nematode worm, fruit fly, and yeast. Results Here, we apply the PhenomeNET to identify related classes from two phenotype and two disease ontologies using automated reasoning. We demonstrate that we can identify a large number of mappings, some of which require automated reasoning and cannot easily be identified through lexical approaches alone. Combining automated reasoning with lexical matching further improves results in aligning ontologies. Conclusions PhenomeNET can be used to align and integrate phenotype ontologies. The results can be utilized for biomedical analyses in which phenomena observed in model organisms are used to identify causative genes and mutations underlying human disease.

  3. Polymorphisms in stromal genes and susceptibility to serous epithelial ovarian cancer: a report from the Ovarian Cancer Association Consortium

    DEFF Research Database (Denmark)

    Amankwah, Ernest K; Wang, Qinggang; Schildkraut, Joellen M

    2011-01-01

    Alterations in stromal tissue components can inhibit or promote epithelial tumorigenesis. Decorin (DCN) and lumican (LUM) show reduced stromal expression in serous epithelial ovarian cancer (sEOC). We hypothesized that common variants in these genes associate with risk. Associations with sEOC among...... and replication set 1 (833 cases and 2,013 controls) showed statistically homogeneous (P(heterogeneity)≥0.48) decreased risks of sEOC at four variants: DCN rs3138165, rs13312816 and rs516115, and LUM rs17018765 (OR = 0.6 to 0.9; P(trend) = 0.001 to 0.03). Results from replication set 2 were statistically...... homogeneous (P(heterogeneity)≥0.13) and associated with increased risks at DCN rs3138165 and rs13312816, and LUM rs17018765: all ORs = 1.2; P(trend)≤0.02. The ORs at the four variants were statistically heterogeneous across all 18 studies (P(heterogeneity)≤0.03), which precluded combining. In post...

  4. Ontology Design of Influential People Identification Using Centrality

    Science.gov (United States)

    Maulana Awangga, Rolly; Yusril, Muhammad; Setyawan, Helmi

    2018-04-01

    Identifying influential people as a node in a graph theory commonly calculated by social network analysis. The social network data has the user as node and edge as relation forming a friend relation graph. This research is conducting different meaning of every nodes relation in the social network. Ontology was perfect match science to describe the social network data as conceptual and domain. Ontology gives essential relationship in a social network more than a current graph. Ontology proposed as a standard for knowledge representation for the semantic web by World Wide Web Consortium. The formal data representation use Resource Description Framework (RDF) and Web Ontology Language (OWL) which is strategic for Open Knowledge-Based website data. Ontology used in the semantic description for a relationship in the social network, it is open to developing semantic based relationship ontology by adding and modifying various and different relationship to have influential people as a conclusion. This research proposes a model using OWL and RDF for influential people identification in the social network. The study use degree centrality, between ness centrality, and closeness centrality measurement for data validation. As a conclusion, influential people identification in Facebook can use proposed Ontology model in the Group, Photos, Photo Tag, Friends, Events and Works data.

  5. Genetically based location from triploid populations and gene ontology of a 3.3-mb genome region linked to Alternaria brown spot resistance in citrus reveal clusters of resistance genes.

    Directory of Open Access Journals (Sweden)

    José Cuenca

    Full Text Available Genetic analysis of phenotypical traits and marker-trait association in polyploid species is generally considered as a challenge. In the present work, different approaches were combined taking advantage of the particular genetic structures of 2n gametes resulting from second division restitution (SDR to map a genome region linked to Alternaria brown spot (ABS resistance in triploid citrus progeny. ABS in citrus is a serious disease caused by the tangerine pathotype of the fungus Alternaria alternata. This pathogen produces ACT-toxin, which induces necrotic lesions on fruit and young leaves, defoliation and fruit drop in susceptible genotypes. It is a strong concern for triploid breeding programs aiming to produce seedless mandarin cultivars. The monolocus dominant inheritance of susceptibility, proposed on the basis of diploid population studies, was corroborated in triploid progeny. Bulk segregant analysis coupled with genome scan using a large set of genetically mapped SNP markers and targeted genetic mapping by half tetrad analysis, using SSR and SNP markers, allowed locating a 3.3 Mb genomic region linked to ABS resistance near the centromere of chromosome III. Clusters of resistance genes were identified by gene ontology analysis of this genomic region. Some of these genes are good candidates to control the dominant susceptibility to the ACT-toxin. SSR and SNP markers were developed for efficient early marker-assisted selection of ABS resistant hybrids.

  6. Genetically based location from triploid populations and gene ontology of a 3.3-mb genome region linked to Alternaria brown spot resistance in citrus reveal clusters of resistance genes.

    Science.gov (United States)

    Cuenca, José; Aleza, Pablo; Vicent, Antonio; Brunel, Dominique; Ollitrault, Patrick; Navarro, Luis

    2013-01-01

    Genetic analysis of phenotypical traits and marker-trait association in polyploid species is generally considered as a challenge. In the present work, different approaches were combined taking advantage of the particular genetic structures of 2n gametes resulting from second division restitution (SDR) to map a genome region linked to Alternaria brown spot (ABS) resistance in triploid citrus progeny. ABS in citrus is a serious disease caused by the tangerine pathotype of the fungus Alternaria alternata. This pathogen produces ACT-toxin, which induces necrotic lesions on fruit and young leaves, defoliation and fruit drop in susceptible genotypes. It is a strong concern for triploid breeding programs aiming to produce seedless mandarin cultivars. The monolocus dominant inheritance of susceptibility, proposed on the basis of diploid population studies, was corroborated in triploid progeny. Bulk segregant analysis coupled with genome scan using a large set of genetically mapped SNP markers and targeted genetic mapping by half tetrad analysis, using SSR and SNP markers, allowed locating a 3.3 Mb genomic region linked to ABS resistance near the centromere of chromosome III. Clusters of resistance genes were identified by gene ontology analysis of this genomic region. Some of these genes are good candidates to control the dominant susceptibility to the ACT-toxin. SSR and SNP markers were developed for efficient early marker-assisted selection of ABS resistant hybrids.

  7. MetaGO: Predicting Gene Ontology of Non-homologous Proteins Through Low-Resolution Protein Structure Prediction and Protein-Protein Network Mapping.

    Science.gov (United States)

    Zhang, Chengxin; Zheng, Wei; Freddolino, Peter L; Zhang, Yang

    2018-03-10

    Homology-based transferal remains the major approach to computational protein function annotations, but it becomes increasingly unreliable when the sequence identity between query and template decreases below 30%. We propose a novel pipeline, MetaGO, to deduce Gene Ontology attributes of proteins by combining sequence homology-based annotation with low-resolution structure prediction and comparison, and partner's homology-based protein-protein network mapping. The pipeline was tested on a large-scale set of 1000 non-redundant proteins from the CAFA3 experiment. Under the stringent benchmark conditions where templates with >30% sequence identity to the query are excluded, MetaGO achieves average F-measures of 0.487, 0.408, and 0.598, for Molecular Function, Biological Process, and Cellular Component, respectively, which are significantly higher than those achieved by other state-of-the-art function annotations methods. Detailed data analysis shows that the major advantage of the MetaGO lies in the new functional homolog detections from partner's homology-based network mapping and structure-based local and global structure alignments, the confidence scores of which can be optimally combined through logistic regression. These data demonstrate the power of using a hybrid model incorporating protein structure and interaction networks to deduce new functional insights beyond traditional sequence homology-based referrals, especially for proteins that lack homologous function templates. The MetaGO pipeline is available at http://zhanglab.ccmb.med.umich.edu/MetaGO/. Copyright © 2018. Published by Elsevier Ltd.

  8. Constructive Ontology Engineering

    Science.gov (United States)

    Sousan, William L.

    2010-01-01

    The proliferation of the Semantic Web depends on ontologies for knowledge sharing, semantic annotation, data fusion, and descriptions of data for machine interpretation. However, ontologies are difficult to create and maintain. In addition, their structure and content may vary depending on the application and domain. Several methods described in…

  9. Towards Agile Ontology Maintenance

    Science.gov (United States)

    Luczak-Rösch, Markus

    Ontologies are an appropriate means to represent knowledge on the Web. Research on ontology engineering reached practices for an integrative lifecycle support. However, a broader success of ontologies in Web-based information systems remains unreached while the more lightweight semantic approaches are rather successful. We assume, paired with the emerging trend of services and microservices on the Web, new dynamic scenarios gain momentum in which a shared knowledge base is made available to several dynamically changing services with disparate requirements. Our work envisions a step towards such a dynamic scenario in which an ontology adapts to the requirements of the accessing services and applications as well as the user's needs in an agile way and reduces the experts' involvement in ontology maintenance processes.

  10. Conceptual querying through ontologies

    DEFF Research Database (Denmark)

    Andreasen, Troels; Bulskov, Henrik

    2009-01-01

    is motivated by an obvious need for users to survey huge volumes of objects in query answers. An ontology formalism and a special notion of-instantiated ontology" are introduced. The latter is a structure reflecting the content in the document collection in that; it is a restriction of a general world......We present here ail approach to conceptual querying where the aim is, given a collection of textual database objects or documents, to target an abstraction of the entire database content in terms of the concepts appearing in documents, rather than the documents in the collection. The approach...... knowledge ontology to the concepts instantiated in the collection. The notion of ontology-based similarity is briefly described, language constructs for direct navigation and retrieval of concepts in the ontology are discussed and approaches to conceptual summarization are presented....

  11. Survey on Ontology Mapping

    Science.gov (United States)

    Zhu, Junwu

    To create a sharable semantic space in which the terms from different domain ontology or knowledge system, Ontology mapping become a hot research point in Semantic Web Community. In this paper, motivated factors of ontology mapping research are given firstly, and then 5 dominating theories and methods, such as information accessing technology, machine learning, linguistics, structure graph and similarity, are illustrated according their technology class. Before we analyses the new requirements and takes a long view, the contributions of these theories and methods are summarized in details. At last, this paper suggest to design a group of semantic connector with the ability of migration learning for OWL-2 extended with constrains and the ontology mapping theory of axiom, so as to provide a new methodology for ontology mapping.

  12. Annotating breast cancer microarray samples using ontologies

    Science.gov (United States)

    Liu, Hongfang; Li, Xin; Yoon, Victoria; Clarke, Robert

    2008-01-01

    As the most common cancer among women, breast cancer results from the accumulation of mutations in essential genes. Recent advance in high-throughput gene expression microarray technology has inspired researchers to use the technology to assist breast cancer diagnosis, prognosis, and treatment prediction. However, the high dimensionality of microarray experiments and public access of data from many experiments have caused inconsistencies which initiated the development of controlled terminologies and ontologies for annotating microarray experiments, such as the standard microarray Gene Expression Data (MGED) ontology (MO). In this paper, we developed BCM-CO, an ontology tailored specifically for indexing clinical annotations of breast cancer microarray samples from the NCI Thesaurus. Our research showed that the coverage of NCI Thesaurus is very limited with respect to i) terms used by researchers to describe breast cancer histology (covering 22 out of 48 histology terms); ii) breast cancer cell lines (covering one out of 12 cell lines); and iii) classes corresponding to the breast cancer grading and staging. By incorporating a wider range of those terms into BCM-CO, we were able to indexed breast cancer microarray samples from GEO using BCM-CO and MGED ontology and developed a prototype system with web interface that allows the retrieval of microarray data based on the ontology annotations. PMID:18999108

  13. Quality control for terms and definitions in ontologies and taxonomies

    Directory of Open Access Journals (Sweden)

    Rüegg Alexander

    2006-04-01

    Full Text Available Abstract Background Ontologies and taxonomies are among the most important computational resources for molecular biology and bioinformatics. A series of recent papers has shown that the Gene Ontology (GO, the most prominent taxonomic resource in these fields, is marked by flaws of certain characteristic types, which flow from a failure to address basic ontological principles. As yet, no methods have been proposed which would allow ontology curators to pinpoint flawed terms or definitions in ontologies in a systematic way. Results We present computational methods that automatically identify terms and definitions which are defined in a circular or unintelligible way. We further demonstrate the potential of these methods by applying them to isolate a subset of 6001 problematic GO terms. By automatically aligning GO with other ontologies and taxonomies we were able to propose alternative synonyms and definitions for some of these problematic terms. This allows us to demonstrate that these other resources do not contain definitions superior to those supplied by GO. Conclusion Our methods provide reliable indications of the quality of terms and definitions in ontologies and taxonomies. Further, they are well suited to assist ontology curators in drawing their attention to those terms that are ill-defined. We have further shown the limitations of ontology mapping and alignment in assisting ontology curators in rectifying problems, thus pointing to the need for manual curation.

  14. Practical ontologies for information professionals

    CERN Document Server

    AUTHOR|(CDS)2071712

    2016-01-01

    Practical Ontologies for Information Professionals provides an introduction to ontologies and their development, an essential tool for fighting back against information overload. The development of robust and widely used ontologies is an increasingly important tool in the fight against information overload. The publishing and sharing of explicit explanations for a wide variety of conceptualizations, in a machine readable format, has the power to both improve information retrieval and identify new knowledge. This new book provides an accessible introduction to the following: * What is an ontology? Defining the concept and why it is increasingly important to the information professional * Ontologies and the semantic web * Existing ontologies, such as SKOS, OWL, FOAF, schema.org, and the DBpedia Ontology * Adopting and building ontologies, showing how to avoid repetition of work and how to build a simple ontology with Protege * Interrogating semantic web ontologies * The future of ontologies and the role of the ...

  15. Ontological foundations for evolutionary economics: A Darwinian social ontology

    NARCIS (Netherlands)

    Stoelhorst, J.W.

    2008-01-01

    The purpose of this paper is to further the project of generalized Darwinism by developing a social ontology on the basis of a combined commitment to ontological continuity and ontological commonality. Three issues that are central to the development of a social ontology are addressed: (1) the

  16. The Planteome database: an integrated resource for reference ontologies, plant genomics and phenomics

    Science.gov (United States)

    Cooper, Laurel; Meier, Austin; Laporte, Marie-Angélique; Elser, Justin L; Mungall, Chris; Sinn, Brandon T; Cavaliere, Dario; Carbon, Seth; Dunn, Nathan A; Smith, Barry; Qu, Botong; Preece, Justin; Zhang, Eugene; Todorovic, Sinisa; Gkoutos, Georgios; Doonan, John H; Stevenson, Dennis W; Arnaud, Elizabeth

    2018-01-01

    Abstract The Planteome project (http://www.planteome.org) provides a suite of reference and species-specific ontologies for plants and annotations to genes and phenotypes. Ontologies serve as common standards for semantic integration of a large and growing corpus of plant genomics, phenomics and genetics data. The reference ontologies include the Plant Ontology, Plant Trait Ontology and the Plant Experimental Conditions Ontology developed by the Planteome project, along with the Gene Ontology, Chemical Entities of Biological Interest, Phenotype and Attribute Ontology, and others. The project also provides access to species-specific Crop Ontologies developed by various plant breeding and research communities from around the world. We provide integrated data on plant traits, phenotypes, and gene function and expression from 95 plant taxa, annotated with reference ontology terms. The Planteome project is developing a plant gene annotation platform; Planteome Noctua, to facilitate community engagement. All the Planteome ontologies are publicly available and are maintained at the Planteome GitHub site (https://github.com/Planteome) for sharing, tracking revisions and new requests. The annotated data are freely accessible from the ontology browser (http://browser.planteome.org/amigo) and our data repository. PMID:29186578

  17. Perspectives on ontology learning

    CERN Document Server

    Lehmann, J

    2014-01-01

    Perspectives on Ontology Learning brings together researchers and practitioners from different communities − natural language processing, machine learning, and the semantic web − in order to give an interdisciplinary overview of recent advances in ontology learning.Starting with a comprehensive introduction to the theoretical foundations of ontology learning methods, the edited volume presents the state-of-the-start in automated knowledge acquisition and maintenance. It outlines future challenges in this area with a special focus on technologies suitable for pushing the boundaries beyond the c

  18. Data mining for ontology development.

    Energy Technology Data Exchange (ETDEWEB)

    Davidson, George S.; Strasburg, Jana (Pacific Northwest National Laboratory, Richland, WA); Stampf, David (Brookhaven National Laboratory, Upton, NY); Neymotin,Lev (Brookhaven National Laboratory, Upton, NY); Czajkowski, Carl (Brookhaven National Laboratory, Upton, NY); Shine, Eugene (Savannah River National Laboratory, Aiken, SC); Bollinger, James (Savannah River National Laboratory, Aiken, SC); Ghosh, Vinita (Brookhaven National Laboratory, Upton, NY); Sorokine, Alexandre (Oak Ridge National Laboratory, Oak Ridge, TN); Ferrell, Regina (Oak Ridge National Laboratory, Oak Ridge, TN); Ward, Richard (Oak Ridge National Laboratory, Oak Ridge, TN); Schoenwald, David Alan

    2010-06-01

    A multi-laboratory ontology construction effort during the summer and fall of 2009 prototyped an ontology for counterfeit semiconductor manufacturing. This effort included an ontology development team and an ontology validation methods team. Here the third team of the Ontology Project, the Data Analysis (DA) team reports on their approaches, the tools they used, and results for mining literature for terminology pertinent to counterfeit semiconductor manufacturing. A discussion of the value of ontology-based analysis is presented, with insights drawn from other ontology-based methods regularly used in the analysis of genomic experiments. Finally, suggestions for future work are offered.

  19. Using genetics to test the causal relationship of total adiposity and periodontitis: Mendelian randomization analyses in the Gene-Lifestyle Interactions and Dental Endpoints (GLIDE) Consortium

    Science.gov (United States)

    Shungin, Dmitry; Cornelis, Marilyn C; Divaris, Kimon; Holtfreter, Birte; Shaffer, John R; Yu, Yau-Hua; Barros, Silvana P; Beck, James D; Biffar, Reiner; Boerwinkle, Eric A; Crout, Richard J.; Ganna, Andrea; Hallmans, Goran; Hindy, George; Hu, Frank B; Kraft, Peter; McNeil, Daniel W; Melander, Olle; Moss, Kevin L; North, Kari E; Orho-Melander, Marju; Pedersen, Nancy L; Ridker, Paul M; Rimm, Eric B; Rose, Lynda M; Rukh, Gull; Teumer, Alexander; Weyant, Robert J; Chasman, Daniel I; Joshipura, Kaumudi; Kocher, Thomas; Magnusson, Patrik KE; Marazita, Mary L; Nilsson, Peter; Offenbacher, Steve; Davey Smith, George; Lundberg, Pernilla; Palmer, Tom M; Timpson, Nicholas J; Johansson, Ingegerd; Franks, Paul W

    2015-01-01

    Background: The observational relationship between obesity and periodontitis is widely known, yet causal evidence is lacking. Our objective was to investigate causal associations between periodontitis and body mass index (BMI). Methods: We performed Mendelian randomization analyses with BMI-associated loci combined in a genetic risk score (GRS) as the instrument for BMI. All analyses were conducted within the Gene-Lifestyle Interactions and Dental Endpoints (GLIDE) Consortium in 13 studies from Europe and the USA, including 49 066 participants with clinically assessed (seven studies, 42.1% of participants) and self-reported (six studies, 57.9% of participants) periodontitis and genotype data (17 672/31 394 with/without periodontitis); 68 761 participants with BMI and genotype data; and 57 871 participants (18 881/38 990 with/without periodontitis) with data on BMI and periodontitis. Results: In the observational meta-analysis of all participants, the pooled crude observational odds ratio (OR) for periodontitis was 1.13 [95% confidence interval (CI): 1.03, 1.24] per standard deviation increase of BMI. Controlling for potential confounders attenuated this estimate (OR = 1.08; 95% CI:1.03, 1.12). For clinically assessed periodontitis, corresponding ORs were 1.25 (95% CI: 1.10, 1.42) and 1.13 (95% CI: 1.10, 1.17), respectively. In the genetic association meta-analysis, the OR for periodontitis was 1.01 (95% CI: 0.99, 1.03) per GRS unit (per one effect allele) in all participants and 1.00 (95% CI: 0.97, 1.03) in participants with clinically assessed periodontitis. The instrumental variable meta-analysis of all participants yielded an OR of 1.05 (95% CI: 0.80, 1.38) per BMI standard deviation, and 0.90 (95% CI: 0.56, 1.46) in participants with clinical data. Conclusions: Our study does not support total adiposity as a causal risk factor for periodontitis, as the point estimate is very close to the null in the causal inference analysis, with wide

  20. Ontology of fractures

    Science.gov (United States)

    Zhong, Jian; Aydina, Atilla; McGuinness, Deborah L.

    2009-03-01

    Fractures are fundamental structures in the Earth's crust and they can impact many societal and industrial activities including oil and gas exploration and production, aquifer management, CO 2 sequestration, waste isolation, the stabilization of engineering structures, and assessing natural hazards (earthquakes, volcanoes, and landslides). Therefore, an ontology which organizes the concepts of fractures could help facilitate a sound education within, and communication among, the highly diverse professional and academic community interested in the problems cited above. We developed a process-based ontology that makes explicit specifications about fractures, their properties, and the deformation mechanisms which lead to their formation and evolution. Our ontology emphasizes the relationships among concepts such as the factors that influence the mechanism(s) responsible for the formation and evolution of specific fracture types. Our ontology is a valuable resource with a potential to applications in a number of fields utilizing recent advances in Information Technology, specifically for digital data and information in computers, grids, and Web services.

  1. A Method for Evaluating and Standardizing Ontologies

    Science.gov (United States)

    Seyed, Ali Patrice

    2012-01-01

    The Open Biomedical Ontology (OBO) Foundry initiative is a collaborative effort for developing interoperable, science-based ontologies. The Basic Formal Ontology (BFO) serves as the upper ontology for the domain-level ontologies of OBO. BFO is an upper ontology of types as conceived by defenders of realism. Among the ontologies developed for OBO…

  2. Manufacturing ontology through templates

    Directory of Open Access Journals (Sweden)

    Diciuc Vlad

    2017-01-01

    Full Text Available The manufacturing industry contains a high volume of knowhow and of high value, much of it being held by key persons in the company. The passing of this know-how is the basis of manufacturing ontology. Among other methods like advanced filtering and algorithm based decision making, one way of handling the manufacturing ontology is via templates. The current paper tackles this approach and highlights the advantages concluding with some recommendations.

  3. The Electronic Notebook Ontology

    OpenAIRE

    Chalk, Stuart

    2016-01-01

    Science is rapidly being brought into the electronic realm and electronic laboratory notebooks (ELN) are a big part of this activity. The representation of the scientific process in the context of an ELN is an important component to making the data recorded in ELNs semantically integrated. This presentation will outline initial developments of an Electronic Notebook Ontology (ENO) that will help tie together the ExptML ontology, HCLS Community Profile data descriptions, and the VIVO-ISF ontol...

  4. Ontology Update in the Cognitive Model of Ontology Learning

    Directory of Open Access Journals (Sweden)

    Zhang De-Hai

    2016-01-01

    Full Text Available Ontology has been used in many hot-spot fields, but most ontology construction methods are semiautomatic, and the construction process of ontology is still a tedious and painstaking task. In this paper, a kind of cognitive models is presented for ontology learning which can simulate human being’s learning from world. In this model, the cognitive strategies are applied with the constrained axioms. Ontology update is a key step when the new knowledge adds into the existing ontology and conflict with old knowledge in the process of ontology learning. This proposal designs and validates the method of ontology update based on the axiomatic cognitive model, which include the ontology update postulates, axioms and operations of the learning model. It is proved that these operators subject to the established axiom system.

  5. Community Hospital Telehealth Consortium

    National Research Council Canada - National Science Library

    Williams, Elton

    2004-01-01

    The Community Hospital Telehealth Consortium is a unique, forward-thinking, community-based healthcare service project organized around 5 not-for-profit community hospitals located throughout Louisiana and Mississippi...

  6. Community Hospital Telehealth Consortium

    National Research Council Canada - National Science Library

    Williams, Elton

    2003-01-01

    The Community Hospital Telehealth Consortium is a unique, forward-thinking, community-based healthcare service project organized around 5 not-for-profit community hospitals located throughout Louisiana and Mississippi...

  7. Community Hospital Telehealth Consortium

    National Research Council Canada - National Science Library

    Williams, Jr, Elton L

    2007-01-01

    The Community Hospital Telehealth Consortium is a unique, forward-thinking, community-based healthcare service project organized around 5 not-for-profit community hospitals located throughout Louisiana and Mississippi...

  8. Mining rare associations between biological ontologies.

    Science.gov (United States)

    Benites, Fernando; Simon, Svenja; Sapozhnikova, Elena

    2014-01-01

    The constantly increasing volume and complexity of available biological data requires new methods for their management and analysis. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining cross and intra-ontology pairwise generalized association rules. Its advantage is sensitivity to rare associations, for these are important for biologists. We propose a new class of interestingness measures designed for hierarchically organized rules. These measures allow one to select the most important rules and to take into account rare cases. They favor rules with an actual interestingness value that exceeds the expected value. The latter is calculated taking into account the parent rule. We demonstrate this approach by applying it to the analysis of data from Gene Ontology and GPCR databases. Our objective is to discover interesting relations between two different ontologies or parts of a single ontology. The association rules that are thus discovered can provide the user with new knowledge about underlying biological processes or help improve annotation consistency. The obtained results show that produced rules represent meaningful and quite reliable associations.

  9. Mining rare associations between biological ontologies.

    Directory of Open Access Journals (Sweden)

    Fernando Benites

    Full Text Available The constantly increasing volume and complexity of available biological data requires new methods for their management and analysis. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining cross and intra-ontology pairwise generalized association rules. Its advantage is sensitivity to rare associations, for these are important for biologists. We propose a new class of interestingness measures designed for hierarchically organized rules. These measures allow one to select the most important rules and to take into account rare cases. They favor rules with an actual interestingness value that exceeds the expected value. The latter is calculated taking into account the parent rule. We demonstrate this approach by applying it to the analysis of data from Gene Ontology and GPCR databases. Our objective is to discover interesting relations between two different ontologies or parts of a single ontology. The association rules that are thus discovered can provide the user with new knowledge about underlying biological processes or help improve annotation consistency. The obtained results show that produced rules represent meaningful and quite reliable associations.

  10. DeMO: An Ontology for Discrete-event Modeling and Simulation

    Science.gov (United States)

    Silver, Gregory A; Miller, John A; Hybinette, Maria; Baramidze, Gregory; York, William S

    2011-01-01

    Several fields have created ontologies for their subdomains. For example, the biological sciences have developed extensive ontologies such as the Gene Ontology, which is considered a great success. Ontologies could provide similar advantages to the Modeling and Simulation community. They provide a way to establish common vocabularies and capture knowledge about a particular domain with community-wide agreement. Ontologies can support significantly improved (semantic) search and browsing, integration of heterogeneous information sources, and improved knowledge discovery capabilities. This paper discusses the design and development of an ontology for Modeling and Simulation called the Discrete-event Modeling Ontology (DeMO), and it presents prototype applications that demonstrate various uses and benefits that such an ontology may provide to the Modeling and Simulation community. PMID:22919114

  11. Prioritising lexical patterns to increase axiomatisation in biomedical ontologies. The role of localisation and modularity.

    Science.gov (United States)

    Quesada-Martínez, M; Fernández-Breis, J T; Stevens, R; Mikroyannidi, E

    2015-01-01

    This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". In previous work, we have defined methods for the extraction of lexical patterns from labels as an initial step towards semi-automatic ontology enrichment methods. Our previous findings revealed that many biomedical ontologies could benefit from enrichment methods using lexical patterns as a starting point.Here, we aim to identify which lexical patterns are appropriate for ontology enrichment, driving its analysis by metrics to prioritised the patterns. We propose metrics for suggesting which lexical regularities should be the starting point to enrich complex ontologies. Our method determines the relevance of a lexical pattern by measuring its locality in the ontology, that is, the distance between the classes associated with the pattern, and the distribution of the pattern in a certain module of the ontology. The methods have been applied to four significant biomedical ontologies including the Gene Ontology and SNOMED CT. The metrics provide information about the engineering of the ontologies and the relevance of the patterns. Our method enables the suggestion of links between classes that are not made explicit in the ontology. We propose a prioritisation of the lexical patterns found in the analysed ontologies. The locality and distribution of lexical patterns offer insights into the further engineering of the ontology. Developers can use this information to improve the axiomatisation of their ontologies.

  12. Annotating the human genome with Disease Ontology

    Science.gov (United States)

    Osborne, John D; Flatow, Jared; Holko, Michelle; Lin, Simon M; Kibbe, Warren A; Zhu, Lihua (Julie); Danila, Maria I; Feng, Gang; Chisholm, Rex L

    2009-01-01

    Background The human genome has been extensively annotated with Gene Ontology for biological functions, but minimally computationally annotated for diseases. Results We used the Unified Medical Language System (UMLS) MetaMap Transfer tool (MMTx) to discover gene-disease relationships from the GeneRIF database. We utilized a comprehensive subset of UMLS, which is disease-focused and structured as a directed acyclic graph (the Disease Ontology), to filter and interpret results from MMTx. The results were validated against the Homayouni gene collection using recall and precision measurements. We compared our results with the widely used Online Mendelian Inheritance in Man (OMIM) annotations. Conclusion The validation data set suggests a 91% recall rate and 97% precision rate of disease annotation using GeneRIF, in contrast with a 22% recall and 98% precision using OMIM. Our thesaurus-based approach allows for comparisons to be made between disease containing databases and allows for increased accuracy in disease identification through synonym matching. The much higher recall rate of our approach demonstrates that annotating human genome with Disease Ontology and GeneRIF for diseases dramatically increases the coverage of the disease annotation of human genome. PMID:19594883

  13. OpenDMAP: An open source, ontology-driven concept analysis engine, with applications to capturing knowledge regarding protein transport, protein interactions and cell-type-specific gene expression

    Directory of Open Access Journals (Sweden)

    Johnson Helen L

    2008-01-01

    Full Text Available Abstract Background Information extraction (IE efforts are widely acknowledged to be important in harnessing the rapid advance of biomedical knowledge, particularly in areas where important factual information is published in a diverse literature. Here we report on the design, implementation and several evaluations of OpenDMAP, an ontology-driven, integrated concept analysis system. It significantly advances the state of the art in information extraction by leveraging knowledge in ontological resources, integrating diverse text processing applications, and using an expanded pattern language that allows the mixing of syntactic and semantic elements and variable ordering. Results OpenDMAP information extraction systems were produced for extracting protein transport assertions (transport, protein-protein interaction assertions (interaction and assertions that a gene is expressed in a cell type (expression. Evaluations were performed on each system, resulting in F-scores ranging from .26 – .72 (precision .39 – .85, recall .16 – .85. Additionally, each of these systems was run over all abstracts in MEDLINE, producing a total of 72,460 transport instances, 265,795 interaction instances and 176,153 expression instances. Conclusion OpenDMAP advances the performance standards for extracting protein-protein interaction predications from the full texts of biomedical research articles. Furthermore, this level of performance appears to generalize to other information extraction tasks, including extracting information about predicates of more than two arguments. The output of the information extraction system is always constructed from elements of an ontology, ensuring that the knowledge representation is grounded with respect to a carefully constructed model of reality. The results of these efforts can be used to increase the efficiency of manual curation efforts and to provide additional features in systems that integrate multiple sources for

  14. Ontology: ambiguity and accuracy

    Directory of Open Access Journals (Sweden)

    Marcelo Schiessl

    2012-08-01

    Full Text Available Ambiguity is a major obstacle to information retrieval. It is source of several researches in Information Science. Ontologies have been studied in order to solve problems related to ambiguities. Paradoxically, “ontology” term is also ambiguous and it is understood according to the use by the community. Philosophy and Computer Science seems to have the most accentuated difference related to the term sense. The former holds undisputed tradition and authority. The latter, in despite of being quite recent, holds an informal sense, but pragmatic. Information Science acts ranging from philosophical to computational approaches so as to get organized collections based on balance between users’ necessities and available information. The semantic web requires informational cycle automation and demands studies related to ontologies. Consequently, revisiting relevant approaches for the study of ontologies plays a relevant role as a way to provide useful ideas to researchers maintaining philosophical rigor, and convenience provided by computers.

  15. Ontological engineering versus metaphysics

    Science.gov (United States)

    Tataj, Emanuel; Tomanek, Roman; Mulawka, Jan

    2011-10-01

    It has been recognized that ontologies are a semantic version of world wide web and can be found in knowledge-based systems. A recent time survey of this field also suggest that practical artificial intelligence systems may be motivated by this research. Especially strong artificial intelligence as well as concept of homo computer can also benefit from their use. The main objective of this contribution is to present and review already created ontologies and identify the main advantages which derive such approach for knowledge management systems. We would like to present what ontological engineering borrows from metaphysics and what a feedback it can provide to natural language processing, simulations and modelling. The potential topics of further development from philosophical point of view is also underlined.

  16. A Method for Building Personalized Ontology Summaries

    OpenAIRE

    Queiroz-Sousa, Paulo Orlando; Salgado, Ana Carolina; Pires, Carlos Eduardo

    2013-01-01

    In the context of ontology engineering, the ontology understanding is the basis for its further developmentand reuse. One intuitive eective approach to support ontology understanding is the process of ontology summarizationwhich highlights the most important concepts of an ontology. Ontology summarization identies an excerpt from anontology that contains the most relevant concepts and produces an abridged ontology. In this article, we present amethod for summarizing ontologies that represent ...

  17. Ontology and medical diagnosis.

    Science.gov (United States)

    Bertaud-Gounot, Valérie; Duvauferrier, Régis; Burgun, Anita

    2012-03-01

    Ontology and associated generic tools are appropriate for knowledge modeling and reasoning, but most of the time, disease definitions in existing description logic (DL) ontology are not sufficient to classify patient's characteristics under a particular disease because they do not formalize operational definitions of diseases (association of signs and symptoms=diagnostic criteria). The main objective of this study is to propose an ontological representation which takes into account the diagnostic criteria on which specific patient conditions may be classified under a specific disease. This method needs as a prerequisite a clear list of necessary and sufficient diagnostic criteria as defined for lots of diseases by learned societies. It does not include probability/uncertainty which Web Ontology Language (OWL 2.0) cannot handle. We illustrate it with spondyloarthritis (SpA). Ontology has been designed in Protégé 4.1 OWL-DL2.0. Several kinds of criteria were formalized: (1) mandatory criteria, (2) picking two criteria among several diagnostic criteria, (3) numeric criteria. Thirty real patient cases were successfully classified with the reasoner. This study shows that it is possible to represent operational definitions of diseases with OWL and successfully classify real patient cases. Representing diagnostic criteria as descriptive knowledge (instead of rules in Semantic Web Rule Language or Prolog) allows us to take advantage of tools already available for OWL. While we focused on Assessment of SpondyloArthritis international Society SpA criteria, we believe that many of the representation issues addressed here are relevant to using OWL-DL for operational definition of other diseases in ontology.

  18. Core Semantics for Public Ontologies

    National Research Council Canada - National Science Library

    Suni, Niranjan

    2005-01-01

    ... (schemas or ontologies) with respect to objects. The DARPA Agent Markup Language (DAML) through the use of ontologies provides a very powerful way to describe objects and their relationships to other objects...

  19. Learning expressive ontologies

    CERN Document Server

    Völker, J

    2009-01-01

    This publication advances the state-of-the-art in ontology learning by presenting a set of novel approaches to the semi-automatic acquisition, refinement and evaluation of logically complex axiomatizations. It has been motivated by the fact that the realization of the semantic web envisioned by Tim Berners-Lee is still hampered by the lack of ontological resources, while at the same time more and more applications of semantic technologies emerge from fast-growing areas such as e-business or life sciences. Such knowledge-intensive applications, requiring large scale reasoning over complex domai

  20. ONTOLOGY IN PHARMACY

    Directory of Open Access Journals (Sweden)

    L. Yu. Babintseva

    2015-05-01

    Full Text Available It’s considered ontological models for formalization of knowledge in pharmacy. There is emphasized the view that the possibility of rapid exchange of information in the pharmaceutical industry, it is necessary to create a single information space. This means not only the establishment of uniform standards for the presentation of information on pharmaceutical groups pharmacotherapeutic classifications, but also the creation of a unified and standardized system for the transfer and renewal of knowledge. It is the organization of information in the ontology helps quickly in the future to build expert systems and applications to work with data.

  1. Summarization by domain ontology navigation

    DEFF Research Database (Denmark)

    Andreasen, Troels; Bulskov, Henrik

    2013-01-01

    of the subject. In between these two extremes, conceptual summaries encompass selected concepts derived using background knowledge. We address in this paper an approach where conceptual summaries are provided through a conceptualization as given by an ontology. The ontology guiding the summarization can...... be a simple taxonomy or a generative domain ontology. A domain ontology can be provided by a preanalysis of a domain corpus and can be used to condense improved summaries that better reflects the conceptualization of a given domain....

  2. The National Center for Biomedical Ontology: Advancing Biomedicinethrough Structured Organization of Scientific Knowledge

    Energy Technology Data Exchange (ETDEWEB)

    Rubin, Daniel L.; Lewis, Suzanna E.; Mungall, Chris J.; Misra,Sima; Westerfield, Monte; Ashburner, Michael; Sim, Ida; Chute,Christopher G.; Solbrig, Harold; Storey, Margaret-Anne; Smith, Barry; Day-Richter, John; Noy, Natalya F.; Musen, Mark A.

    2006-01-23

    The National Center for Biomedical Ontology (http://bioontology.org) is a consortium that comprises leading informaticians, biologists, clinicians, and ontologists funded by the NIH Roadmap to develop innovative technology and methods that allow scientists to record, manage, and disseminate biomedical information and knowledge in machine-processable form. The goals of the Center are: (1) to help unify the divergent and isolated efforts in ontology development by promoting high quality open-source, standards-based tools to create, manage, and use ontologies, (2) to create new software tools so that scientists can use ontologies to annotate and analyze biomedical data, (3) to provide a national resource for the ongoing evaluation, integration, and evolution of biomedical ontologies and associated tools and theories in the context of driving biomedical projects (DBPs), and (4) to disseminate the tools and resources of the Center and to identify, evaluate, and communicate best practices of ontology development to the biomedical community. The Center is working toward these objectives by providing tools to develop ontologies and to annotate experimental data, and by developing resources to integrate and relate existing ontologies as well as by creating repositories of biomedical data that are annotated using those ontologies. The Center is providing training workshops in ontology design, development, and usage, and is also pursuing research in ontology evaluation, quality, and use of ontologies to promote scientific discovery. Through the research activities within the Center, collaborations with the DBPs, and interactions with the biomedical community, our goal is to help scientists to work more effectively in the e-science paradigm, enhancing experiment design, experiment execution, data analysis, information synthesis, hypothesis generation and testing, and understand human disease.

  3. InfAcrOnt: calculating cross-ontology term similarities using information flow by a random walk.

    Science.gov (United States)

    Cheng, Liang; Jiang, Yue; Ju, Hong; Sun, Jie; Peng, Jiajie; Zhou, Meng; Hu, Yang

    2018-01-19

    Since the establishment of the first biomedical ontology Gene Ontology (GO), the number of biomedical ontology has increased dramatically. Nowadays over 300 ontologies have been built including extensively used Disease Ontology (DO) and Human Phenotype Ontology (HPO). Because of the advantage of identifying novel relationships between terms, calculating similarity between ontology terms is one of the major tasks in this research area. Though similarities between terms within each ontology have been studied with in silico methods, term similarities across different ontologies were not investigated as deeply. The latest method took advantage of gene functional interaction network (GFIN) to explore such inter-ontology similarities of terms. However, it only used gene interactions and failed to make full use of the connectivity among gene nodes of the network. In addition, all existent methods are particularly designed for GO and their performances on the extended ontology community remain unknown. We proposed a method InfAcrOnt to infer similarities between terms across ontologies utilizing the entire GFIN. InfAcrOnt builds a term-gene-gene network which comprised ontology annotations and GFIN, and acquires similarities between terms across ontologies through modeling the information flow within the network by random walk. In our benchmark experiments on sub-ontologies of GO, InfAcrOnt achieves a high average area under the receiver operating characteristic curve (AUC) (0.9322 and 0.9309) and low standard deviations (1.8746e-6 and 3.0977e-6) in both human and yeast benchmark datasets exhibiting superior performance. Meanwhile, comparisons of InfAcrOnt results and prior knowledge on pair-wise DO-HPO terms and pair-wise DO-GO terms show high correlations. The experiment results show that InfAcrOnt significantly improves the performance of inferring similarities between terms across ontologies in benchmark set.

  4. Biomedical ontologies: toward scientific debate.

    Science.gov (United States)

    Maojo, V; Crespo, J; García-Remesal, M; de la Iglesia, D; Perez-Rey, D; Kulikowski, C

    2011-01-01

    Biomedical ontologies have been very successful in structuring knowledge for many different applications, receiving widespread praise for their utility and potential. Yet, the role of computational ontologies in scientific research, as opposed to knowledge management applications, has not been extensively discussed. We aim to stimulate further discussion on the advantages and challenges presented by biomedical ontologies from a scientific perspective. We review various aspects of biomedical ontologies going beyond their practical successes, and focus on some key scientific questions in two ways. First, we analyze and discuss current approaches to improve biomedical ontologies that are based largely on classical, Aristotelian ontological models of reality. Second, we raise various open questions about biomedical ontologies that require further research, analyzing in more detail those related to visual reasoning and spatial ontologies. We outline significant scientific issues that biomedical ontologies should consider, beyond current efforts of building practical consensus between them. For spatial ontologies, we suggest an approach for building "morphospatial" taxonomies, as an example that could stimulate research on fundamental open issues for biomedical ontologies. Analysis of a large number of problems with biomedical ontologies suggests that the field is very much open to alternative interpretations of current work, and in need of scientific debate and discussion that can lead to new ideas and research directions.

  5. Using a Foundational Ontology for Reengineering a Software Enterprise Ontology

    Science.gov (United States)

    Perini Barcellos, Monalessa; de Almeida Falbo, Ricardo

    The knowledge about software organizations is considerably relevant to software engineers. The use of a common vocabulary for representing the useful knowledge about software organizations involved in software projects is important for several reasons, such as to support knowledge reuse and to allow communication and interoperability between tools. Domain ontologies can be used to define a common vocabulary for sharing and reuse of knowledge about some domain. Foundational ontologies can be used for evaluating and re-designing domain ontologies, giving to these real-world semantics. This paper presents an evaluating of a Software Enterprise Ontology that was reengineered using the Unified Foundation Ontology (UFO) as basis.

  6. The design ontology

    DEFF Research Database (Denmark)

    Storga, Mario; Andreasen, Mogens Myrup; Marjanovic, Dorian

    2010-01-01

    The article presents the research of the nature, building and practical role of a Design Ontology as a potential framework for the more efficient product development (PD) data-, information- and knowledge- description, -explanation, -understanding and -reusing. In the methodology for development ...

  7. Dahlbeck and Pure Ontology

    Science.gov (United States)

    Mackenzie, Jim

    2016-01-01

    This article responds to Johan Dahlbeck's "Towards a pure ontology: Children's bodies and morality" ["Educational Philosophy and Theory," vol. 46 (1), 2014, pp. 8-23 (EJ1026561)]. His arguments from Nietzsche and Spinoza do not carry the weight he supposes, and the conclusions he draws from them about pedagogy would be…

  8. Audit Validation Using Ontologies

    Directory of Open Access Journals (Sweden)

    Ion IVAN

    2015-01-01

    Full Text Available Requirements to increase quality audit processes in enterprises are defined. It substantiates the need for assessment and management audit processes using ontologies. Sets of rules, ways to assess the consistency of rules and behavior within the organization are defined. Using ontologies are obtained qualifications that assess the organization's audit. Elaboration of the audit reports is a perfect algorithm-based activity characterized by generality, determinism, reproducibility, accuracy and a well-established. The auditors obtain effective levels. Through ontologies obtain the audit calculated level. Because the audit report is qualitative structure of information and knowledge it is very hard to analyze and interpret by different groups of users (shareholders, managers or stakeholders. Developing ontology for audit reports validation will be a useful instrument for both auditors and report users. In this paper we propose an instrument for validation of audit reports contain a lot of keywords that calculates indicators, a lot of indicators for each key word there is an indicator, qualitative levels; interpreter who builds a table of indicators, levels of actual and calculated levels.

  9. Biomedicine: an ontological dissection.

    Science.gov (United States)

    Baronov, David

    2008-01-01

    Though ubiquitous across the medical social sciences literature, the term "biomedicine" as an analytical concept remains remarkably slippery. It is argued here that this imprecision is due in part to the fact that biomedicine is comprised of three interrelated ontological spheres, each of which frames biomedicine as a distinct subject of investigation. This suggests that, depending upon one's ontological commitment, the meaning of biomedicine will shift. From an empirical perspective, biomedicine takes on the appearance of a scientific enterprise and is defined as a derivative category of Western science more generally. From an interpretive perspective, biomedicine represents a symbolic-cultural expression whose adherence to the principles of scientific objectivity conceals an ideological agenda. From a conceptual perspective, biomedicine represents an expression of social power that reflects structures of power and privilege within capitalist society. No one perspective exists in isolation and so the image of biomedicine from any one presents an incomplete understanding. It is the mutually-conditioning interrelations between these ontological spheres that account for biomedicine's ongoing development. Thus, the ontological dissection of biomedicine that follows, with particular emphasis on the period of its formal crystallization in the latter nineteenth and early twentieth century, is intended to deepen our understanding of biomedicine as an analytical concept across the medical social sciences literature.

  10. Epistemology and ontology in core ontologies: FOLaw and LRI-Core, two core ontologies for law

    NARCIS (Netherlands)

    Breukers, J.A.P.J.; Hoekstra, R.J.

    2004-01-01

    For more than a decade constructing ontologies for legal domains, we, at the Leibniz Center for Law, felt really the need to develop a core ontology for law that would enable us to re-use the common denominator of the various legal domains. In this paper we present two core ontologies for law. The

  11. The Genomic Standards Consortium

    DEFF Research Database (Denmark)

    Field, Dawn; Amaral-Zettler, Linda; Cochrane, Guy

    2011-01-01

    Standards Consortium (GSC), an open-membership organization that drives community-based standardization activities, Here we provide a short history of the GSC, provide an overview of its range of current activities, and make a call for the scientific community to join forces to improve the quality...

  12. Development of an Ontology for Periodontitis.

    Science.gov (United States)

    Suzuki, Asami; Takai-Igarashi, Takako; Nakaya, Jun; Tanaka, Hiroshi

    2015-01-01

    In the clinical dentists and periodontal researchers' community, there is an obvious demand for a systems model capable of linking the clinical presentation of periodontitis to underlying molecular knowledge. A computer-readable representation of processes on disease development will give periodontal researchers opportunities to elucidate pathways and mechanisms of periodontitis. An ontology for periodontitis can be a model for integration of large variety of factors relating to a complex disease such as chronic inflammation in different organs accompanied by bone remodeling and immune system disorders, which has recently been referred to as osteoimmunology. Terms characteristic of descriptions related to the onset and progression of periodontitis were manually extracted from 194 review articles and PubMed abstracts by experts in periodontology. We specified all the relations between the extracted terms and constructed them into an ontology for periodontitis. We also investigated matching between classes of our ontology and that of Gene Ontology Biological Process. We developed an ontology for periodontitis called Periodontitis-Ontology (PeriO). The pathological progression of periodontitis is caused by complex, multi-factor interrelationships. PeriO consists of all the required concepts to represent the pathological progression and clinical treatment of periodontitis. The pathological processes were formalized with reference to Basic Formal Ontology and Relation Ontology, which accounts for participants in the processes realized by biological objects such as molecules and cells. We investigated the peculiarity of biological processes observed in pathological progression and medical treatments for the disease in comparison with Gene Ontology Biological Process (GO-BP) annotations. The results indicated that peculiarities of Perio existed in 1) granularity and context dependency of both the conceptualizations, and 2) causality intrinsic to the pathological processes

  13. Benchmarking ontologies: bigger or better?

    Directory of Open Access Journals (Sweden)

    Lixia Yao

    2011-01-01

    Full Text Available A scientific ontology is a formal representation of knowledge within a domain, typically including central concepts, their properties, and relations. With the rise of computers and high-throughput data collection, ontologies have become essential to data mining and sharing across communities in the biomedical sciences. Powerful approaches exist for testing the internal consistency of an ontology, but not for assessing the fidelity of its domain representation. We introduce a family of metrics that describe the breadth and depth with which an ontology represents its knowledge domain. We then test these metrics using (1 four of the most common medical ontologies with respect to a corpus of medical documents and (2 seven of the most popular English thesauri with respect to three corpora that sample language from medicine, news, and novels. Here we show that our approach captures the quality of ontological representation and guides efforts to narrow the breach between ontology and collective discourse within a domain. Our results also demonstrate key features of medical ontologies, English thesauri, and discourse from different domains. Medical ontologies have a small intersection, as do English thesauri. Moreover, dialects characteristic of distinct domains vary strikingly as many of the same words are used quite differently in medicine, news, and novels. As ontologies are intended to mirror the state of knowledge, our methods to tighten the fit between ontology and domain will increase their relevance for new areas of biomedical science and improve the accuracy and power of inferences computed across them.

  14. Ontology-based Information Retrieval

    DEFF Research Database (Denmark)

    Styltsvig, Henrik Bulskov

    In this thesis, we will present methods for introducing ontologies in information retrieval. The main hypothesis is that the inclusion of conceptual knowledge such as ontologies in the information retrieval process can contribute to the solution of major problems currently found in information...... retrieval. This utilization of ontologies has a number of challenges. Our focus is on the use of similarity measures derived from the knowledge about relations between concepts in ontologies, the recognition of semantic information in texts and the mapping of this knowledge into the ontologies in use......, as well as how to fuse together the ideas of ontological similarity and ontological indexing into a realistic information retrieval scenario. To achieve the recognition of semantic knowledge in a text, shallow natural language processing is used during indexing that reveals knowledge to the level of noun...

  15. Ontology Design Patterns for Combining Pathology and Anatomy: Application to Study Aging and Longevity in Inbred Mouse Strains

    KAUST Repository

    Alghamdi, Sarah M.

    2018-05-13

    In biomedical research, ontologies are widely used to represent knowledge as well as to annotate datasets. Many of the existing ontologies cover a single type of phenomena, such as a process, cell type, gene, pathological entity or anatomical structure. Consequently, there is a requirement to use multiple ontologies to fully characterize the observations in the datasets. Although this allows precise annotation of different aspects of a given dataset, it limits our ability to use the ontologies in data analysis, as the ontologies are usually disconnected and their combinations cannot be exploited. Motivated by this, here we present novel ontology design methods for combining pathology and anatomy concepts. To this end, we use a dataset of mouse models which has been characterized through two ontologies: one of them is the mouse pathology ontology (MPATH) covering pathological lesions while the other is the mouse anatomy ontology (MA) covering the anatomical site of the lesions. We propose four novel ontology design patterns for combining these ontologies, and use these patterns to generate four ontologies in a data-driven way. To evaluate the generated ontologies, we utilize these in ontology-based data analysis, including ontology enrichment analysis and computation of semantic similarity. We demonstrate that there are significant differences between the four ontologies in different analysis approaches. In addition, when using semantic similarity to confirm the hypothesis that genetically identical mice should develop more similar diseases, the generated combined ontologies lead to significantly better analysis results compared to using each ontology individually. Our results reveal that using ontology design patterns to combine different facets characterizing a dataset can improve established analysis methods.

  16. Semantics in support of biodiversity knowledge discovery: an introduction to the biological collections ontology and related ontologies.

    Science.gov (United States)

    Walls, Ramona L; Deck, John; Guralnick, Robert; Baskauf, Steve; Beaman, Reed; Blum, Stanley; Bowers, Shawn; Buttigieg, Pier Luigi; Davies, Neil; Endresen, Dag; Gandolfo, Maria Alejandra; Hanner, Robert; Janning, Alyssa; Krishtalka, Leonard; Matsunaga, Andréa; Midford, Peter; Morrison, Norman; Ó Tuama, Éamonn; Schildhauer, Mark; Smith, Barry; Stucky, Brian J; Thomer, Andrea; Wieczorek, John; Whitacre, Jamie; Wooley, John

    2014-01-01

    The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers.

  17. Semantics in Support of Biodiversity Knowledge Discovery: An Introduction to the Biological Collections Ontology and Related Ontologies

    Science.gov (United States)

    Baskauf, Steve; Blum, Stanley; Bowers, Shawn; Davies, Neil; Endresen, Dag; Gandolfo, Maria Alejandra; Hanner, Robert; Janning, Alyssa; Krishtalka, Leonard; Matsunaga, Andréa; Midford, Peter; Tuama, Éamonn Ó.; Schildhauer, Mark; Smith, Barry; Stucky, Brian J.; Thomer, Andrea; Wieczorek, John; Whitacre, Jamie; Wooley, John

    2014-01-01

    The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers

  18. Owlready: Ontology-oriented programming in Python with automatic classification and high level constructs for biomedical ontologies.

    Science.gov (United States)

    Lamy, Jean-Baptiste

    2017-07-01

    Ontologies are widely used in the biomedical domain. While many tools exist for the edition, alignment or evaluation of ontologies, few solutions have been proposed for ontology programming interface, i.e. for accessing and modifying an ontology within a programming language. Existing query languages (such as SPARQL) and APIs (such as OWLAPI) are not as easy-to-use as object programming languages are. Moreover, they provide few solutions to difficulties encountered with biomedical ontologies. Our objective was to design a tool for accessing easily the entities of an OWL ontology, with high-level constructs helping with biomedical ontologies. From our experience on medical ontologies, we identified two difficulties: (1) many entities are represented by classes (rather than individuals), but the existing tools do not permit manipulating classes as easily as individuals, (2) ontologies rely on the open-world assumption, whereas the medical reasoning must consider only evidence-based medical knowledge as true. We designed a Python module for ontology-oriented programming. It allows access to the entities of an OWL ontology as if they were objects in the programming language. We propose a simple high-level syntax for managing classes and the associated "role-filler" constraints. We also propose an algorithm for performing local closed world reasoning in simple situations. We developed Owlready, a Python module for a high-level access to OWL ontologies. The paper describes the architecture and the syntax of the module version 2. It details how we integrated the OWL ontology model with the Python object model. The paper provides examples based on Gene Ontology (GO). We also demonstrate the interest of Owlready in a use case focused on the automatic comparison of the contraindications of several drugs. This use case illustrates the use of the specific syntax proposed for manipulating classes and for performing local closed world reasoning. Owlready has been successfully

  19. Completeness, supervenience and ontology

    International Nuclear Information System (INIS)

    Maudlin, Tim W E

    2007-01-01

    In 1935, Einstein, Podolsky and Rosen raised the issue of the completeness of the quantum description of a physical system. What they had in mind is whether or not the quantum description is informationally complete, in that all physical features of a system can be recovered from it. In a collapse theory such as the theory of Ghirardi, Rimini and Weber, the quantum wavefunction is informationally complete, and this has often been taken to suggest that according to that theory the wavefunction is all there is. If we distinguish the ontological completeness of a description from its informational completeness, we can see that the best interpretations of the GRW theory must postulate more physical ontology than just the wavefunction

  20. Completeness, supervenience and ontology

    Energy Technology Data Exchange (ETDEWEB)

    Maudlin, Tim W E [Department of Philosophy, Rutgers University, 26 Nichol Avenue, New Brunswick, NJ 08901-1411 (United States)

    2007-03-23

    In 1935, Einstein, Podolsky and Rosen raised the issue of the completeness of the quantum description of a physical system. What they had in mind is whether or not the quantum description is informationally complete, in that all physical features of a system can be recovered from it. In a collapse theory such as the theory of Ghirardi, Rimini and Weber, the quantum wavefunction is informationally complete, and this has often been taken to suggest that according to that theory the wavefunction is all there is. If we distinguish the ontological completeness of a description from its informational completeness, we can see that the best interpretations of the GRW theory must postulate more physical ontology than just the wavefunction.

  1. LOGISTICS OPTIMIZATION USING ONTOLOGIES

    OpenAIRE

    Hendi , Hayder; Ahmad , Adeel; Bouneffa , Mourad; Fonlupt , Cyril

    2014-01-01

    International audience; Logistics processes involve complex physical flows and integration of different elements. It is widely observed that the uncontrolled processes can decline the state of logistics. The optimization of logistic processes can support the desired growth and consistent continuity of logistics. In this paper, we present a software framework for logistic processes optimization. It primarily defines logistic ontologies and then optimize them. It intends to assist the design of...

  2. A unified anatomy ontology of the vertebrate skeletal system.

    Directory of Open Access Journals (Sweden)

    Wasila M Dahdul

    Full Text Available The skeleton is of fundamental importance in research in comparative vertebrate morphology, paleontology, biomechanics, developmental biology, and systematics. Motivated by research questions that require computational access to and comparative reasoning across the diverse skeletal phenotypes of vertebrates, we developed a module of anatomical concepts for the skeletal system, the Vertebrate Skeletal Anatomy Ontology (VSAO, to accommodate and unify the existing skeletal terminologies for the species-specific (mouse, the frog Xenopus, zebrafish and multispecies (teleost, amphibian vertebrate anatomy ontologies. Previous differences between these terminologies prevented even simple queries across databases pertaining to vertebrate morphology. This module of upper-level and specific skeletal terms currently includes 223 defined terms and 179 synonyms that integrate skeletal cells, tissues, biological processes, organs (skeletal elements such as bones and cartilages, and subdivisions of the skeletal system. The VSAO is designed to integrate with other ontologies, including the Common Anatomy Reference Ontology (CARO, Gene Ontology (GO, Uberon, and Cell Ontology (CL, and it is freely available to the community to be updated with additional terms required for research. Its structure accommodates anatomical variation among vertebrate species in development, structure, and composition. Annotation of diverse vertebrate phenotypes with this ontology will enable novel inquiries across the full spectrum of phenotypic diversity.

  3. A unified anatomy ontology of the vertebrate skeletal system.

    Science.gov (United States)

    Dahdul, Wasila M; Balhoff, James P; Blackburn, David C; Diehl, Alexander D; Haendel, Melissa A; Hall, Brian K; Lapp, Hilmar; Lundberg, John G; Mungall, Christopher J; Ringwald, Martin; Segerdell, Erik; Van Slyke, Ceri E; Vickaryous, Matthew K; Westerfield, Monte; Mabee, Paula M

    2012-01-01

    The skeleton is of fundamental importance in research in comparative vertebrate morphology, paleontology, biomechanics, developmental biology, and systematics. Motivated by research questions that require computational access to and comparative reasoning across the diverse skeletal phenotypes of vertebrates, we developed a module of anatomical concepts for the skeletal system, the Vertebrate Skeletal Anatomy Ontology (VSAO), to accommodate and unify the existing skeletal terminologies for the species-specific (mouse, the frog Xenopus, zebrafish) and multispecies (teleost, amphibian) vertebrate anatomy ontologies. Previous differences between these terminologies prevented even simple queries across databases pertaining to vertebrate morphology. This module of upper-level and specific skeletal terms currently includes 223 defined terms and 179 synonyms that integrate skeletal cells, tissues, biological processes, organs (skeletal elements such as bones and cartilages), and subdivisions of the skeletal system. The VSAO is designed to integrate with other ontologies, including the Common Anatomy Reference Ontology (CARO), Gene Ontology (GO), Uberon, and Cell Ontology (CL), and it is freely available to the community to be updated with additional terms required for research. Its structure accommodates anatomical variation among vertebrate species in development, structure, and composition. Annotation of diverse vertebrate phenotypes with this ontology will enable novel inquiries across the full spectrum of phenotypic diversity.

  4. A Unified Anatomy Ontology of the Vertebrate Skeletal System

    Science.gov (United States)

    Dahdul, Wasila M.; Balhoff, James P.; Blackburn, David C.; Diehl, Alexander D.; Haendel, Melissa A.; Hall, Brian K.; Lapp, Hilmar; Lundberg, John G.; Mungall, Christopher J.; Ringwald, Martin; Segerdell, Erik; Van Slyke, Ceri E.; Vickaryous, Matthew K.; Westerfield, Monte; Mabee, Paula M.

    2012-01-01

    The skeleton is of fundamental importance in research in comparative vertebrate morphology, paleontology, biomechanics, developmental biology, and systematics. Motivated by research questions that require computational access to and comparative reasoning across the diverse skeletal phenotypes of vertebrates, we developed a module of anatomical concepts for the skeletal system, the Vertebrate Skeletal Anatomy Ontology (VSAO), to accommodate and unify the existing skeletal terminologies for the species-specific (mouse, the frog Xenopus, zebrafish) and multispecies (teleost, amphibian) vertebrate anatomy ontologies. Previous differences between these terminologies prevented even simple queries across databases pertaining to vertebrate morphology. This module of upper-level and specific skeletal terms currently includes 223 defined terms and 179 synonyms that integrate skeletal cells, tissues, biological processes, organs (skeletal elements such as bones and cartilages), and subdivisions of the skeletal system. The VSAO is designed to integrate with other ontologies, including the Common Anatomy Reference Ontology (CARO), Gene Ontology (GO), Uberon, and Cell Ontology (CL), and it is freely available to the community to be updated with additional terms required for research. Its structure accommodates anatomical variation among vertebrate species in development, structure, and composition. Annotation of diverse vertebrate phenotypes with this ontology will enable novel inquiries across the full spectrum of phenotypic diversity. PMID:23251424

  5. IPD-Work consortium

    DEFF Research Database (Denmark)

    Kivimäki, Mika; Singh-Manoux, Archana; Virtanen, Marianna

    2015-01-01

    of countries. The aim of the consortium is to estimate reliably the associations of work-related psychosocial factors with chronic diseases, disability, and mortality. Our findings are highly cited by the occupational health, epidemiology, and clinical medicine research community. However, some of the IPD-Work......'s findings have also generated disagreement as they challenge the importance of job strain as a major target for coronary heart disease (CHD) prevention, this is reflected in the critical discussion paper by Choi et al (1). In this invited reply to Choi et al, we aim to (i) describe how IPD-Work seeks......Established in 2008 and comprising over 60 researchers, the IPD-Work (individual-participant data meta-analysis in working populations) consortium is a collaborative research project that uses pre-defined meta-analyses of individual-participant data from multiple cohort studies representing a range...

  6. Kansas Wind Energy Consortium

    Energy Technology Data Exchange (ETDEWEB)

    Gruenbacher, Don [Kansas State Univ., Manhattan, KS (United States)

    2015-12-31

    This project addresses both fundamental and applied research problems that will help with problems defined by the DOE “20% Wind by 2030 Report”. In particular, this work focuses on increasing the capacity of small or community wind generation capabilities that would be operated in a distributed generation approach. A consortium (KWEC – Kansas Wind Energy Consortium) of researchers from Kansas State University and Wichita State University aims to dramatically increase the penetration of wind energy via distributed wind power generation. We believe distributed generation through wind power will play a critical role in the ability to reach and extend the renewable energy production targets set by the Department of Energy. KWEC aims to find technical and economic solutions to enable widespread implementation of distributed renewable energy resources that would apply to wind.

  7. Genetic variation in the immunosuppression pathway genes and breast cancer susceptibility: a pooled analysis of 42,510 cases and 40,577 controls from the Breast Cancer Association Consortium.

    Science.gov (United States)

    Lei, Jieping; Rudolph, Anja; Moysich, Kirsten B; Behrens, Sabine; Goode, Ellen L; Bolla, Manjeet K; Dennis, Joe; Dunning, Alison M; Easton, Douglas F; Wang, Qin; Benitez, Javier; Hopper, John L; Southey, Melissa C; Schmidt, Marjanka K; Broeks, Annegien; Fasching, Peter A; Haeberle, Lothar; Peto, Julian; Dos-Santos-Silva, Isabel; Sawyer, Elinor J; Tomlinson, Ian; Burwinkel, Barbara; Marmé, Frederik; Guénel, Pascal; Truong, Thérèse; Bojesen, Stig E; Flyger, Henrik; Nielsen, Sune F; Nordestgaard, Børge G; González-Neira, Anna; Menéndez, Primitiva; Anton-Culver, Hoda; Neuhausen, Susan L; Brenner, Hermann; Arndt, Volker; Meindl, Alfons; Schmutzler, Rita K; Brauch, Hiltrud; Hamann, Ute; Nevanlinna, Heli; Fagerholm, Rainer; Dörk, Thilo; Bogdanova, Natalia V; Mannermaa, Arto; Hartikainen, Jaana M; Van Dijck, Laurien; Smeets, Ann; Flesch-Janys, Dieter; Eilber, Ursula; Radice, Paolo; Peterlongo, Paolo; Couch, Fergus J; Hallberg, Emily; Giles, Graham G; Milne, Roger L; Haiman, Christopher A; Schumacher, Fredrick; Simard, Jacques; Goldberg, Mark S; Kristensen, Vessela; Borresen-Dale, Anne-Lise; Zheng, Wei; Beeghly-Fadiel, Alicia; Winqvist, Robert; Grip, Mervi; Andrulis, Irene L; Glendon, Gord; García-Closas, Montserrat; Figueroa, Jonine; Czene, Kamila; Brand, Judith S; Darabi, Hatef; Eriksson, Mikael; Hall, Per; Li, Jingmei; Cox, Angela; Cross, Simon S; Pharoah, Paul D P; Shah, Mitul; Kabisch, Maria; Torres, Diana; Jakubowska, Anna; Lubinski, Jan; Ademuyiwa, Foluso; Ambrosone, Christine B; Swerdlow, Anthony; Jones, Michael; Chang-Claude, Jenny

    2016-01-01

    Immunosuppression plays a pivotal role in assisting tumors to evade immune destruction and promoting tumor development. We hypothesized that genetic variation in the immunosuppression pathway genes may be implicated in breast cancer tumorigenesis. We included 42,510 female breast cancer cases and 40,577 controls of European ancestry from 37 studies in the Breast Cancer Association Consortium (2015) with available genotype data for 3595 single nucleotide polymorphisms (SNPs) in 133 candidate genes. Associations between genotyped SNPs and overall breast cancer risk, and secondarily according to estrogen receptor (ER) status, were assessed using multiple logistic regression models. Gene-level associations were assessed based on principal component analysis. Gene expression analyses were conducted using RNA sequencing level 3 data from The Cancer Genome Atlas for 989 breast tumor samples and 113 matched normal tissue samples. SNP rs1905339 (A>G) in the STAT3 region was associated with an increased breast cancer risk (per allele odds ratio 1.05, 95 % confidence interval 1.03-1.08; p value = 1.4 × 10(-6)). The association did not differ significantly by ER status. On the gene level, in addition to TGFBR2 and CCND1, IL5 and GM-CSF showed the strongest associations with overall breast cancer risk (p value = 1.0 × 10(-3) and 7.0 × 10(-3), respectively). Furthermore, STAT3 and IL5 but not GM-CSF were differentially expressed between breast tumor tissue and normal tissue (p value = 2.5 × 10(-3), 4.5 × 10(-4) and 0.63, respectively). Our data provide evidence that the immunosuppression pathway genes STAT3, IL5, and GM-CSF may be novel susceptibility loci for breast cancer in women of European ancestry.

  8. Feasibility of automated foundational ontology interchangeability

    CSIR Research Space (South Africa)

    Khan, ZC

    2014-11-01

    Full Text Available the Source Domain Ontology (sOd), with the domain knowledge com- ponent of the source ontology, the Source Foundational Ontology (sOf ) that is the foundational ontology component of the source ontology that is to be interchanged, and any equivalence... or subsumption mappings between enti- ties in sOd and sOf . – The Target Ontology (tO) which has been interchanged, which comprises the Target Domain Ontology (tOd), with the domain knowledge component of the target ontology, and the Target Foundational Ontology...

  9. An Ontology for Software Engineering Education

    Science.gov (United States)

    Ling, Thong Chee; Jusoh, Yusmadi Yah; Adbullah, Rusli; Alwi, Nor Hayati

    2013-01-01

    Software agents communicate using ontology. It is important to build an ontology for specific domain such as Software Engineering Education. Building an ontology from scratch is not only hard, but also incur much time and cost. This study aims to propose an ontology through adaptation of the existing ontology which is originally built based on a…

  10. Ontology of a scene based on Java 3D architecture.

    Directory of Open Access Journals (Sweden)

    Rubén González Crespo

    2009-12-01

    Full Text Available The present article seeks to make an approach to the class hierarchy of a scene built with the architecture Java 3D, to develop an ontology of a scene as from the semantic essential components for the semantic structuring of the Web3D. Java was selected because the language recommended by the W3C Consortium for the Development of the Web3D oriented applications as from X3D standard is Xj3D which compositionof their Schemas is based the architecture of Java3D In first instance identifies the domain and scope of the ontology, defining classes and subclasses that comprise from Java3D architecture and the essential elements of a scene, as its point of origin, the field of rotation, translation The limitation of the scene and the definition of shaders, then define the slots that are declared in RDF as a framework for describing the properties of the classes established from identifying thedomain and range of each class, then develops composition of the OWL ontology on SWOOP Finally, be perform instantiations of the ontology building for a Iconosphere object as from class expressions defined.

  11. Drug target ontology to classify and integrate drug discovery data

    DEFF Research Database (Denmark)

    Lin, Yu; Mehta, Saurabh; Küçük-McGinty, Hande

    2017-01-01

    using a new software tool to auto-generate most axioms from a database while supporting manual knowledge acquisition. A modular, hierarchical implementation facilitate ontology development and maintenance and makes use of various external ontologies, thus integrating the DTO into the ecosystem...... of biomedical ontologies. As a formal OWL-DL ontology, DTO contains asserted and inferred axioms. Modeling data from the Library of Integrated Network-based Cellular Signatures (LINCS) program illustrates the potential of DTO for contextual data integration and nuanced definition of important drug target...... characteristics. DTO has been implemented in the IDG user interface Portal, Pharos and the TIN-X explorer of protein target disease relationships. CONCLUSIONS: DTO was built based on the need for a formal semantic model for druggable targets including various related information such as protein, gene, protein...

  12. Interaction between leptin and leptin receptor in gastric carcinoma: Gene ontology analysis Interacción entre la leptina y su receptor en el carcinoma gástrico: análisis de ontología genética

    Directory of Open Access Journals (Sweden)

    V. Wiwanitkit

    2007-04-01

    Full Text Available Gastric carcinoma is a rare but important malignancy. The link between leptin, a cytokine that is elevated in obese individuals, and cancer development has been proposed. It is noted that leptin and its receptor may play a positive role in the progression in gastric cancer. However, the exact mechanism resulting form the interaction between leptin and leptin receptor has never been clarified. Here, the author used a new gene ontology technology to predict the molecular function and biological process due to the interaction between leptin and leptin receptor. Comparing to leptin and leptin receptor, the leptin-leptin receptor poses the same function and biological process as leptin receptor. This can confirm that leptin receptor has a significant suppressive effect on the expression of leptin. Loss of hormone activity and disturbance of normal cell signaling pathway of leptin can be seen. Blocking of receptor might be rational therapeutic strategy.El carcinoma gástrico es un cáncer muy poco frecuente pero importante. Se ha postulado que la leptina, una citocina que aparece elevada en las personas obesas, está relacionada con el cáncer. Se sabe que la leptina y su receptor pueden desempeñar un papel positivo en la progresión del cáncer gástrico. Sin embargo, nunca se ha dilucidado el mecanismo exacto al que daría lugar la interacción entre la leptina y el receptor de leptina. Aquí, el autor empleó una nueva tecnología de ontología genética para predecir la función molecular y el proceso biológico resultantes de la interacción entre la leptina y su receptor. Frente a la leptina y su receptor, el compuesto leptina-receptor realiza la misma función y el mismo proceso biológico que el receptor de leptina. Esto puede confirmar que el receptor de leptina ejerce un importante efecto supresor sobre la expresión de leptina. Pueden observarse una pérdida de actividad hormonal y la alteración de la vía normal de señalización celular

  13. ONSET: Automated foundational ontology selection and explanation

    CSIR Research Space (South Africa)

    Khan, Z

    2012-10-01

    Full Text Available It has been shown that using a foundational ontology for domain ontology development is beneficial in theory and practice. However, developers have difficulty with choosing the appropriate foundational ontology, and why. In order to solve...

  14. Ontology Based Model Transformation Infrastructure

    NARCIS (Netherlands)

    Göknil, Arda; Topaloglu, N.Y.

    2005-01-01

    Using MDA in ontology development has been investigated in several works recently. The mappings and transformations between the UML constructs and the OWL elements to develop ontologies are the main concern of these research projects. We propose another approach in order to achieve the collaboration

  15. Ontology through a Mindfulness Process

    Science.gov (United States)

    Bearance, Deborah; Holmes, Kimberley

    2015-01-01

    Traditionally, when ontology is taught in a graduate studies course on social research, there is a tendency for this concept to be examined through the process of lectures and readings. Such an approach often leaves graduate students to grapple with a personal embodiment of this concept and to comprehend how ontology can ground their research.…

  16. The foundational ontology library ROMULUS

    CSIR Research Space (South Africa)

    Khan, ZC

    2013-09-01

    Full Text Available . We present here a basic step in that direction with the Repository of Ontologies for MULtiple USes, ROMULUS, which is the first online library of machine-processable, modularised, aligned, and logic-based merged foundational ontologies. In addition...

  17. Tracking Changes during Ontology Evolution

    NARCIS (Netherlands)

    Noy, Natalya F.; Kunnatur, Sandhya; Klein, Michel; Musen, Mark A.

    2004-01-01

    As ontology development becomes a collaborative process, developers face the problem of maintaining versions of ontologies akin to maintaining versions of software code or versions of documents in large projects. Traditional versioning systems enable users to compare versions, examine changes, and

  18. PDON: Parkinson's disease ontology for representation and modeling of the Parkinson's disease knowledge domain.

    Science.gov (United States)

    Younesi, Erfan; Malhotra, Ashutosh; Gündel, Michaela; Scordis, Phil; Kodamullil, Alpha Tom; Page, Matt; Müller, Bernd; Springstubbe, Stephan; Wüllner, Ullrich; Scheller, Dieter; Hofmann-Apitius, Martin

    2015-09-22

    Despite the unprecedented and increasing amount of data, relatively little progress has been made in molecular characterization of mechanisms underlying Parkinson's disease. In the area of Parkinson's research, there is a pressing need to integrate various pieces of information into a meaningful context of presumed disease mechanism(s). Disease ontologies provide a novel means for organizing, integrating, and standardizing the knowledge domains specific to disease in a compact, formalized and computer-readable form and serve as a reference for knowledge exchange or systems modeling of disease mechanism. The Parkinson's disease ontology was built according to the life cycle of ontology building. Structural, functional, and expert evaluation of the ontology was performed to ensure the quality and usability of the ontology. A novelty metric has been introduced to measure the gain of new knowledge using the ontology. Finally, a cause-and-effect model was built around PINK1 and two gene expression studies from the Gene Expression Omnibus database were re-annotated to demonstrate the usability of the ontology. The Parkinson's disease ontology with a subclass-based taxonomic hierarchy covers the broad spectrum of major biomedical concepts from molecular to clinical features of the disease, and also reflects different views on disease features held by molecular biologists, clinicians and drug developers. The current version of the ontology contains 632 concepts, which are organized under nine views. The structural evaluation showed the balanced dispersion of concept classes throughout the ontology. The functional evaluation demonstrated that the ontology-driven literature search could gain novel knowledge not present in the reference Parkinson's knowledge map. The ontology was able to answer specific questions related to Parkinson's when evaluated by experts. Finally, the added value of the Parkinson's disease ontology is demonstrated by ontology-driven modeling of PINK1

  19. A combined blood based gene expression and plasma protein abundance signature for diagnosis of epithelial ovarian cancer - a study of the OVCAD consortium

    International Nuclear Information System (INIS)

    Pils, Dietmar; Sehouli, Jalid; Braicu, Ioana; Vergote, Ignace; Van Gorp, Toon; Mahner, Sven; Concin, Nicole; Speiser, Paul; Zeillinger, Robert; Tong, Dan; Hager, Gudrun; Obermayr, Eva; Aust, Stefanie; Heinze, Georg; Kohl, Maria; Schuster, Eva; Wolf, Andrea

    2013-01-01

    The immune system is a key player in fighting cancer. Thus, we sought to identify a molecular ‘immune response signature’ indicating the presence of epithelial ovarian cancer (EOC) and to combine this with a serum protein biomarker panel to increase the specificity and sensitivity for earlier detection of EOC. Comparing the expression of 32,000 genes in a leukocytes fraction from 44 EOC patients and 19 controls, three uncorrelated shrunken centroid models were selected, comprised of 7, 14, and 6 genes. A second selection step using RT-qPCR data and significance analysis of microarrays yielded 13 genes (AP2A1, B4GALT1, C1orf63, CCR2, CFP, DIS3, NEAT1, NOXA1, OSM, PAPOLG, PRIC285, ZNF419, and BC037918) which were finally used in 343 samples (90 healthy, six cystadenoma, eight low malignant potential tumor, 19 FIGO I/II, and 220 FIGO III/IV EOC patients). Using new 65 controls and 224 EOC patients (thereof 14 FIGO I/II) the abundances of six plasma proteins (MIF, prolactin, CA125, leptin, osteopondin, and IGF2) was determined and used in combination with the expression values from the 13 genes for diagnosis of EOC. Combined diagnostic models using either each five gene expression and plasma protein abundance values or 13 gene expression and six plasma protein abundance values can discriminate controls from patients with EOC with Receiver Operator Characteristics Area Under the Curve values of 0.998 and bootstrap .632+ validated classification errors of 3.1% and 2.8%, respectively. The sensitivities were 97.8% and 95.6%, respectively, at a set specificity of 99.6%. The combination of gene expression and plasma protein based blood derived biomarkers in one diagnostic model increases the sensitivity and the specificity significantly. Such a diagnostic test may allow earlier diagnosis of epithelial ovarian cancer

  20. Polymorphisms in Genes of Relevance for Oestrogen and Oxytocin Pathways and Risk of Barrett's Oesophagus and Oesophageal Adenocarcinoma: A Pooled Analysis from the BEACON Consortium.

    Directory of Open Access Journals (Sweden)

    Katarina Lagergren

    Full Text Available The strong male predominance in oesophageal adenocarcinoma (OAC and Barrett's oesophagus (BO continues to puzzle. Hormonal influence, e.g. oestrogen or oxytocin, might contribute.This genetic-epidemiological study pooled 14 studies from three continents, Australia, Europe, and North America. Polymorphisms in 3 key genes coding for the oestrogen pathway (receptor alpha (ESR1, receptor beta (ESR2, and aromatase (CYP19A1, and 3 key genes of the oxytocin pathway (the oxytocin receptor (OXTR, oxytocin protein (OXT, and cyclic ADP ribose hydrolase glycoprotein (CD38, were analysed using a gene-based approach, versatile gene-based test association study (VEGAS.Among 1508 OAC patients, 2383 BO patients, and 2170 controls, genetic variants within ESR1 were associated with BO in males (p = 0.0058 and an increased risk of OAC and BO combined in males (p = 0.0023. Genetic variants within OXTR were associated with an increased risk of BO in both sexes combined (p = 0.0035 and in males (p = 0.0012. We followed up these suggestive findings in a further smaller data set, but found no replication. There were no significant associations between the other 4 genes studied and risk of OAC, BO, separately on in combination, in males and females combined or in males only.Genetic variants in the oestrogen receptor alpha and the oxytocin receptor may be associated with an increased risk of BO or OAC, but replication in other large samples are needed.

  1. Polymorphisms in Genes of Relevance for Oestrogen and Oxytocin Pathways and Risk of Barrett's Oesophagus and Oesophageal Adenocarcinoma: A Pooled Analysis from the BEACON Consortium.

    Science.gov (United States)

    Lagergren, Katarina; Ek, Weronica E; Levine, David; Chow, Wong-Ho; Bernstein, Leslie; Casson, Alan G; Risch, Harvey A; Shaheen, Nicholas J; Bird, Nigel C; Reid, Brian J; Corley, Douglas A; Hardie, Laura J; Wu, Anna H; Fitzgerald, Rebecca C; Pharoah, Paul; Caldas, Carlos; Romero, Yvonne; Vaughan, Thomas L; MacGregor, Stuart; Whiteman, David; Westberg, Lars; Nyren, Olof; Lagergren, Jesper

    2015-01-01

    The strong male predominance in oesophageal adenocarcinoma (OAC) and Barrett's oesophagus (BO) continues to puzzle. Hormonal influence, e.g. oestrogen or oxytocin, might contribute. This genetic-epidemiological study pooled 14 studies from three continents, Australia, Europe, and North America. Polymorphisms in 3 key genes coding for the oestrogen pathway (receptor alpha (ESR1), receptor beta (ESR2), and aromatase (CYP19A1)), and 3 key genes of the oxytocin pathway (the oxytocin receptor (OXTR), oxytocin protein (OXT), and cyclic ADP ribose hydrolase glycoprotein (CD38)), were analysed using a gene-based approach, versatile gene-based test association study (VEGAS). Among 1508 OAC patients, 2383 BO patients, and 2170 controls, genetic variants within ESR1 were associated with BO in males (p = 0.0058) and an increased risk of OAC and BO combined in males (p = 0.0023). Genetic variants within OXTR were associated with an increased risk of BO in both sexes combined (p = 0.0035) and in males (p = 0.0012). We followed up these suggestive findings in a further smaller data set, but found no replication. There were no significant associations between the other 4 genes studied and risk of OAC, BO, separately on in combination, in males and females combined or in males only. Genetic variants in the oestrogen receptor alpha and the oxytocin receptor may be associated with an increased risk of BO or OAC, but replication in other large samples are needed.

  2. Identification of protein features encoded by alternative exons using Exon Ontology.

    Science.gov (United States)

    Tranchevent, Léon-Charles; Aubé, Fabien; Dulaurier, Louis; Benoit-Pilven, Clara; Rey, Amandine; Poret, Arnaud; Chautard, Emilie; Mortada, Hussein; Desmet, François-Olivier; Chakrama, Fatima Zahra; Moreno-Garcia, Maira Alejandra; Goillot, Evelyne; Janczarski, Stéphane; Mortreux, Franck; Bourgeois, Cyril F; Auboeuf, Didier

    2017-06-01

    Transcriptomic genome-wide analyses demonstrate massive variation of alternative splicing in many physiological and pathological situations. One major challenge is now to establish the biological contribution of alternative splicing variation in physiological- or pathological-associated cellular phenotypes. Toward this end, we developed a computational approach, named "Exon Ontology," based on terms corresponding to well-characterized protein features organized in an ontology tree. Exon Ontology is conceptually similar to Gene Ontology-based approaches but focuses on exon-encoded protein features instead of gene level functional annotations. Exon Ontology describes the protein features encoded by a selected list of exons and looks for potential Exon Ontology term enrichment. By applying this strategy to exons that are differentially spliced between epithelial and mesenchymal cells and after extensive experimental validation, we demonstrate that Exon Ontology provides support to discover specific protein features regulated by alternative splicing. We also show that Exon Ontology helps to unravel biological processes that depend on suites of coregulated alternative exons, as we uncovered a role of epithelial cell-enriched splicing factors in the AKT signaling pathway and of mesenchymal cell-enriched splicing factors in driving splicing events impacting on autophagy. Freely available on the web, Exon Ontology is the first computational resource that allows getting a quick insight into the protein features encoded by alternative exons and investigating whether coregulated exons contain the same biological information. © 2017 Tranchevent et al.; Published by Cold Spring Harbor Laboratory Press.

  3. Knowledge retrieval from PubMed abstracts and electronic medical records with the Multiple Sclerosis Ontology.

    Science.gov (United States)

    Malhotra, Ashutosh; Gündel, Michaela; Rajput, Abdul Mateen; Mevissen, Heinz-Theodor; Saiz, Albert; Pastor, Xavier; Lozano-Rubi, Raimundo; Martinez-Lapiscina, Elena H; Martinez-Lapsicina, Elena H; Zubizarreta, Irati; Mueller, Bernd; Kotelnikova, Ekaterina; Toldo, Luca; Hofmann-Apitius, Martin; Villoslada, Pablo

    2015-01-01

    In order to retrieve useful information from scientific literature and electronic medical records (EMR) we developed an ontology specific for Multiple Sclerosis (MS). The MS Ontology was created using scientific literature and expert review under the Protégé OWL environment. We developed a dictionary with semantic synonyms and translations to different languages for mining EMR. The MS Ontology was integrated with other ontologies and dictionaries (diseases/comorbidities, gene/protein, pathways, drug) into the text-mining tool SCAIView. We analyzed the EMRs from 624 patients with MS using the MS ontology dictionary in order to identify drug usage and comorbidities in MS. Testing competency questions and functional evaluation using F statistics further validated the usefulness of MS ontology. Validation of the lexicalized ontology by means of named entity recognition-based methods showed an adequate performance (F score = 0.73). The MS Ontology retrieved 80% of the genes associated with MS from scientific abstracts and identified additional pathways targeted by approved disease-modifying drugs (e.g. apoptosis pathways associated with mitoxantrone, rituximab and fingolimod). The analysis of the EMR from patients with MS identified current usage of disease modifying drugs and symptomatic therapy as well as comorbidities, which are in agreement with recent reports. The MS Ontology provides a semantic framework that is able to automatically extract information from both scientific literature and EMR from patients with MS, revealing new pathogenesis insights as well as new clinical information.

  4. The International Human Epigenome Consortium

    DEFF Research Database (Denmark)

    Stunnenberg, Hendrik G; Hirst, Martin

    2016-01-01

    The International Human Epigenome Consortium (IHEC) coordinates the generation of a catalog of high-resolution reference epigenomes of major primary human cell types. The studies now presented (see the Cell Press IHEC web portal at http://www.cell.com/consortium/IHEC) highlight the coordinated ac...

  5. Hawaii Space Grant Consortium

    Science.gov (United States)

    Flynn, Luke P.

    2005-01-01

    The Hawai'i Space Grant Consortium is composed of ten institutions of higher learning including the University of Hawai'i at Manoa, the University of Hawai'i at Hilo, the University of Guam, and seven Community Colleges spread over the 4 main Hawaiian islands. Geographic separation is not the only obstacle that we face as a Consortium. Hawai'i has been mired in an economic downturn due to a lack of tourism for almost all of the period (2001 - 2004) covered by this report, although hotel occupancy rates and real estate sales have sky-rocketed in the last year. Our challenges have been many including providing quality educational opportunities in the face of shrinking State and Federal budgets, encouraging science and technology course instruction at the K-12 level in a public school system that is becoming less focused on high technology and more focused on developing basic reading and math skills, and assembling community college programs with instructors who are expected to teach more classes for the same salary. Motivated people can overcome these problems. Fortunately, the Hawai'i Space Grant Consortium (HSGC) consists of a group of highly motivated and talented individuals who have not only overcome these obstacles, but have excelled with the Program. We fill a critical need within the State of Hawai'i to provide our children with opportunities to pursue their dreams of becoming the next generation of NASA astronauts, engineers, and explorers. Our strength lies not only in our diligent and creative HSGC advisory board, but also with Hawai'i's teachers, students, parents, and industry executives who are willing to invest their time, effort, and resources into Hawai'i's future. Our operational philosophy is to FACE the Future, meaning that we will facilitate, administer, catalyze, and educate in order to achieve our objective of creating a highly technically capable workforce both here in Hawai'i and for NASA. In addition to administering to programs and

  6. GAS STORAGE TECHNOLOGY CONSORTIUM

    Energy Technology Data Exchange (ETDEWEB)

    Robert W. Watson

    2004-10-18

    Gas storage is a critical element in the natural gas industry. Producers, transmission and distribution companies, marketers, and end users all benefit directly from the load balancing function of storage. The unbundling process has fundamentally changed the way storage is used and valued. As an unbundled service, the value of storage is being recovered at rates that reflect its value. Moreover, the marketplace has differentiated between various types of storage services, and has increasingly rewarded flexibility, safety, and reliability. The size of the natural gas market has increased and is projected to continue to increase towards 30 trillion cubic feet (TCF) over the next 10 to 15 years. Much of this increase is projected to come from electric generation, particularly peaking units. Gas storage, particularly the flexible services that are most suited to electric loads, is critical in meeting the needs of these new markets. In order to address the gas storage needs of the natural gas industry, an industry-driven consortium was created--the Gas Storage Technology Consortium (GSTC). The objective of the GSTC is to provide a means to accomplish industry-driven research and development designed to enhance operational flexibility and deliverability of the Nation's gas storage system, and provide a cost effective, safe, and reliable supply of natural gas to meet domestic demand. To accomplish this objective, the project is divided into three phases that are managed and directed by the GSTC Coordinator. The first phase, Phase 1A, was initiated on September 30, 2003, and was completed on March 31, 2004. Phase 1A of the project included the creation of the GSTC structure, development and refinement of a technical approach (work plan) for deliverability enhancement and reservoir management. This report deals with Phase 1B and encompasses the period July 1, 2004, through September 30, 2004. During this time period there were three main activities. First was the

  7. Logic and Ontology

    Directory of Open Access Journals (Sweden)

    Newton C. A. da Costa

    2002-12-01

    Full Text Available In view of the present state of development of non classical logic, especially of paraconsistent logic, a new stand regarding the relations between logic and ontology is defended In a parody of a dictum of Quine, my stand May be summarized as follows. To be is to be the value of a variable a specific language with a given underlying logic Yet my stand differs from Quine’s, because, among other reasons, I accept some first order heterodox logics as genuine alternatives to classical logic I also discuss some questions of non classical logic to substantiate my argument, and suggest that may position complements and extends some ideas advanced by L Apostel.

  8. Building a developmental toxicity ontology.

    Science.gov (United States)

    Baker, Nancy; Boobis, Alan; Burgoon, Lyle; Carney, Edward; Currie, Richard; Fritsche, Ellen; Knudsen, Thomas; Laffont, Madeleine; Piersma, Aldert H; Poole, Alan; Schneider, Steffen; Daston, George

    2018-04-03

    As more information is generated about modes of action for developmental toxicity and more data are generated using high-throughput and high-content technologies, it is becoming necessary to organize that information. This report discussed the need for a systematic representation of knowledge about developmental toxicity (i.e., an ontology) and proposes a method to build one based on knowledge of developmental biology and mode of action/ adverse outcome pathways in developmental toxicity. This report is the result of a consensus working group developing a plan to create an ontology for developmental toxicity that spans multiple levels of biological organization. This report provide a description of some of the challenges in building a developmental toxicity ontology and outlines a proposed methodology to meet those challenges. As the ontology is built on currently available web-based resources, a review of these resources is provided. Case studies on one of the most well-understood morphogens and developmental toxicants, retinoic acid, are presented as examples of how such an ontology might be developed. This report outlines an approach to construct a developmental toxicity ontology. Such an ontology will facilitate computer-based prediction of substances likely to induce human developmental toxicity. © 2018 Wiley Periodicals, Inc.

  9. Polymorphism in the GALNT1 gene and epithelial ovarian cancer in non-Hispanic white women: the Ovarian Cancer Association Consortium

    DEFF Research Database (Denmark)

    Phelan, Catherine M; Tsai, Ya-Yu; Goode, Ellen L

    2010-01-01

    Aberrant glycosylation is a well-described hallmark of cancer. In a previous ovarian cancer case control study that examined polymorphisms in 26 glycosylation-associated genes, we found strong statistical evidence (P = 0.00017) that women who inherited two copies of a single-nucleotide polymorphism...... sites but significant differences compared with the original study population (P = 0.03). This study underscores the need for replication of putative findings in genetic association studies....

  10. Nuclear Fabrication Consortium

    Energy Technology Data Exchange (ETDEWEB)

    Levesque, Stephen [EWI, Columbus, OH (United States)

    2013-04-05

    This report summarizes the activities undertaken by EWI while under contract from the Department of Energy (DOE) Office of Nuclear Energy (NE) for the management and operation of the Nuclear Fabrication Consortium (NFC). The NFC was established by EWI to independently develop, evaluate, and deploy fabrication approaches and data that support the re-establishment of the U.S. nuclear industry: ensuring that the supply chain will be competitive on a global stage, enabling more cost-effective and reliable nuclear power in a carbon constrained environment. The NFC provided a forum for member original equipment manufactures (OEM), fabricators, manufacturers, and materials suppliers to effectively engage with each other and rebuild the capacity of this supply chain by : Identifying and removing impediments to the implementation of new construction and fabrication techniques and approaches for nuclear equipment, including system components and nuclear plants. Providing and facilitating detailed scientific-based studies on new approaches and technologies that will have positive impacts on the cost of building of nuclear plants. Analyzing and disseminating information about future nuclear fabrication technologies and how they could impact the North American and the International Nuclear Marketplace. Facilitating dialog and initiate alignment among fabricators, owners, trade associations, and government agencies. Supporting industry in helping to create a larger qualified nuclear supplier network. Acting as an unbiased technology resource to evaluate, develop, and demonstrate new manufacturing technologies. Creating welder and inspector training programs to help enable the necessary workforce for the upcoming construction work. Serving as a focal point for technology, policy, and politically interested parties to share ideas and concepts associated with fabrication across the nuclear industry. The report the objectives and summaries of the Nuclear Fabrication Consortium

  11. There is no quantum ontology without classical ontology

    Energy Technology Data Exchange (ETDEWEB)

    Fink, Helmut [Institut fuer Theoretische Physik, Univ. Erlangen-Nuernberg (Germany)

    2011-07-01

    The relation between quantum physics and classical physics is still under debate. In his recent book ''Rational Reconstructions of Modern Physics'', Peter Mittelstaedt explores a route from classical to quantum mechanics by reduction and elimination of (some of) the ontological hypotheses underlying classical mechanics. While, according to Mittelstaedt, classical mechanics describes a fictitious world that does not exist in reality, he claims to achieve a universal quantum ontology that can be improved by incorporating unsharp properties and equipped with Planck's constant without any need to refer to classical concepts. In this talk, we argue that quantum ontology in Mittelstaedt's sense is not enough. Quantum ontology can never be universal as long as the difference between potential and real properties is not represented adequately. Quantum properties are potential, not (yet) real, be they sharp or unsharp. Hence, preparation and measurement presuppose classical concepts, even in quantum theory. We end up with a classical-quantum sandwich ontology, which is still less extravagant than Bohmian or many-worlds ontologies are.

  12. development of ontological knowledge representation

    African Journals Online (AJOL)

    Preferred Customer

    ABSTRACT. This paper presents the development of an ontological knowledge organization and .... intelligence in order to facilitate knowledge sharing and reuse of acquired knowledge (15). Soon, ..... Water Chemistry, AJCE, 1(2), 50-58. 25.

  13. A Mobile Army of Ontologies

    DEFF Research Database (Denmark)

    Juul, Jesper

    2015-01-01

    Presentation at the Ludo-ontologies panel. Do we need ludo-ontologies, and what are they? In this event several scholars of games and videogames discuss these questions from a variety of perspectives. What different game and videogame ontologies exist and could exist, and why they are important...... for game and videogame research? The round table is designed to promote ludo-ontological dialogue in order to make these questions visible and debated. A series of short presentations (approximately 10 minutes each) will be followed by an intense debate through freeform dialogue. After the industrial...... commercialization of games and videogames their study has shifted between approaches focused on players (ludic processes) and artifacts (ludic objects). Some attempts to analyze the relationship between the process and the object have occasionally been done in terms of ‘ontology’ (Zagal 2005; Leino 2010; Gualeni...

  14. Gas Storage Technology Consortium

    Energy Technology Data Exchange (ETDEWEB)

    Joel Morrison; Elizabeth Wood; Barbara Robuck

    2010-09-30

    The EMS Energy Institute at The Pennsylvania State University (Penn State) has managed the Gas Storage Technology Consortium (GSTC) since its inception in 2003. The GSTC infrastructure provided a means to accomplish industry-driven research and development designed to enhance the operational flexibility and deliverability of the nation's gas storage system, and provide a cost-effective, safe, and reliable supply of natural gas to meet domestic demand. The GSTC received base funding from the U.S. Department of Energy's (DOE) National Energy Technology Laboratory (NETL) Oil & Natural Gas Supply Program. The GSTC base funds were highly leveraged with industry funding for individual projects. Since its inception, the GSTC has engaged 67 members. The GSTC membership base was diverse, coming from 19 states, the District of Columbia, and Canada. The membership was comprised of natural gas storage field operators, service companies, industry consultants, industry trade organizations, and academia. The GSTC organized and hosted a total of 18 meetings since 2003. Of these, 8 meetings were held to review, discuss, and select proposals submitted for funding consideration. The GSTC reviewed a total of 75 proposals and committed co-funding to support 31 industry-driven projects. The GSTC committed co-funding to 41.3% of the proposals that it received and reviewed. The 31 projects had a total project value of $6,203,071 of which the GSTC committed $3,205,978 in co-funding. The committed GSTC project funding represented an average program cost share of 51.7%. Project applicants provided an average program cost share of 48.3%. In addition to the GSTC co-funding, the consortium provided the domestic natural gas storage industry with a technology transfer and outreach infrastructure. The technology transfer and outreach were conducted by having project mentoring teams and a GSTC website, and by working closely with the Pipeline Research Council International (PRCI) to

  15. Building a Chemical Ontology using Methontology and the Ontology Design Environment

    OpenAIRE

    Fernández López, Mariano; Gómez-Pérez, A.; Pazos Sierra, Alejandro; Pazos Sierra, Juan

    1999-01-01

    METHONTOLOGY PROVIDES GUIDELINES FOR SPECIFYING ONTOLOGIES AT THE KNOWLEDGE LEVEL, AS A SPECIFICATION OF A CONCEPTUALIZATION. ODE ENABLES ONTOLOGY CONSTRUCTION, COVERING THE ENTIRE LIFE CYCLE AND AUTOMATICALLY IMPLEMENTING ONTOLOGIES

  16. External RNA Controls Consortium Beta Version Update.

    Science.gov (United States)

    Lee, Hangnoh; Pine, P Scott; McDaniel, Jennifer; Salit, Marc; Oliver, Brian

    2016-01-01

    Spike-in RNAs are valuable controls for a variety of gene expression measurements. The External RNA Controls Consortium developed test sets that were used in a number of published reports. Here we provide an authoritative table that summarizes, updates, and corrects errors in the test version that ultimately resulted in the certified Standard Reference Material 2374. We have noted existence of anti-sense RNA controls in the material, corrected sub-pool memberships, and commented on control RNAs that displayed inconsistent behavior.

  17. ``Force,'' ontology, and language

    Science.gov (United States)

    Brookes, David T.; Etkina, Eugenia

    2009-06-01

    We introduce a linguistic framework through which one can interpret systematically students’ understanding of and reasoning about force and motion. Some researchers have suggested that students have robust misconceptions or alternative frameworks grounded in everyday experience. Others have pointed out the inconsistency of students’ responses and presented a phenomenological explanation for what is observed, namely, knowledge in pieces. We wish to present a view that builds on and unifies aspects of this prior research. Our argument is that many students’ difficulties with force and motion are primarily due to a combination of linguistic and ontological difficulties. It is possible that students are primarily engaged in trying to define and categorize the meaning of the term “force” as spoken about by physicists. We found that this process of negotiation of meaning is remarkably similar to that engaged in by physicists in history. In this paper we will describe a study of the historical record that reveals an analogous process of meaning negotiation, spanning multiple centuries. Using methods from cognitive linguistics and systemic functional grammar, we will present an analysis of the force and motion literature, focusing on prior studies with interview data. We will then discuss the implications of our findings for physics instruction.

  18. Atlantic Coast Environmental Indicators Consortium

    Data.gov (United States)

    Federal Laboratory Consortium — n 2000, the US EPA granted authority to establish up to five Estuarine Indicator Research Programs. These Programs were designed to identify, evaluate, recommend and...

  19. NCI Pediatric Preclinical Testing Consortium

    Science.gov (United States)

    NCI has awarded grants to five research teams to participate in its Pediatric Preclinical Testing Consortium, which is intended to help to prioritize which agents to pursue in pediatric clinical trials.

  20. Hickory Consortium 2001 Final Report

    Energy Technology Data Exchange (ETDEWEB)

    2003-02-01

    As with all Building America Program consortia, systems thinking is the key to understanding the processes that Hickory Consortium hopes to improve. The Hickory Consortium applies this thinking to more than the whole-building concept. Their systems thinking embraces the meta process of how housing construction takes place in America. By understanding the larger picture, they are able to identify areas where improvements can be made and how to implement them.

  1. Combustion Byproducts Recycling Consortium

    Energy Technology Data Exchange (ETDEWEB)

    Ziemkiewicz, Paul; Vandivort, Tamara; Pflughoeft-Hassett, Debra; Chugh, Y Paul; Hower, James

    2008-08-31

    Each year, over 100 million tons of solid byproducts are produced by coal-burning electric utilities in the United States. Annual production of flue gas desulfurization (FGD) byproducts continues to increase as the result of more stringent sulfur emission restrictions. In addition, stricter limits on NOx emissions mandated by the 1990 Clean Air Act have resulted in utility burner/boiler modifications that frequently yield higher carbon concentrations in fly ash, which restricts the use of the ash as a cement replacement. Controlling ammonia in ash is also of concern. If newer, “clean coal” combustion and gasification technologies are adopted, their byproducts may also present a management challenge. The objective of the Combustion Byproducts Recycling Consortium (CBRC) is to develop and demonstrate technologies to address issues related to the recycling of byproducts associated with coal combustion processes. A goal of CBRC is that these technologies, by the year 2010, will lead to an overall ash utilization rate from the current 34% to 50% by such measures as increasing the current rate of FGD byproduct use and increasing in the number of uses considered “allowable” under state regulations. Another issue of interest to the CBRC would be to examine the environmental impact of both byproduct utilization and disposal. No byproduct utilization technology is likely to be adopted by industry unless it is more cost-effective than landfilling. Therefore, it is extremely important that the utility industry provide guidance to the R&D program. Government agencies and privatesector organizations that may be able to utilize these materials in the conduct of their missions should also provide input. The CBRC will serve as an effective vehicle for acquiring and maintaining guidance from these diverse organizations so that the proper balance in the R&D program is achieved.

  2. Use of the CIM Ontology

    Energy Technology Data Exchange (ETDEWEB)

    Neumann, Scott; Britton, Jay; Devos, Arnold N.; Widergren, Steven E.

    2006-02-08

    There are many uses for the Common Information Model (CIM), an ontology that is being standardized through Technical Committee 57 of the International Electrotechnical Commission (IEC TC57). The most common uses to date have included application modeling, information exchanges, information management and systems integration. As one should expect, there are many issues that become apparent when the CIM ontology is applied to any one use. Some of these issues are shortcomings within the current draft of the CIM, and others are a consequence of the different ways in which the CIM can be applied using different technologies. As the CIM ontology will and should evolve, there are several dangers that need to be recognized. One is overall consistency and impact upon applications when extending the CIM for a specific need. Another is that a tight coupling of the CIM to specific technologies could limit the value of the CIM in the longer term as an ontology, which becomes a larger issue over time as new technologies emerge. The integration of systems is one specific area of interest for application of the CIM ontology. This is an area dominated by the use of XML for the definition of messages. While this is certainly true when using Enterprise Application Integration (EAI) products, it is even more true with the movement towards the use of Web Services (WS), Service-Oriented Architectures (SOA) and Enterprise Service Buses (ESB) for integration. This general IT industry trend is consistent with trends seen within the IEC TC57 scope of power system management and associated information exchange. The challenge for TC57 is how to best leverage the CIM ontology using the various XML technologies and standards for integration. This paper will provide examples of how the CIM ontology is used and describe some specific issues that should be addressed within the CIM in order to increase its usefulness as an ontology. It will also describe some of the issues and challenges that will

  3. Microarray gene expression profiling and analysis in renal cell carcinoma

    Directory of Open Access Journals (Sweden)

    Sadhukhan Provash

    2004-06-01

    Full Text Available Abstract Background Renal cell carcinoma (RCC is the most common cancer in adult kidney. The accuracy of current diagnosis and prognosis of the disease and the effectiveness of the treatment for the disease are limited by the poor understanding of the disease at the molecular level. To better understand the genetics and biology of RCC, we profiled the expression of 7,129 genes in both clear cell RCC tissue and cell lines using oligonucleotide arrays. Methods Total RNAs isolated from renal cell tumors, adjacent normal tissue and metastatic RCC cell lines were hybridized to affymatrix HuFL oligonucleotide arrays. Genes were categorized into different functional groups based on the description of the Gene Ontology Consortium and analyzed based on the gene expression levels. Gene expression profiles of the tissue and cell line samples were visualized and classified by singular value decomposition. Reverse transcription polymerase chain reaction was performed to confirm the expression alterations of selected genes in RCC. Results Selected genes were annotated based on biological processes and clustered into functional groups. The expression levels of genes in each group were also analyzed. Seventy-four commonly differentially expressed genes with more than five-fold changes in RCC tissues were identified. The expression alterations of selected genes from these seventy-four genes were further verified using reverse transcription polymerase chain reaction (RT-PCR. Detailed comparison of gene expression patterns in RCC tissue and RCC cell lines shows significant differences between the two types of samples, but many important expression patterns were preserved. Conclusions This is one of the initial studies that examine the functional ontology of a large number of genes in RCC. Extensive annotation, clustering and analysis of a large number of genes based on the gene functional ontology revealed many interesting gene expression patterns in RCC. Most

  4. Protein complex prediction in large ontology attributed protein-protein interaction networks.

    Science.gov (United States)

    Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Li, Yanpeng; Xu, Bo

    2013-01-01

    Protein complexes are important for unraveling the secrets of cellular organization and function. Many computational approaches have been developed to predict protein complexes in protein-protein interaction (PPI) networks. However, most existing approaches focus mainly on the topological structure of PPI networks, and largely ignore the gene ontology (GO) annotation information. In this paper, we constructed ontology attributed PPI networks with PPI data and GO resource. After constructing ontology attributed networks, we proposed a novel approach called CSO (clustering based on network structure and ontology attribute similarity). Structural information and GO attribute information are complementary in ontology attributed networks. CSO can effectively take advantage of the correlation between frequent GO annotation sets and the dense subgraph for protein complex prediction. Our proposed CSO approach was applied to four different yeast PPI data sets and predicted many well-known protein complexes. The experimental results showed that CSO was valuable in predicting protein complexes and achieved state-of-the-art performance.

  5. Toward semantic interoperability with linked foundational ontologies in ROMULUS

    CSIR Research Space (South Africa)

    Khan, ZC

    2013-06-01

    Full Text Available A purpose of a foundational ontology is to solve interoperability issues among ontologies. Many foundational ontologies have been developed, reintroducing the ontology interoperability problem. We address this with the new online foundational...

  6. Drug target ontology to classify and integrate drug discovery data.

    Science.gov (United States)

    Lin, Yu; Mehta, Saurabh; Küçük-McGinty, Hande; Turner, John Paul; Vidovic, Dusica; Forlin, Michele; Koleti, Amar; Nguyen, Dac-Trung; Jensen, Lars Juhl; Guha, Rajarshi; Mathias, Stephen L; Ursu, Oleg; Stathias, Vasileios; Duan, Jianbin; Nabizadeh, Nooshin; Chung, Caty; Mader, Christopher; Visser, Ubbo; Yang, Jeremy J; Bologa, Cristian G; Oprea, Tudor I; Schürer, Stephan C

    2017-11-09

    model for druggable targets including various related information such as protein, gene, protein domain, protein structure, binding site, small molecule drug, mechanism of action, protein tissue localization, disease association, and many other types of information. DTO will further facilitate the otherwise challenging integration and formal linking to biological assays, phenotypes, disease models, drug poly-pharmacology, binding kinetics and many other processes, functions and qualities that are at the core of drug discovery. The first version of DTO is publically available via the website http://drugtargetontology.org/ , Github ( http://github.com/DrugTargetOntology/DTO ), and the NCBO Bioportal ( http://bioportal.bioontology.org/ontologies/DTO ). The long-term goal of DTO is to provide such an integrative framework and to populate the ontology with this information as a community resource.

  7. Complex Topographic Feature Ontology Patterns

    Science.gov (United States)

    Varanka, Dalia E.; Jerris, Thomas J.

    2015-01-01

    Semantic ontologies are examined as effective data models for the representation of complex topographic feature types. Complex feature types are viewed as integrated relations between basic features for a basic purpose. In the context of topographic science, such component assemblages are supported by resource systems and found on the local landscape. Ontologies are organized within six thematic modules of a domain ontology called Topography that includes within its sphere basic feature types, resource systems, and landscape types. Context is constructed not only as a spatial and temporal setting, but a setting also based on environmental processes. Types of spatial relations that exist between components include location, generative processes, and description. An example is offered in a complex feature type ‘mine.’ The identification and extraction of complex feature types are an area for future research.

  8. Geographic Ontologies, Gazetteers and Multilingualism

    Directory of Open Access Journals (Sweden)

    Robert Laurini

    2015-01-01

    Full Text Available Different languages imply different visions of space, so that terminologies are different in geographic ontologies. In addition to their geometric shapes, geographic features have names, sometimes different in diverse languages. In addition, the role of gazetteers, as dictionaries of place names (toponyms, is to maintain relations between place names and location. The scope of geographic information retrieval is to search for geographic information not against a database, but against the whole Internet: but the Internet stores information in different languages, and it is of paramount importance not to remain stuck to a unique language. In this paper, our first step is to clarify the links between geographic objects as computer representations of geographic features, ontologies and gazetteers designed in various languages. Then, we propose some inference rules for matching not only types, but also relations in geographic ontologies with the assistance of gazetteers.

  9. Ontology Matching with Semantic Verification.

    Science.gov (United States)

    Jean-Mary, Yves R; Shironoshita, E Patrick; Kabuka, Mansur R

    2009-09-01

    ASMOV (Automated Semantic Matching of Ontologies with Verification) is a novel algorithm that uses lexical and structural characteristics of two ontologies to iteratively calculate a similarity measure between them, derives an alignment, and then verifies it to ensure that it does not contain semantic inconsistencies. In this paper, we describe the ASMOV algorithm, and then present experimental results that measure its accuracy using the OAEI 2008 tests, and that evaluate its use with two different thesauri: WordNet, and the Unified Medical Language System (UMLS). These results show the increased accuracy obtained by combining lexical, structural and extensional matchers with semantic verification, and demonstrate the advantage of using a domain-specific thesaurus for the alignment of specialized ontologies.

  10. An ontology approach to comparative phenomics in plants

    KAUST Repository

    Oellrich, Anika

    2015-02-25

    Background: Plant phenotype datasets include many different types of data, formats, and terms from specialized vocabularies. Because these datasets were designed for different audiences, they frequently contain language and details tailored to investigators with different research objectives and backgrounds. Although phenotype comparisons across datasets have long been possible on a small scale, comprehensive queries and analyses that span a broad set of reference species, research disciplines, and knowledge domains continue to be severely limited by the absence of a common semantic framework. Results: We developed a workflow to curate and standardize existing phenotype datasets for six plant species, encompassing both model species and crop plants with established genetic resources. Our effort focused on mutant phenotypes associated with genes of known sequence in Arabidopsis thaliana (L.) Heynh. (Arabidopsis), Zea mays L. subsp. mays (maize), Medicago truncatula Gaertn. (barrel medic or Medicago), Oryza sativa L. (rice), Glycine max (L.) Merr. (soybean), and Solanum lycopersicum L. (tomato). We applied the same ontologies, annotation standards, formats, and best practices across all six species, thereby ensuring that the shared dataset could be used for cross-species querying and semantic similarity analyses. Curated phenotypes were first converted into a common format using taxonomically broad ontologies such as the Plant Ontology, Gene Ontology, and Phenotype and Trait Ontology. We then compared ontology-based phenotypic descriptions with an existing classification system for plant phenotypes and evaluated our semantic similarity dataset for its ability to enhance predictions of gene families, protein functions, and shared metabolic pathways that underlie informative plant phenotypes. Conclusions: The use of ontologies, annotation standards, shared formats, and best practices for cross-taxon phenotype data analyses represents a novel approach to plant phenomics

  11. An ontology approach to comparative phenomics in plants

    KAUST Repository

    Oellrich, Anika; Walls, Ramona L; Cannon, Ethalinda KS; Cannon, Steven B; Cooper, Laurel; Gardiner, Jack; Gkoutos, Georgios V; Harper, Lisa; He, Mingze; Hoehndorf, Robert; Jaiswal, Pankaj; Kalberer, Scott R; Lloyd, John P; Meinke, David; Menda, Naama; Moore, Laura; Nelson, Rex T; Pujar, Anuradha; Lawrence, Carolyn J; Huala, Eva

    2015-01-01

    Background: Plant phenotype datasets include many different types of data, formats, and terms from specialized vocabularies. Because these datasets were designed for different audiences, they frequently contain language and details tailored to investigators with different research objectives and backgrounds. Although phenotype comparisons across datasets have long been possible on a small scale, comprehensive queries and analyses that span a broad set of reference species, research disciplines, and knowledge domains continue to be severely limited by the absence of a common semantic framework. Results: We developed a workflow to curate and standardize existing phenotype datasets for six plant species, encompassing both model species and crop plants with established genetic resources. Our effort focused on mutant phenotypes associated with genes of known sequence in Arabidopsis thaliana (L.) Heynh. (Arabidopsis), Zea mays L. subsp. mays (maize), Medicago truncatula Gaertn. (barrel medic or Medicago), Oryza sativa L. (rice), Glycine max (L.) Merr. (soybean), and Solanum lycopersicum L. (tomato). We applied the same ontologies, annotation standards, formats, and best practices across all six species, thereby ensuring that the shared dataset could be used for cross-species querying and semantic similarity analyses. Curated phenotypes were first converted into a common format using taxonomically broad ontologies such as the Plant Ontology, Gene Ontology, and Phenotype and Trait Ontology. We then compared ontology-based phenotypic descriptions with an existing classification system for plant phenotypes and evaluated our semantic similarity dataset for its ability to enhance predictions of gene families, protein functions, and shared metabolic pathways that underlie informative plant phenotypes. Conclusions: The use of ontologies, annotation standards, shared formats, and best practices for cross-taxon phenotype data analyses represents a novel approach to plant phenomics

  12. Linking human diseases to animal models using ontology-based phenotype annotation.

    Directory of Open Access Journals (Sweden)

    Nicole L Washington

    2009-11-01

    Full Text Available Scientists and clinicians who study genetic alterations and disease have traditionally described phenotypes in natural language. The considerable variation in these free-text descriptions has posed a hindrance to the important task of identifying candidate genes and models for human diseases and indicates the need for a computationally tractable method to mine data resources for mutant phenotypes. In this study, we tested the hypothesis that ontological annotation of disease phenotypes will facilitate the discovery of new genotype-phenotype relationships within and across species. To describe phenotypes using ontologies, we used an Entity-Quality (EQ methodology, wherein the affected entity (E and how it is affected (Q are recorded using terms from a variety of ontologies. Using this EQ method, we annotated the phenotypes of 11 gene-linked human diseases described in Online Mendelian Inheritance in Man (OMIM. These human annotations were loaded into our Ontology-Based Database (OBD along with other ontology-based phenotype descriptions of mutants from various model organism databases. Phenotypes recorded with this EQ method can be computationally compared based on the hierarchy of terms in the ontologies and the frequency of annotation. We utilized four similarity metrics to compare phenotypes and developed an ontology of homologous and analogous anatomical structures to compare phenotypes between species. Using these tools, we demonstrate that we can identify, through the similarity of the recorded phenotypes, other alleles of the same gene, other members of a signaling pathway, and orthologous genes and pathway members across species. We conclude that EQ-based annotation of phenotypes, in conjunction with a cross-species ontology, and a variety of similarity metrics can identify biologically meaningful similarities between genes by comparing phenotypes alone. This annotation and search method provides a novel and efficient means to identify

  13. Inferring ontology graph structures using OWL reasoning

    KAUST Repository

    Rodriguez-Garcia, Miguel Angel; Hoehndorf, Robert

    2018-01-01

    ' semantic content remains a challenge.We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies

  14. Ontologies, Knowledge Bases and Knowledge Management

    National Research Council Canada - National Science Library

    Chalupsky, Hans

    2002-01-01

    ...) an application called Strategy Development Assistant (SDA) that uses that ontology. The JFACC ontology served as a basis for knowledge sharing among several applications in the domain of air campaign planning...

  15. Addressing issues in foundational ontology mediation

    CSIR Research Space (South Africa)

    Khan, ZC

    2013-09-01

    Full Text Available An approach in achieving semantic interoperability among heterogeneous systems is to offer infrastructure to assist with linking and integration using a foundational ontology. Due to the creation of multiple foundational ontologies, this also means...

  16. Technique for designing a domain ontology

    OpenAIRE

    Palagin, A. V.; Petrenko, N. G.; Malakhov, K. S.

    2018-01-01

    The article describes the technique for designing a domain ontology, shows the flowchart of algorithm design and example of constructing a fragment of the ontology of the subject area of Computer Science is considered.

  17. Platonic wholes and quantum ontology

    CERN Document Server

    Woszczek, Marek

    2015-01-01

    The subject of the book is a reconsideration of the internalistic model of composition of the Platonic type, more radical than traditional, post-Aristotelian externalistic compositionism, and its application in the field of the ontology of quantum theory. At the centre of quantum ontology is nonseparability. Quantum wholes are atemporal wholes governed by internalistic logic and they are primitive, global physical entities, requiring an extreme relativization of the fundamental notions of mechanics. That ensures quantum theory to be fully consistent with the relativistic causal structure, with

  18. Multimedia ontology representation and applications

    CERN Document Server

    Chaudhury, Santanu; Ghosh, Hiranmay

    2015-01-01

    The result of more than 15 years of collective research, Multimedia Ontology: Representation and Applications provides a theoretical foundation for understanding the nature of media data and the principles involved in its interpretation. The book presents a unified approach to recent advances in multimedia and explains how a multimedia ontology can fill the semantic gap between concepts and the media world. It relays real-life examples of implementations in different domains to illustrate how this gap can be filled.The book contains information that helps with building semantic, content-based

  19. Root justifications for ontology repair

    CSIR Research Space (South Africa)

    Moodley, K

    2011-08-01

    Full Text Available stream_source_info Moodley_2011.pdf.txt stream_content_type text/plain stream_size 32328 Content-Encoding ISO-8859-1 stream_name Moodley_2011.pdf.txt Content-Type text/plain; charset=ISO-8859-1 Root Justi cations... the ontology, based on the no- tion of root justi cations [8, 9]. In Section 5, we discuss the implementation of a Prot eg e3 plugin which demonstrates our approach to ontology repair. In this section we also discuss some experimental results comparing...

  20. Towards ontology based search and knowledgesharing using domain ontologies

    DEFF Research Database (Denmark)

    Zambach, Sine

    verbs for relations in the ontology modeling. For this work we use frequency lists from a biomedical text corpus of different genres as well as a study of the relations used in other biomedical text mining tools. In addition, we discuss how these relations can be used in broarder perspective....

  1. An Ontology for Knowledge Representation and Applications

    OpenAIRE

    Nhon Do

    2008-01-01

    Ontology is a terminology which is used in artificial intelligence with different meanings. Ontology researching has an important role in computer science and practical applications, especially distributed knowledge systems. In this paper we present an ontology which is called Computational Object Knowledge Base Ontology. It has been used in designing some knowledge base systems for solving problems such as the system that supports studying knowledge and solving analytic ...

  2. On Algebraic Spectrum of Ontology Evaluation

    OpenAIRE

    Adekoya Adebayo Felix; kinwale Adio Taofiki; Sofoluwe Adetokunbo

    2011-01-01

    Ontology evaluation remains an important open problem in the area of its application. The ontology structure evaluation framework for benchmarking the internal graph structures was proposed. The framework was used in transport and biochemical ontology. The corresponding adjacency, incidence matrices and other structural properties due to the class hierarchical structure of the transport and biochemical ontology were computed using MATLAB. The results showed that the choice of suitable choice ...

  3. The National Astronomy Consortium (NAC)

    Science.gov (United States)

    Von Schill, Lyndele; Ivory, Joyce

    2017-01-01

    The National Astronomy Consortium (NAC) program is designed to increase the number of underrepresented minority students into STEM and STEM careers by providing unique summer research experiences followed by long-term mentoring and cohort support. Hallmarks of the NAC program include: research or internship opportunities at one of the NAC partner sites, a framework to continue research over the academic year, peer and faculty mentoring, monthly virtual hangouts, and much more. NAC students also participate in two professional travel opportunities each year: the annual NAC conference at Howard University and poster presentation at the annual AAS winter meeting following their summer internship.The National Astronomy Consortium (NAC) is a program led by the National Radio Astronomy Consortium (NRAO) and Associated Universities, Inc. (AUI), in partnership with the National Society of Black Physicist (NSBP), along with a number of minority and majority universities.

  4. BiNChE: a web tool and library for chemical enrichment analysis based on the ChEBI ontology.

    Science.gov (United States)

    Moreno, Pablo; Beisken, Stephan; Harsha, Bhavana; Muthukrishnan, Venkatesh; Tudose, Ilinca; Dekker, Adriano; Dornfeldt, Stefanie; Taruttis, Franziska; Grosse, Ivo; Hastings, Janna; Neumann, Steffen; Steinbeck, Christoph

    2015-02-21

    Ontology-based enrichment analysis aids in the interpretation and understanding of large-scale biological data. Ontologies are hierarchies of biologically relevant groupings. Using ontology annotations, which link ontology classes to biological entities, enrichment analysis methods assess whether there is a significant over or under representation of entities for ontology classes. While many tools exist that run enrichment analysis for protein sets annotated with the Gene Ontology, there are only a few that can be used for small molecules enrichment analysis. We describe BiNChE, an enrichment analysis tool for small molecules based on the ChEBI Ontology. BiNChE displays an interactive graph that can be exported as a high-resolution image or in network formats. The tool provides plain, weighted and fragment analysis based on either the ChEBI Role Ontology or the ChEBI Structural Ontology. BiNChE aids in the exploration of large sets of small molecules produced within Metabolomics or other Systems Biology research contexts. The open-source tool provides easy and highly interactive web access to enrichment analysis with the ChEBI ontology tool and is additionally available as a standalone library.

  5. An ontological approach to domain engineering

    NARCIS (Netherlands)

    Falbo, R.A.; Guizzardi, G.; Duarte, K.

    2002-01-01

    Domain engineering aims to support systematic reuse, focusing on modeling common knowledge in a problem domain. Ontologies have also been pointed as holding great promise for software reuse. In this paper, we present ODE (Ontology-based Domain Engineering), an ontological approach for domain

  6. Aspects of ontology visualization and integration

    NARCIS (Netherlands)

    Dmitrieva, Joelia Borisovna

    2011-01-01

    In this thesis we will describe and discuss methodologies for ontology visualization and integration. Two visualization methods will be elaborated. In one method the ontology is visualized with the node-link technique, and with the other method the ontology is visualized with the containment

  7. Combustion Byproducts Recycling Consortium

    Energy Technology Data Exchange (ETDEWEB)

    Paul Ziemkiewicz; Tamara Vandivort; Debra Pflughoeft-Hassett; Y. Paul Chugh; James Hower

    2008-08-31

    The Combustion Byproducts Recycling Consortium (CBRC) program was developed as a focused program to remove and/or minimize the barriers for effective management of over 123 million tons of coal combustion byproducts (CCBs) annually generated in the USA. At the time of launching the CBRC in 1998, about 25% of CCBs were beneficially utilized while the remaining was disposed in on-site or off-site landfills. During the ten (10) year tenure of CBRC (1998-2008), after a critical review, 52 projects were funded nationwide. By region, the East, Midwest, and West had 21, 18, and 13 projects funded, respectively. Almost all projects were cooperative projects involving industry, government, and academia. The CBRC projects, to a large extent, successfully addressed the problems of large-scale utilization of CCBs. A few projects, such as the two Eastern Region projects that addressed the use of fly ash in foundry applications, might be thought of as a somewhat smaller application in comparison to construction and agricultural uses, but as a novel niche use, they set the stage to draw interest that fly ash substitution for Portland cement might not attract. With consideration of the large increase in flue gas desulfurization (FGD) gypsum in response to EPA regulations, agricultural uses of FGD gypsum hold promise for large-scale uses of a product currently directed to the (currently stagnant) home construction market. Outstanding achievements of the program are: (1) The CBRC successfully enhanced professional expertise in the area of CCBs throughout the nation. The enhanced capacity continues to provide technology and information transfer expertise to industry and regulatory agencies. (2) Several technologies were developed that can be used immediately. These include: (a) Use of CCBs for road base and sub-base applications; (b) full-depth, in situ stabilization of gravel roads or highway/pavement construction recycled materials; and (c) fired bricks containing up to 30%-40% F

  8. Military Suicide Research Consortium

    Science.gov (United States)

    2015-10-01

    funded autism study – it covers autism spectrum disorders . He was not aware that DOD had this subject in their portfolio. He will be working with Dr...serotonin transporter gene and family history of depression? Journal of Affective Disorders , 77, 273-275. 8. Joiner, T., Sheldon, K., Williams, G...the military, impact unit morale, and take a large emotional toll on the involved friends, family , and commanders. As noted before with continued

  9. The OncoArray Consortium

    DEFF Research Database (Denmark)

    Amos, Christopher I; Dennis, Joe; Wang, Zhaoming

    2017-01-01

    by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy...... among centers and by ethnic background. RESULTS: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring...

  10. The ocean sampling day consortium

    DEFF Research Database (Denmark)

    Kopf, Anna; Bicak, Mesude; Kottmann, Renzo

    2015-01-01

    Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapshot of the marine microbial biodiversity and function of the world’s oceans. It is a simultaneous global mega-sequencing campaign aiming to generate...... the largest standardized microbial data set in a single day. This will be achievable only through the coordinated efforts of an Ocean Sampling Day Consortium, supportive partnerships and networks between sites. This commentary outlines the establishment, function and aims of the Consortium and describes our...

  11. Alignment of ICNP? 2.0 Ontology and a proposed INCP? Brazilian Ontology1

    OpenAIRE

    Carvalho, Carina Maris Gaspar; Cubas, Marcia Regina; Malucelli, Andreia; da N?brega, Maria Miriam Lima

    2014-01-01

    OBJECTIVE: to align the International Classification for Nursing Practice (ICNP®) Version 2.0 ontology and a proposed INCP® Brazilian Ontology.METHOD: document-based, exploratory and descriptive study, the empirical basis of which was provided by the ICNP® 2.0 Ontology and the INCP® Brazilian Ontology. The ontology alignment was performed using a computer tool with algorithms to identify correspondences between concepts, which were organized and analyzed according to their presence or absence...

  12. CLO : The cell line ontology

    NARCIS (Netherlands)

    Sarntivijai, Sirarat; Lin, Yu; Xiang, Zuoshuang; Meehan, Terrence F.; Diehl, Alexander D.; Vempati, Uma D.; Schuerer, Stephan C.; Pang, Chao; Malone, James; Parkinson, Helen; Liu, Yue; Takatsuki, Terue; Saijo, Kaoru; Masuya, Hiroshi; Nakamura, Yukio; Brush, Matthew H.; Haendel, Melissa A.; Zheng, Jie; Stoeckert, Christian J.; Peters, Bjoern; Mungall, Christopher J.; Carey, Thomas E.; States, David J.; Athey, Brian D.; He, Yongqun

    2014-01-01

    Background: Cell lines have been widely used in biomedical research. The community-based Cell Line Ontology (CLO) is a member of the OBO Foundry library that covers the domain of cell lines. Since its publication two years ago, significant updates have been made, including new groups joining the CLO

  13. Emotion Education without Ontological Commitment?

    Science.gov (United States)

    Kristjansson, Kristjan

    2010-01-01

    Emotion education is enjoying new-found popularity. This paper explores the "cosy consensus" that seems to have developed in education circles, according to which approaches to emotion education are immune from metaethical considerations such as contrasting rationalist and sentimentalist views about the moral ontology of emotions. I spell out five…

  14. Quantum physics and relational ontology

    Energy Technology Data Exchange (ETDEWEB)

    Cordovil, Joao [Center of Philosophy of Sciences of University of Lisbon (Portugal)

    2013-07-01

    The discovery of the quantum domain of reality put a serious ontological challenge, a challenge that is still well present in the recent developments of Quantum Physics. Physics was conceived from an atomistic conception of the world, reducing it, in all its diversity, to two types of entities: simple, individual and immutable entities (atoms, in metaphysical sense) and composite entities, resulting solely from combinations. Linear combinations, additive, indifferent to the structure or to the context. However, the discovery of wave-particle dualism and the developments in Quantum Field Theories and in Quantum Nonlinear Physical, showed that quantum entities are not, in metaphysical sense, neither simple, nor merely the result of linear (or additive) combinations. In other words, the ontological foundations of Physics revealed as inadequate to account for the nature of quantum entities. Then a fundamental challenge arises: How to think the ontic nature of these entities? In my view, this challenge appeals to a relational and dynamist ontology of physical entities. This is the central hypothesis of this communication. In this sense, this communication has two main intentions: 1) positively characterize this relational and dynamist ontology; 2) show some elements of its metaphysical suitability to contemporary Quantum Physics.

  15. Ontological problems of contemporary linguistics

    Directory of Open Access Journals (Sweden)

    А В Бондаренко

    2009-03-01

    Full Text Available The article studies linguistic ontology problems such as evolution of essential-existential views of language, interrelation within Being-Language-Man triad, linguistics gnosiological principles, language essence localization, and «expression» as language metalinguistic unit as well as architectonics of language personality et alia.

  16. An ontological approach to logistics

    NARCIS (Netherlands)

    Daniele, L.M.; Ferreira Pires, Luis; Zelm, M.; van Sinderen, Marten J.; Doumeingts, G.

    2013-01-01

    In today’s global market, the competitiveness of enterprises is strongly dictated by their ability to collaborate with other enterprises. Ontologies enable common understanding of concepts and have been acknowledged as a powerful means to foster collaboration, both within the boundaries of an

  17. Gradient Learning Algorithms for Ontology Computing

    Science.gov (United States)

    Gao, Wei; Zhu, Linli

    2014-01-01

    The gradient learning model has been raising great attention in view of its promising perspectives for applications in statistics, data dimensionality reducing, and other specific fields. In this paper, we raise a new gradient learning model for ontology similarity measuring and ontology mapping in multidividing setting. The sample error in this setting is given by virtue of the hypothesis space and the trick of ontology dividing operator. Finally, two experiments presented on plant and humanoid robotics field verify the efficiency of the new computation model for ontology similarity measure and ontology mapping applications in multidividing setting. PMID:25530752

  18. Gradient Learning Algorithms for Ontology Computing

    Directory of Open Access Journals (Sweden)

    Wei Gao

    2014-01-01

    Full Text Available The gradient learning model has been raising great attention in view of its promising perspectives for applications in statistics, data dimensionality reducing, and other specific fields. In this paper, we raise a new gradient learning model for ontology similarity measuring and ontology mapping in multidividing setting. The sample error in this setting is given by virtue of the hypothesis space and the trick of ontology dividing operator. Finally, two experiments presented on plant and humanoid robotics field verify the efficiency of the new computation model for ontology similarity measure and ontology mapping applications in multidividing setting.

  19. History Matters: Incremental Ontology Reasoning Using Modules

    Science.gov (United States)

    Cuenca Grau, Bernardo; Halaschek-Wiener, Christian; Kazakov, Yevgeny

    The development of ontologies involves continuous but relatively small modifications. Existing ontology reasoners, however, do not take advantage of the similarities between different versions of an ontology. In this paper, we propose a technique for incremental reasoning—that is, reasoning that reuses information obtained from previous versions of an ontology—based on the notion of a module. Our technique does not depend on a particular reasoning calculus and thus can be used in combination with any reasoner. We have applied our results to incremental classification of OWL DL ontologies and found significant improvement over regular classification time on a set of real-world ontologies.

  20. Massachusetts Institute of Technology Consortium Agreement

    National Research Council Canada - National Science Library

    Asada, Haruhiko

    1999-01-01

    ... of Phase 2 of the Home Automation and Healthcare Consortium. This report describes all major research accomplishments within the last six months since we launched the second phase of the consortium...

  1. Brain Tumor Epidemiology Consortium (BTEC)

    Science.gov (United States)

    The Brain Tumor Epidemiology Consortium is an open scientific forum organized to foster the development of multi-center, international and inter-disciplinary collaborations that will lead to a better understanding of the etiology, outcomes, and prevention of brain tumors.

  2. Establishing an International Soil Modelling Consortium

    Science.gov (United States)

    Vereecken, Harry; Schnepf, Andrea; Vanderborght, Jan

    2015-04-01

    -change-feedback processes, bridge basic soil science research and management, and facilitate the communication between science and society . To meet these challenges an international community effort is required, similar to initiatives in systems biology, hydrology, and climate and crop research. We therefore propose to establish an international soil modelling consortium with the aims of 1) bringing together leading experts in modelling soil processes within all major soil disciplines, 2) addressing major scientific gaps in describing key processes and their long term impacts with respect to the different functions and ecosystem services provided by soil, 3) intercomparing soil model performance based on standardized and harmonized data sets, 4) identifying interactions with other relevant platforms related to common data formats, protocols and ontologies, 5) developing new approaches to inverse modelling, calibration, and validation of soil models, 6) integrating soil modelling expertise and state of the art knowledge on soil processes in climate, land surface, ecological, crop and contaminant models, and 7) linking process models with new observation, measurement and data evaluation technologies for mapping and characterizing soil properties across scales. Our consortium will bring together modelers and experimental soil scientists at the forefront of new technologies and approaches to characterize soils. By addressing these aims, the consortium will contribute to improve the role of soil modeling as a knowledge dissemination instrument in addressing key global issues and stimulate the development of translational research activities. This presentation will provide a compelling case for this much-needed effort, with a focus on tangible benefits to the scientific and food security communities.

  3. Linkage analysis of candidate genes in autoimmune thyroid disease. II. Selected gender-related genes and the X-chromosome. International Consortium for the Genetics of Autoimmune Thyroid Disease.

    Science.gov (United States)

    Barbesino, G; Tomer, Y; Concepcion, E S; Davies, T F; Greenberg, D A

    1998-09-01

    Hashimoto's thyroiditis (HT) and Graves' disease (GD) are autoimmune thyroid diseases (AITD) in which multiple genetic factors are suspected to play an important role. Until now, only a few minor risk factors for these diseases have been identified. Susceptibility seems to be stronger in women, pointing toward a possible role for genes related to sex steroid action or mechanisms related to genes on the X-chromosome. We have studied a total of 45 multiplex families, each containing at least 2 members affected with either GD (55 patients) or HT (72 patients), and used linkage analysis to target as candidate susceptibility loci genes involved in estrogen activity, such as the estrogen receptor alpha and beta and the aromatase genes. We then screened the entire X-chromosome using a set of polymorphic microsatellite markers spanning the whole chromosome. We found a region of the X-chromosome (Xq21.33-22) giving positive logarithm of odds (LOD) scores and then reanalyzed this area with dense markers in a multipoint analysis. Our results excluded linkage to the estrogen receptor alpha and aromatase genes when either the patients with GD only, those with HT only, or those with any AITD were considered as affected. Linkage to the estrogen receptor beta could not be totally ruled out, partly due to incomplete mapping information for the gene itself at this time. The X-chromosome data revealed consistently positive LOD scores (maximum of 1.88 for marker DXS8020 and GD patients) when either definition of affectedness was considered. Analysis of the family data using a multipoint analysis with eight closely linked markers generated LOD scores suggestive of linkage to GD in a chromosomal area (Xq21.33-22) extending for about 6 cM and encompassing four markers. The maximum LOD score (2.5) occurred at DXS8020. In conclusion, we ruled out a major role for estrogen receptor alpha and the aromatase genes in the genetic predisposition to AITD. Estrogen receptor beta remains a

  4. Biomedical word sense disambiguation with ontologies and metadata: automation meets accuracy

    Directory of Open Access Journals (Sweden)

    Hakenberg Jörg

    2009-01-01

    Full Text Available Abstract Background Ontology term labels can be ambiguous and have multiple senses. While this is no problem for human annotators, it is a challenge to automated methods, which identify ontology terms in text. Classical approaches to word sense disambiguation use co-occurring words or terms. However, most treat ontologies as simple terminologies, without making use of the ontology structure or the semantic similarity between terms. Another useful source of information for disambiguation are metadata. Here, we systematically compare three approaches to word sense disambiguation, which use ontologies and metadata, respectively. Results The 'Closest Sense' method assumes that the ontology defines multiple senses of the term. It computes the shortest path of co-occurring terms in the document to one of these senses. The 'Term Cooc' method defines a log-odds ratio for co-occurring terms including co-occurrences inferred from the ontology structure. The 'MetaData' approach trains a classifier on metadata. It does not require any ontology, but requires training data, which the other methods do not. To evaluate these approaches we defined a manually curated training corpus of 2600 documents for seven ambiguous terms from the Gene Ontology and MeSH. All approaches over all conditions achieve 80% success rate on average. The 'MetaData' approach performed best with 96%, when trained on high-quality data. Its performance deteriorates as quality of the training data decreases. The 'Term Cooc' approach performs better on Gene Ontology (92% success than on MeSH (73% success as MeSH is not a strict is-a/part-of, but rather a loose is-related-to hierarchy. The 'Closest Sense' approach achieves on average 80% success rate. Conclusion Metadata is valuable for disambiguation, but requires high quality training data. Closest Sense requires no training, but a large, consistently modelled ontology, which are two opposing conditions. Term Cooc achieves greater 90

  5. Building a biomedical ontology recommender web service

    Directory of Open Access Journals (Sweden)

    Jonquet Clement

    2010-06-01

    Full Text Available Abstract Background Researchers in biomedical informatics use ontologies and terminologies to annotate their data in order to facilitate data integration and translational discoveries. As the use of ontologies for annotation of biomedical datasets has risen, a common challenge is to identify ontologies that are best suited to annotating specific datasets. The number and variety of biomedical ontologies is large, and it is cumbersome for a researcher to figure out which ontology to use. Methods We present the Biomedical Ontology Recommender web service. The system uses textual metadata or a set of keywords describing a domain of interest and suggests appropriate ontologies for annotating or representing the data. The service makes a decision based on three criteria. The first one is coverage, or the ontologies that provide most terms covering the input text. The second is connectivity, or the ontologies that are most often mapped to by other ontologies. The final criterion is size, or the number of concepts in the ontologies. The service scores the ontologies as a function of scores of the annotations created using the National Center for Biomedical Ontology (NCBO Annotator web service. We used all the ontologies from the UMLS Metathesaurus and the NCBO BioPortal. Results We compare and contrast our Recommender by an exhaustive functional comparison to previously published efforts. We evaluate and discuss the results of several recommendation heuristics in the context of three real world use cases. The best recommendations heuristics, rated ‘very relevant’ by expert evaluators, are the ones based on coverage and connectivity criteria. The Recommender service (alpha version is available to the community and is embedded into BioPortal.

  6. Alignment of ICNP® 2.0 ontology and a proposed INCP® Brazilian ontology.

    Science.gov (United States)

    Carvalho, Carina Maris Gaspar; Cubas, Marcia Regina; Malucelli, Andreia; Nóbrega, Maria Miriam Lima da

    2014-01-01

    to align the International Classification for Nursing Practice (ICNP®) Version 2.0 ontology and a proposed INCP® Brazilian Ontology. document-based, exploratory and descriptive study, the empirical basis of which was provided by the ICNP® 2.0 Ontology and the INCP® Brazilian Ontology. The ontology alignment was performed using a computer tool with algorithms to identify correspondences between concepts, which were organized and analyzed according to their presence or absence, their names, and their sibling, parent, and child classes. there were 2,682 concepts present in the ICNP® 2.0 Ontology that were missing in the Brazilian Ontology; 717 concepts present in the Brazilian Ontology were missing in the ICNP® 2.0 Ontology; and there were 215 pairs of matching concepts. it is believed that the correspondences identified in this study might contribute to the interoperability between the representations of nursing practice elements in ICNP®, thus allowing the standardization of nursing records based on this classification system.

  7. The MGED Ontology: A Framework for Describing Functional Genomics Experiments

    OpenAIRE

    Stoeckert, Christian J.; Parkinson, Helen

    2003-01-01

    The Microarray Gene Expression Data (MGED) society was formed with an initial focus on experiments involving microarray technology. Despite the diversity of applications, there are common concepts used and a common need to capture experimental information in a standardized manner. In building the MGED ontology, it was recognized that it would be impractical to cover all the different types of experiments on all the different types of organisms by listing and defining all the types of organism...

  8. Ontological realism: A methodology for coordinated evolution of scientific ontologies.

    Science.gov (United States)

    Smith, Barry; Ceusters, Werner

    2010-11-15

    Since 2002 we have been testing and refining a methodology for ontology development that is now being used by multiple groups of researchers in different life science domains. Gary Merrill, in a recent paper in this journal, describes some of the reasons why this methodology has been found attractive by researchers in the biological and biomedical sciences. At the same time he assails the methodology on philosophical grounds, focusing specifically on our recommendation that ontologies developed for scientific purposes should be constructed in such a way that their terms are seen as referring to what we call universals or types in reality. As we show, Merrill's critique is of little relevance to the success of our realist project, since it not only reveals no actual errors in our work but also criticizes views on universals that we do not in fact hold. However, it nonetheless provides us with a valuable opportunity to clarify the realist methodology, and to show how some of its principles are being applied, especially within the framework of the OBO (Open Biomedical Ontologies) Foundry initiative.

  9. Corn in consortium with forages

    Directory of Open Access Journals (Sweden)

    Cássia Maria de Paula Garcia

    2013-12-01

    Full Text Available The basic premises for sustainable agricultural development with focus on rural producers are reducing the costs of production and aggregation of values through the use crop-livestock system (CLS throughout the year. The CLS is based on the consortium of grain crops, especially corn with tropical forages, mainly of the genus Panicum and Urochloa. The study aimed to evaluate the grain yield of irrigated corn crop intercropped with forage of the genus Panicum and Urochloa. The experiment was conducted at the Fazenda de Ensino, Pesquisa e Extensão – FEPE  of the Faculdade de Engenharia - UNESP, Ilha Solteira in an Oxisol in savannah conditions and in the autumn winter of 2009. The experimental area was irrigated by a center pivot and had a history of no-tillage system for 8 years. The corn hybrid used was simple DKB 390 YG at distances of 0.90 m. The seeds of grasses were sown in 0.34 m spacing in the amount of 5 kg ha-1, they were mixed with fertilizer minutes before sowing  and placed in a compartment fertilizer seeder and fertilizers were mechanically deposited in the soil at a depth of 0.03 m. The experimental design used was a randomized block with four replications and five treatments: Panicum maximum cv. Tanzania sown during the nitrogen fertilization (CTD of the corn; Panicum maximum cv. Mombaça sown during the nitrogen fertilization (CMD of the corn; Urochloa brizantha cv. Xaraés sown during the occasion of nitrogen fertilization (CBD of the corn; Urochloa ruziziensis cv. Comumsown during the nitrogen fertilization (CRD of the corn and single corn (control. The production components of corn: plant population per hectare (PlPo, number of ears per hectare (NE ha-1, number of rows per ear (NRE, number of kernels per row on the cob (NKR, number of grain in the ear (NGE and mass of 100 grains (M100G were not influenced by consortium with forage. Comparing grain yield (GY single corn and maize intercropped with forage of the genus Panicum

  10. Formal Ontologies and Uncertainty. In Geographical Knowledge

    Directory of Open Access Journals (Sweden)

    Matteo Caglioni

    2014-05-01

    Full Text Available Formal ontologies have proved to be a very useful tool to manage interoperability among data, systems and knowledge. In this paper we will show how formal ontologies can evolve from a crisp, deterministic framework (ontologies of hard knowledge to new probabilistic, fuzzy or possibilistic frameworks (ontologies of soft knowledge. This can considerably enlarge the application potential of formal ontologies in geographic analysis and planning, where soft knowledge is intrinsically linked to the complexity of the phenomena under study.  The paper briefly presents these new uncertainty-based formal ontologies. It then highlights how ontologies are formal tools to define both concepts and relations among concepts. An example from the domain of urban geography finally shows how the cause-to-effect relation between household preferences and urban sprawl can be encoded within a crisp, a probabilistic and a possibilistic ontology, respectively. The ontology formalism will also determine the kind of reasoning that can be developed from available knowledge. Uncertain ontologies can be seen as the preliminary phase of more complex uncertainty-based models. The advantages of moving to uncertainty-based models is evident: whether it is in the analysis of geographic space or in decision support for planning, reasoning on geographic space is almost always reasoning with uncertain knowledge of geographic phenomena.

  11. Knowledge Portals: Ontologies at Work

    OpenAIRE

    Staab, Steffen; Maedche, Alexander

    2001-01-01

    Knowledge portals provide views onto domain-specific information on the World Wide Web, thus helping their users find relevant, domain-specific information. The construction of intelligent access and the contribution of information to knowledge portals, however, remained an ad hoc task, requiring extensive manual editing and maintenance by the knowledge portal providers. To diminish these efforts, we use ontologies as a conceptual backbone for providing, accessing, and structuring information...

  12. The Christological Ontology of Reason

    DEFF Research Database (Denmark)

    Nissen, Ulrik Becker

    2006-01-01

    Taking the startingpoint in an assertion of an ambiguity in the Lutheran tradition’s assessment of reason, the essay argues that the Kantian unreserved confidence in reason is criticised in Bonhoeffer. Based upon a Christological understanding of reason, Bonhoeffer endorses a view of reason which...... is treated in the essay. Here it is argued that Bonhoeffer may be appropriated in attempting to outline a Christological ontology of reason holding essential implications for the sources and conditions of public discourse....

  13. Emotion Ontology for Context Awareness

    OpenAIRE

    Berthelon , Franck; Sander , Peter

    2013-01-01

    International audience; We present an emotion ontology for describing and reasoning on emotion context in order to improve emotion detection based on bodily expression. We incorporate context into the two-factor theory of emotion (bodily reaction plus cognitive input) and demonstrate the importance of context in the emotion experience. In attempting to determine emotion felt by another person, the bodily expresson of their emotion is the only evidence directly available, eg, ''John looks angr...

  14. Towards an Ontology of Software

    OpenAIRE

    Wang, Xiaowei

    2016-01-01

    Software is permeating every aspect of our personal and social life. And yet, the cluster of concepts around the notion of software, such as the notions of a software product, software requirements, software specifications, are still poorly understood with no consensus on the horizon. For many, software is just code, something intangible best defined in contrast with hardware, but it is not particularly illuminating. This erroneous notion, software is just code, presents both in the ontology ...

  15. Ontology Maintenance using Textual Analysis

    Directory of Open Access Journals (Sweden)

    Yassine Gargouri

    2003-10-01

    Full Text Available Ontologies are continuously confronted to evolution problem. Due to the complexity of the changes to be made, a maintenance process, at least a semi-automatic one, is more and more necessary to facilitate this task and to ensure its reliability. In this paper, we propose a maintenance ontology model for a domain, whose originality is to be language independent and based on a sequence of text processing in order to extract highly related terms from corpus. Initially, we deploy the document classification technique using GRAMEXCO to generate classes of texts segments having a similar information type and identify their shared lexicon, agreed as highly related to a unique topic. This technique allows a first general and robust exploration of the corpus. Further, we apply the Latent Semantic Indexing method to extract from this shared lexicon, the most associated terms that has to be seriously considered by an expert to eventually confirm their relevance and thus updating the current ontology. Finally, we show how the complementarity between these two techniques, based on cognitive foundation, constitutes a powerful refinement process.

  16. Scientific Reproducibility in Biomedical Research: Provenance Metadata Ontology for Semantic Annotation of Study Description.

    Science.gov (United States)

    Sahoo, Satya S; Valdez, Joshua; Rueschman, Michael

    2016-01-01

    Scientific reproducibility is key to scientific progress as it allows the research community to build on validated results, protect patients from potentially harmful trial drugs derived from incorrect results, and reduce wastage of valuable resources. The National Institutes of Health (NIH) recently published a systematic guideline titled "Rigor and Reproducibility " for supporting reproducible research studies, which has also been accepted by several scientific journals. These journals will require published articles to conform to these new guidelines. Provenance metadata describes the history or origin of data and it has been long used in computer science to capture metadata information for ensuring data quality and supporting scientific reproducibility. In this paper, we describe the development of Provenance for Clinical and healthcare Research (ProvCaRe) framework together with a provenance ontology to support scientific reproducibility by formally modeling a core set of data elements representing details of research study. We extend the PROV Ontology (PROV-O), which has been recommended as the provenance representation model by World Wide Web Consortium (W3C), to represent both: (a) data provenance, and (b) process provenance. We use 124 study variables from 6 clinical research studies from the National Sleep Research Resource (NSRR) to evaluate the coverage of the provenance ontology. NSRR is the largest repository of NIH-funded sleep datasets with 50,000 studies from 36,000 participants. The provenance ontology reuses ontology concepts from existing biomedical ontologies, for example the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), to model the provenance information of research studies. The ProvCaRe framework is being developed as part of the Big Data to Knowledge (BD2K) data provenance project.

  17. Virginia ADS consortium - thorium utilization

    International Nuclear Information System (INIS)

    Myneni, Ganapati

    2015-01-01

    A Virginia ADS consortium, consisting of Virginia Universities (UVa, VCU, VT), Industry (Casting Analysis Corporation, GEM*STAR, MuPlus Inc.), Jefferson Lab and not-for-profit ISOHIM, has been organizing International Accelerator-Driven Sub-Critical Systems (ADS) and Thorium Utilization (ThU) workshops. The third workshop of this series was hosted by VCU in Richmond, Virginia, USA Oct 2014 with CBMM and IAEA sponsorship and was endorsed by International Thorium Energy Committee (IThEC), Geneva and Virginia Nuclear Energy Consortium Authority. In this presentation a brief summary of the successful 3 rd International ADS and ThU workshop proceedings and review the worldwide ADS plans and/or programs is given. Additionally, a report on new start-ups on Molten Salt Reactor (MSR) systems is presented. Further, a discussion on potential simplistic fertile 232 Th to fissile 233 U conversion is made

  18. John Glenn Biomedical Engineering Consortium

    Science.gov (United States)

    Nall, Marsha

    2004-01-01

    The John Glenn Biomedical Engineering Consortium is an inter-institutional research and technology development, beginning with ten projects in FY02 that are aimed at applying GRC expertise in fluid physics and sensor development with local biomedical expertise to mitigate the risks of space flight on the health, safety, and performance of astronauts. It is anticipated that several new technologies will be developed that are applicable to both medical needs in space and on earth.

  19. Appalachian clean coal technology consortium

    International Nuclear Information System (INIS)

    Kutz, K.; Yoon, Roe-Hoan

    1995-01-01

    The Appalachian Clean Coal Technology Consortium (ACCTC) has been established to help U.S. coal producers, particularly those in the Appalachian region, increase the production of lower-sulfur coal. The cooperative research conducted as part of the consortium activities will help utilities meet the emissions standards established by the 1990 Clean Air Act Amendments, enhance the competitiveness of U.S. coals in the world market, create jobs in economically-depressed coal producing regions, and reduce U.S. dependence on foreign energy supplies. The research activities will be conducted in cooperation with coal companies, equipment manufacturers, and A ampersand E firms working in the Appalachian coal fields. This approach is consistent with President Clinton's initiative in establishing Regional Technology Alliances to meet regional needs through technology development in cooperation with industry. The consortium activities are complementary to the High-Efficiency Preparation program of the Pittsburgh Energy Technology Center, but are broader in scope as they are inclusive of technology developments for both near-term and long-term applications, technology transfer, and training a highly-skilled work force

  20. Appalachian clean coal technology consortium

    Energy Technology Data Exchange (ETDEWEB)

    Kutz, K.; Yoon, Roe-Hoan [Virginia Polytechnic Institute and State Univ., Blacksburg, VA (United States)

    1995-11-01

    The Appalachian Clean Coal Technology Consortium (ACCTC) has been established to help U.S. coal producers, particularly those in the Appalachian region, increase the production of lower-sulfur coal. The cooperative research conducted as part of the consortium activities will help utilities meet the emissions standards established by the 1990 Clean Air Act Amendments, enhance the competitiveness of U.S. coals in the world market, create jobs in economically-depressed coal producing regions, and reduce U.S. dependence on foreign energy supplies. The research activities will be conducted in cooperation with coal companies, equipment manufacturers, and A&E firms working in the Appalachian coal fields. This approach is consistent with President Clinton`s initiative in establishing Regional Technology Alliances to meet regional needs through technology development in cooperation with industry. The consortium activities are complementary to the High-Efficiency Preparation program of the Pittsburgh Energy Technology Center, but are broader in scope as they are inclusive of technology developments for both near-term and long-term applications, technology transfer, and training a highly-skilled work force.

  1. Database Concepts in a Domain Ontology

    Directory of Open Access Journals (Sweden)

    Gorskis Henrihs

    2017-12-01

    Full Text Available There are multiple approaches for mapping from a domain ontology to a database in the task of ontology-based data access. For that purpose, external mapping documents are most commonly used. These documents describe how the data necessary for the description of ontology individuals and other values, are to be obtained from the database. The present paper investigates the use of special database concepts. These concepts are not separated from the domain ontology; they are mixed with domain concepts to form a combined application ontology. By creating natural relationships between database concepts and domain concepts, mapping can be implemented more easily and with a specific purpose. The paper also investigates how the use of such database concepts in addition to domain concepts impacts ontology building and data retrieval.

  2. Ontology-aided Data Fusion (Invited)

    Science.gov (United States)

    Raskin, R.

    2009-12-01

    An ontology provides semantic descriptions that are analogous to those in a dictionary, but are readable by both computers and humans. A data or service is semantically annotated when it is formally associated with elements of an ontology. The ESIP Federation Semantic Web Cluster has developed a set of ontologies to describe datatypes and data services that can be used to support automated data fusion. The service ontology includes descriptors of the service function, its inputs/outputs, and its invocation method. The datatype descriptors resemble typical metadata fields (data format, data model, data structure, originator, etc.) augmented with descriptions of the meaning of the data. These ontologies, in combination with the SWEET science ontology, enable a registered data fusion service to be chained together and implemented that is scientifically meaningful based on machine understanding of the associated data and services. This presentation describes initial results and experiences in automated data fusion.

  3. An Ontological Architecture for Orbital Debris Data

    OpenAIRE

    Rovetto, Robert J.

    2017-01-01

    The orbital debris problem presents an opportunity for inter-agency and international cooperation toward the mutually beneficial goals of debris prevention, mitigation, remediation, and improved space situational awareness (SSA). Achieving these goals requires sharing orbital debris and other SSA data. Toward this, I present an ontological architecture for the orbital debris domain, taking steps in the creation of an orbital debris ontology (ODO). The purpose of this ontological system is to ...

  4. Versioning System for Distributed Ontology Development

    Science.gov (United States)

    2016-03-15

    Framework for Grid Computing and Semantic Web Services,” Trust Management, Springer Berlin Heidelberg (2004), pp. 16−26. [TIME] W3C, “Time Ontology in...Distributed Ontology Development S.K. Damodaran 15 March 2016 This material is based on work supported by the Assistant Secretary of Defense for...Distributed Ontology Development S.K. Damodaran Formerly Group 59 15 March 2016 Massachusetts Institute of Technology Lincoln Laboratory

  5. Ontorat: automatic generation of new ontology terms, annotations, and axioms based on ontology design patterns.

    Science.gov (United States)

    Xiang, Zuoshuang; Zheng, Jie; Lin, Yu; He, Yongqun

    2015-01-01

    It is time-consuming to build an ontology with many terms and axioms. Thus it is desired to automate the process of ontology development. Ontology Design Patterns (ODPs) provide a reusable solution to solve a recurrent modeling problem in the context of ontology engineering. Because ontology terms often follow specific ODPs, the Ontology for Biomedical Investigations (OBI) developers proposed a Quick Term Templates (QTTs) process targeted at generating new ontology classes following the same pattern, using term templates in a spreadsheet format. Inspired by the ODPs and QTTs, the Ontorat web application is developed to automatically generate new ontology terms, annotations of terms, and logical axioms based on a specific ODP(s). The inputs of an Ontorat execution include axiom expression settings, an input data file, ID generation settings, and a target ontology (optional). The axiom expression settings can be saved as a predesigned Ontorat setting format text file for reuse. The input data file is generated based on a template file created by a specific ODP (text or Excel format). Ontorat is an efficient tool for ontology expansion. Different use cases are described. For example, Ontorat was applied to automatically generate over 1,000 Japan RIKEN cell line cell terms with both logical axioms and rich annotation axioms in the Cell Line Ontology (CLO). Approximately 800 licensed animal vaccines were represented and annotated in the Vaccine Ontology (VO) by Ontorat. The OBI team used Ontorat to add assay and device terms required by ENCODE project. Ontorat was also used to add missing annotations to all existing Biobank specific terms in the Biobank Ontology. A collection of ODPs and templates with examples are provided on the Ontorat website and can be reused to facilitate ontology development. With ever increasing ontology development and applications, Ontorat provides a timely platform for generating and annotating a large number of ontology terms by following

  6. Towards Process-Ontology: A Critical Study of Substance-Ontological Premises

    DEFF Research Database (Denmark)

    Seibt, Johanna

    The thesis proposes therapeutic revision of fundamental assumptions in contemporary ontological thought. I show that non of the prevalent theories of objects, by virtue of certain implicit substance-ontological assumptions provides a viable account of the numerical, qualitative, and trans-tempora......-ontological presuppositions, I finally explore the result of rejecting all of them and sketch a scheme basic on dynamic masses which promises to yield coherent explanation of the ontological features of those complex processes that we commonly call objects....

  7. OntologyWidget – a reusable, embeddable widget for easily locating ontology terms

    OpenAIRE

    Beauheim, Catherine C; Wymore, Farrell; Nitzberg, Michael; Zachariah, Zachariah K; Jin, Heng; Skene, JH Pate; Ball, Catherine A; Sherlock, Gavin

    2007-01-01

    Abstract Background Biomedical ontologies are being widely used to annotate biological data in a computer-accessible, consistent and well-defined manner. However, due to their size and complexity, annotating data with appropriate terms from an ontology is often challenging for experts and non-experts alike, because there exist few tools that allow one to quickly find relevant ontology terms to easily populate a web form. Results We have produced a tool, OntologyWidget, which allows users to r...

  8. Towards refactoring the Molecular Function Ontology with a UML profile for function modeling.

    Science.gov (United States)

    Burek, Patryk; Loebe, Frank; Herre, Heinrich

    2017-10-04

    Gene Ontology (GO) is the largest resource for cataloging gene products. This resource grows steadily and, naturally, this growth raises issues regarding the structure of the ontology. Moreover, modeling and refactoring large ontologies such as GO is generally far from being simple, as a whole as well as when focusing on certain aspects or fragments. It seems that human-friendly graphical modeling languages such as the Unified Modeling Language (UML) could be helpful in connection with these tasks. We investigate the use of UML for making the structural organization of the Molecular Function Ontology (MFO), a sub-ontology of GO, more explicit. More precisely, we present a UML dialect, called the Function Modeling Language (FueL), which is suited for capturing functions in an ontologically founded way. FueL is equipped, among other features, with language elements that arise from studying patterns of subsumption between functions. We show how to use this UML dialect for capturing the structure of molecular functions. Furthermore, we propose and discuss some refactoring options concerning fragments of MFO. FueL enables the systematic, graphical representation of functions and their interrelations, including making information explicit that is currently either implicit in MFO or is mainly captured in textual descriptions. Moreover, the considered subsumption patterns lend themselves to the methodical analysis of refactoring options with respect to MFO. On this basis we argue that the approach can increase the comprehensibility of the structure of MFO for humans and can support communication, for example, during revision and further development.

  9. The NASA Air Traffic Management Ontology (atmonto)

    Data.gov (United States)

    National Aeronautics and Space Administration — The NASA ATM (Air Traffic Management) Ontology describes classes, properties, and relationships relevant to the domain of air traffic management, and represents...

  10. Ontology Enabled Generation of Embedded Web Services

    DEFF Research Database (Denmark)

    Hansen, Klaus Marius; Zhang, Weishan; Soares, Goncalo Teofilo Afonso Pinheiro

    2008-01-01

    and software platforms, and of devices state and context changes. To address these challenges, we developed a Web service compiler, Limbo, in which Web Ontology Language (OWL) ontologies are used to make the Limbo compiler aware of its compilation context, such as targeted hardware and software. At the same...... time, knowledge on device details, platform dependencies, and resource/power consumption is built into the supporting ontologies, which are used to configure Limbo for generating resource efficient web service code. A state machine ontology is used to generate stub code to facilitate handling of state...

  11. Scientific Digital Libraries, Interoperability, and Ontologies

    Science.gov (United States)

    Hughes, J. Steven; Crichton, Daniel J.; Mattmann, Chris A.

    2009-01-01

    Scientific digital libraries serve complex and evolving research communities. Justifications for the development of scientific digital libraries include the desire to preserve science data and the promises of information interconnectedness, correlative science, and system interoperability. Shared ontologies are fundamental to fulfilling these promises. We present a tool framework, some informal principles, and several case studies where shared ontologies are used to guide the implementation of scientific digital libraries. The tool framework, based on an ontology modeling tool, was configured to develop, manage, and keep shared ontologies relevant within changing domains and to promote the interoperability, interconnectedness, and correlation desired by scientists.

  12. Finding the best visualization of an ontology

    DEFF Research Database (Denmark)

    Fabritius, Christina; Madsen, Nadia; Clausen, Jens

    2006-01-01

    An ontology is a classification model for a given domain.In information retrieval ontologies are used to perform broad searches.An ontology can be visualized as nodes and edges. Each node represents an element and each edge a relation between a parent and a child element. Working with an ontology....... One method uses a discrete location model to create an initial solution and we propose heuristic methods to further improve the visual result. We evaluate the visual results according to our success criteria and the feedback from users. Running times of the heuristic indicate that an improved version...

  13. Finding the best visualization of an ontology

    DEFF Research Database (Denmark)

    Fabritius, Christina Valentin; Madsen, Nadia Lyngaa; Clausen, Jens

    2004-01-01

    An ontology is a classification model for a given domain. In information retrieval ontologies are used to perform broad searches. An ontology can be visualized as nodes and edges. Each node represents an element and each edge a relation between a parent and a child element. Working with an ontology....... One method uses a discrete location model to create an initial solution and we propose heuristic methods to further improve the visual result. We evaluate the visual results according to our success criteria and the feedback from users. Running times of the heuristic indicate that an improved version...

  14. The current landscape of pitfalls in Ontologies

    CSIR Research Space (South Africa)

    Keet, CM

    2013-09-01

    Full Text Available 2Ontology Engineering Group, Departamento de Inteligencia Artificial, Universidad Polite´cnica de Madrid, Madrid, Spain keet@ukzn.ac.za, {mcsuarez,mpoveda}@fi.upm.es Keywords: Ontology Development : Ontology Quality : Pitfall Abstract: A growing... in Ontologies C. Maria Keet1, Mari Carmen Sua´rez-Figueroa2 and Marı´a Poveda-Villalo´n2 1School of Mathematics, Statistics, and Computer Science, University of KwaZulu-Natal, and UKZN/CSIR-Meraka Centre for Artificial Intelligence Research, Durban, South Africa...

  15. DEPONTO: A Reusable Dependability Domain Ontology

    Directory of Open Access Journals (Sweden)

    Teodora Sanislav

    2015-08-01

    Full Text Available This paper proposes a dependability reusable ontology for knowledge representation. The fundamental knowledge related to dependability follows its taxonomy. Thus, this paper gives an analysis of what is the dependability domain ontology andof its components.The dependability domain ontology plays an important role in ensuring the dependability of information systems by providing support for their diagnosis in case of faults, errors and failures.The proposed ontology is used as a dependability framework in two case study Cyber-Physical Systemswhich demonstrate its reusability within this category of systems.

  16. Learning Resources Organization Using Ontological Framework

    Science.gov (United States)

    Gavrilova, Tatiana; Gorovoy, Vladimir; Petrashen, Elena

    The paper describes the ontological approach to the knowledge structuring for the e-learning portal design as it turns out to be efficient and relevant to current domain conditions. It is primarily based on the visual ontology-based description of the content of the learning materials and this helps to provide productive and personalized access to these materials. The experience of ontology developing for Knowledge Engineering coursetersburg State University is discussed and “OntolingeWiki” tool for creating ontology-based e-learning portals is described.

  17. Ontological Engineering for the Cadastral Domain

    DEFF Research Database (Denmark)

    Stubkjær, Erik; Stuckenschmidt, Heiner

    2000-01-01

    conceptualization of the world is that much information remains implicit. Ontologies have set out to overcome the problem of implicit and hidden knowledge by making the conceptualization of a domain (e.g. mathematics) explicit. Ontological engineering is thus an approach to achieve a conceptual rigor...... that characterizes established academic disciplines, like geodesy. Many university courses address more application oriented fields, like cadastral law, and spatial planning, and they may benefit from the ontological engineering approach. The paper provides an introduction to the field of ontological engineering...

  18. Vaccine and Drug Ontology Studies (VDOS 2014).

    Science.gov (United States)

    Tao, Cui; He, Yongqun; Arabandi, Sivaram

    2016-01-01

    The "Vaccine and Drug Ontology Studies" (VDOS) international workshop series focuses on vaccine- and drug-related ontology modeling and applications. Drugs and vaccines have been critical to prevent and treat human and animal diseases. Work in both (drugs and vaccines) areas is closely related - from preclinical research and development to manufacturing, clinical trials, government approval and regulation, and post-licensure usage surveillance and monitoring. Over the last decade, tremendous efforts have been made in the biomedical ontology community to ontologically represent various areas associated with vaccines and drugs - extending existing clinical terminology systems such as SNOMED, RxNorm, NDF-RT, and MedDRA, developing new models such as the Vaccine Ontology (VO) and Ontology of Adverse Events (OAE), vernacular medical terminologies such as the Consumer Health Vocabulary (CHV). The VDOS workshop series provides a platform for discussing innovative solutions as well as the challenges in the development and applications of biomedical ontologies for representing and analyzing drugs and vaccines, their administration, host immune responses, adverse events, and other related topics. The five full-length papers included in this 2014 thematic issue focus on two main themes: (i) General vaccine/drug-related ontology development and exploration, and (ii) Interaction and network-related ontology studies.

  19. OntologyWidget – a reusable, embeddable widget for easily locating ontology terms

    Directory of Open Access Journals (Sweden)

    Skene JH Pate

    2007-09-01

    Full Text Available Abstract Background Biomedical ontologies are being widely used to annotate biological data in a computer-accessible, consistent and well-defined manner. However, due to their size and complexity, annotating data with appropriate terms from an ontology is often challenging for experts and non-experts alike, because there exist few tools that allow one to quickly find relevant ontology terms to easily populate a web form. Results We have produced a tool, OntologyWidget, which allows users to rapidly search for and browse ontology terms. OntologyWidget can easily be embedded in other web-based applications. OntologyWidget is written using AJAX (Asynchronous JavaScript and XML and has two related elements. The first is a dynamic auto-complete ontology search feature. As a user enters characters into the search box, the appropriate ontology is queried remotely for terms that match the typed-in text, and the query results populate a drop-down list with all potential matches. Upon selection of a term from the list, the user can locate this term within a generic and dynamic ontology browser, which comprises the second element of the tool. The ontology browser shows the paths from a selected term to the root as well as parent/child tree hierarchies. We have implemented web services at the Stanford Microarray Database (SMD, which provide the OntologyWidget with access to over 40 ontologies from the Open Biological Ontology (OBO website 1. Each ontology is updated weekly. Adopters of the OntologyWidget can either use SMD's web services, or elect to rely on their own. Deploying the OntologyWidget can be accomplished in three simple steps: (1 install Apache Tomcat 2 on one's web server, (2 download and install the OntologyWidget servlet stub that provides access to the SMD ontology web services, and (3 create an html (HyperText Markup Language file that refers to the OntologyWidget using a simple, well-defined format. Conclusion We have developed Ontology

  20. Ontobee: A linked ontology data server to support ontology term dereferencing, linkage, query and integration

    Science.gov (United States)

    Ong, Edison; Xiang, Zuoshuang; Zhao, Bin; Liu, Yue; Lin, Yu; Zheng, Jie; Mungall, Chris; Courtot, Mélanie; Ruttenberg, Alan; He, Yongqun

    2017-01-01

    Linked Data (LD) aims to achieve interconnected data by representing entities using Unified Resource Identifiers (URIs), and sharing information using Resource Description Frameworks (RDFs) and HTTP. Ontologies, which logically represent entities and relations in specific domains, are the basis of LD. Ontobee (http://www.ontobee.org/) is a linked ontology data server that stores ontology information using RDF triple store technology and supports query, visualization and linkage of ontology terms. Ontobee is also the default linked data server for publishing and browsing biomedical ontologies in the Open Biological Ontology (OBO) Foundry (http://obofoundry.org) library. Ontobee currently hosts more than 180 ontologies (including 131 OBO Foundry Library ontologies) with over four million terms. Ontobee provides a user-friendly web interface for querying and visualizing the details and hierarchy of a specific ontology term. Using the eXtensible Stylesheet Language Transformation (XSLT) technology, Ontobee is able to dereference a single ontology term URI, and then output RDF/eXtensible Markup Language (XML) for computer processing or display the HTML information on a web browser for human users. Statistics and detailed information are generated and displayed for each ontology listed in Ontobee. In addition, a SPARQL web interface is provided for custom advanced SPARQL queries of one or multiple ontologies. PMID:27733503

  1. Ontobee: A linked ontology data server to support ontology term dereferencing, linkage, query and integration.

    Science.gov (United States)

    Ong, Edison; Xiang, Zuoshuang; Zhao, Bin; Liu, Yue; Lin, Yu; Zheng, Jie; Mungall, Chris; Courtot, Mélanie; Ruttenberg, Alan; He, Yongqun

    2017-01-04

    Linked Data (LD) aims to achieve interconnected data by representing entities using Unified Resource Identifiers (URIs), and sharing information using Resource Description Frameworks (RDFs) and HTTP. Ontologies, which logically represent entities and relations in specific domains, are the basis of LD. Ontobee (http://www.ontobee.org/) is a linked ontology data server that stores ontology information using RDF triple store technology and supports query, visualization and linkage of ontology terms. Ontobee is also the default linked data server for publishing and browsing biomedical ontologies in the Open Biological Ontology (OBO) Foundry (http://obofoundry.org) library. Ontobee currently hosts more than 180 ontologies (including 131 OBO Foundry Library ontologies) with over four million terms. Ontobee provides a user-friendly web interface for querying and visualizing the details and hierarchy of a specific ontology term. Using the eXtensible Stylesheet Language Transformation (XSLT) technology, Ontobee is able to dereference a single ontology term URI, and then output RDF/eXtensible Markup Language (XML) for computer processing or display the HTML information on a web browser for human users. Statistics and detailed information are generated and displayed for each ontology listed in Ontobee. In addition, a SPARQL web interface is provided for custom advanced SPARQL queries of one or multiple ontologies. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  2. How Ontologies are Made: Studying the Hidden Social Dynamics Behind Collaborative Ontology Engineering Projects.

    Science.gov (United States)

    Strohmaier, Markus; Walk, Simon; Pöschko, Jan; Lamprecht, Daniel; Tudorache, Tania; Nyulas, Csongor; Musen, Mark A; Noy, Natalya F

    2013-05-01

    Traditionally, evaluation methods in the field of semantic technologies have focused on the end result of ontology engineering efforts, mainly, on evaluating ontologies and their corresponding qualities and characteristics. This focus has led to the development of a whole arsenal of ontology-evaluation techniques that investigate the quality of ontologies as a product . In this paper, we aim to shed light on the process of ontology engineering construction by introducing and applying a set of measures to analyze hidden social dynamics. We argue that especially for ontologies which are constructed collaboratively, understanding the social processes that have led to its construction is critical not only in understanding but consequently also in evaluating the ontology. With the work presented in this paper, we aim to expose the texture of collaborative ontology engineering processes that is otherwise left invisible. Using historical change-log data, we unveil qualitative differences and commonalities between different collaborative ontology engineering projects. Explaining and understanding these differences will help us to better comprehend the role and importance of social factors in collaborative ontology engineering projects. We hope that our analysis will spur a new line of evaluation techniques that view ontologies not as the static result of deliberations among domain experts, but as a dynamic, collaborative and iterative process that needs to be understood, evaluated and managed in itself. We believe that advances in this direction would help our community to expand the existing arsenal of ontology evaluation techniques towards more holistic approaches.

  3. Sample ontology, GOstat and ontology term enrichment - FANTOM5 | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data List Contact us FANTOM....biosciencedbc.jp/archive/fantom5/datafiles/LATEST/extra/Ontology/ File size: 1.8 MB Simple search URL - Dat...t Us Sample ontology, GOstat and ontology term enrichment - FANTOM5 | LSDB Archive ...

  4. How Ontologies are Made: Studying the Hidden Social Dynamics Behind Collaborative Ontology Engineering Projects

    Science.gov (United States)

    Strohmaier, Markus; Walk, Simon; Pöschko, Jan; Lamprecht, Daniel; Tudorache, Tania; Nyulas, Csongor; Musen, Mark A.; Noy, Natalya F.

    2013-01-01

    Traditionally, evaluation methods in the field of semantic technologies have focused on the end result of ontology engineering efforts, mainly, on evaluating ontologies and their corresponding qualities and characteristics. This focus has led to the development of a whole arsenal of ontology-evaluation techniques that investigate the quality of ontologies as a product. In this paper, we aim to shed light on the process of ontology engineering construction by introducing and applying a set of measures to analyze hidden social dynamics. We argue that especially for ontologies which are constructed collaboratively, understanding the social processes that have led to its construction is critical not only in understanding but consequently also in evaluating the ontology. With the work presented in this paper, we aim to expose the texture of collaborative ontology engineering processes that is otherwise left invisible. Using historical change-log data, we unveil qualitative differences and commonalities between different collaborative ontology engineering projects. Explaining and understanding these differences will help us to better comprehend the role and importance of social factors in collaborative ontology engineering projects. We hope that our analysis will spur a new line of evaluation techniques that view ontologies not as the static result of deliberations among domain experts, but as a dynamic, collaborative and iterative process that needs to be understood, evaluated and managed in itself. We believe that advances in this direction would help our community to expand the existing arsenal of ontology evaluation techniques towards more holistic approaches. PMID:24311994

  5. Where to Publish and Find Ontologies? A Survey of Ontology Libraries

    Science.gov (United States)

    d'Aquin, Mathieu; Noy, Natalya F.

    2011-01-01

    One of the key promises of the Semantic Web is its potential to enable and facilitate data interoperability. The ability of data providers and application developers to share and reuse ontologies is a critical component of this data interoperability: if different applications and data sources use the same set of well defined terms for describing their domain and data, it will be much easier for them to “talk” to one another. Ontology libraries are the systems that collect ontologies from different sources and facilitate the tasks of finding, exploring, and using these ontologies. Thus ontology libraries can serve as a link in enabling diverse users and applications to discover, evaluate, use, and publish ontologies. In this paper, we provide a survey of the growing—and surprisingly diverse—landscape of ontology libraries. We highlight how the varying scope and intended use of the libraries a ects their features, content, and potential exploitation in applications. From reviewing eleven ontology libraries, we identify a core set of questions that ontology practitioners and users should consider in choosing an ontology library for finding ontologies or publishing their own. We also discuss the research challenges that emerge from this survey, for the developers of ontology libraries to address. PMID:22408576

  6. Surreptitious, Evolving and Participative Ontology Development: An End-User Oriented Ontology Development Methodology

    Science.gov (United States)

    Bachore, Zelalem

    2012-01-01

    Ontology not only is considered to be the backbone of the semantic web but also plays a significant role in distributed and heterogeneous information systems. However, ontology still faces limited application and adoption to date. One of the major problems is that prevailing engineering-oriented methodologies for building ontologies do not…

  7. Towards Ontology-Driven Information Systems: Guidelines to the Creation of New Methodologies to Build Ontologies

    Science.gov (United States)

    Soares, Andrey

    2009-01-01

    This research targeted the area of Ontology-Driven Information Systems, where ontology plays a central role both at development time and at run time of Information Systems (IS). In particular, the research focused on the process of building domain ontologies for IS modeling. The motivation behind the research was the fact that researchers have…

  8. NCBO Ontology Recommender 2.0: an enhanced approach for biomedical ontology recommendation.

    Science.gov (United States)

    Martínez-Romero, Marcos; Jonquet, Clement; O'Connor, Martin J; Graybeal, John; Pazos, Alejandro; Musen, Mark A

    2017-06-07

    Ontologies and controlled terminologies have become increasingly important in biomedical research. Researchers use ontologies to annotate their data with ontology terms, enabling better data integration and interoperability across disparate datasets. However, the number, variety and complexity of current biomedical ontologies make it cumbersome for researchers to determine which ones to reuse for their specific needs. To overcome this problem, in 2010 the National Center for Biomedical Ontology (NCBO) released the Ontology Recommender, which is a service that receives a biomedical text corpus or a list of keywords and suggests ontologies appropriate for referencing the indicated terms. We developed a new version of the NCBO Ontology Recommender. Called Ontology Recommender 2.0, it uses a novel recommendation approach that evaluates the relevance of an ontology to biomedical text data according to four different criteria: (1) the extent to which the ontology covers the input data; (2) the acceptance of the ontology in the biomedical community; (3) the level of detail of the ontology classes that cover the input data; and (4) the specialization of the ontology to the domain of the input data. Our evaluation shows that the enhanced recommender provides higher quality suggestions than the original approach, providing better coverage of the input data, more detailed information about their concepts, increased specialization for the domain of the input data, and greater acceptance and use in the community. In addition, it provides users with more explanatory information, along with suggestions of not only individual ontologies but also groups of ontologies to use together. It also can be customized to fit the needs of different ontology recommendation scenarios. Ontology Recommender 2.0 suggests relevant ontologies for annotating biomedical text data. It combines the strengths of its predecessor with a range of adjustments and new features that improve its reliability

  9. A high-resolution anatomical ontology of the developing murine genitourinary tract

    Science.gov (United States)

    Little, Melissa H.; Brennan, Jane; Georgas, Kylie; Davies, Jamie A.; Davidson, Duncan R.; Baldock, Richard A.; Beverdam, Annemiek; Bertram, John F.; Capel, Blanche; Chiu, Han Sheng; Clements, Dave; Cullen-McEwen, Luise; Fleming, Jean; Gilbert, Thierry; Houghton, Derek; Kaufman, Matt H.; Kleymenova, Elena; Koopman, Peter A.; Lewis, Alfor G.; McMahon, Andrew P.; Mendelsohn, Cathy L.; Mitchell, Eleanor K.; Rumballe, Bree A.; Sweeney, Derina E.; Valerius, M. Todd; Yamada, Gen; Yang, Yiya; Yu., Jing

    2007-01-01

    Cataloguing gene expression during development of the genitourinary tract will increase our understanding not only of this process but also of congenital defects and disease affecting this organ system. We have developed a high-resolution ontology with which to describe the subcompartments of the developing murine genitourinary tract. This ontology incorporates what can be defined histologically and begins to encompass other structures and cell types already identified at the molecular level. The ontology is being used to annotate in situ hybridisation data generated as part of the Genitourinary Development Molecular Anatomy Project (GUDMAP), a publicly available data resource on gene and protein expression during genitourinary development. The GUDMAP ontology encompasses Theiler stage (TS) 17 to 27 of development as well as the sexually mature adult. It has been written as a partonomic, text-based, hierarchical ontology that, for the embryological stages, has been developed as a high-resolution expansion of the existing Edinburgh Mouse Atlas Project (EMAP) ontology. It also includes group terms for well-characterised structural and/or functional units comprising several sub-structures, such as the nephron and juxtaglomerular complex. Each term has been assigned a unique identification number. Synonyms have been used to improve the success of query searching and maintain wherever possible existing EMAP terms relating to this organ system. We describe here the principles and structure of the ontology and provide representative diagrammatic, histological, and whole mount and section RNA in situ hybridisation images to clarify the terms used within the ontology. Visual examples of how terms appear in different specimen types are also provided. PMID:17452023

  10. Deep learning meets ontologies: experiments to anchor the cardiovascular disease ontology in the biomedical literature.

    Science.gov (United States)

    Arguello Casteleiro, Mercedes; Demetriou, George; Read, Warren; Fernandez Prieto, Maria Jesus; Maroto, Nava; Maseda Fernandez, Diego; Nenadic, Goran; Klein, Julie; Keane, John; Stevens, Robert

    2018-04-12

    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. We have manually annotated 105 gene/protein names from 25 PubMed titles/abstracts and mapped them to 79 unique UniProtKB entries corresponding to gene and protein classes from the CVDO. Using more than 14 M PubMed articles (titles and available abstracts), word embeddings were generated with CBOW and Skip-gram. We setup two experiments for a synonym detection task, each with four raters, and 3672 pairs of terms (target term and candidate term) from the word embeddings created. For Experiment I, the target terms for 64 UniProtKB entries were those that appear in the titles/abstracts; Experiment II involves 63 UniProtKB entries and the target terms are a combination of terms from PubMed titles/abstracts with terms (i.e. increased context) from the CVDO protein class expressions and labels. In Experiment I, Skip-gram finds term variants (full and/or partial) for 89% of the 64 UniProtKB entries, while CBOW finds term variants for 67%. In Experiment II (with the aid of the CVDO), Skip-gram finds term variants for 95% of the 63 UniProtKB entries, while CBOW finds term variants for 78%. Combining the results of both experiments, Skip-gram finds term variants for 97% of the 79 UniProtKB entries, while CBOW finds term variants for 81%. This study shows performance improvements for both CBOW and Skip-gram on a gene/protein synonym detection task by

  11. Concepts, ontologies, and knowledge representation

    CERN Document Server

    Jakus, Grega; Omerovic, Sanida; Tomažic, Sašo

    2013-01-01

    Recording knowledge in a common framework that would make it possible to seamlessly share global knowledge remains an important challenge for researchers. This brief examines several ideas about the representation of knowledge addressing this challenge. A widespread general agreement is followed that states uniform knowledge representation should be achievable by using ontologies populated with concepts. A separate chapter is dedicated to each of the three introduced topics, following a uniform outline: definition, organization, and use. This brief is intended for those who want to get to know

  12. Nosology, ontology and promiscuous realism.

    Science.gov (United States)

    Binney, Nicholas

    2015-06-01

    Medics may consider worrying about their metaphysics and ontology to be a waste of time. I will argue here that this is not the case. Promiscuous realism is a metaphysical position which holds that multiple, equally valid, classification schemes should be applied to objects (such as patients) to capture different aspects of their complex and heterogeneous nature. As medics at the bedside may need to capture different aspects of their patients' problems, they may need to use multiple classification schemes (multiple nosologies), and thus consider adopting a different metaphysics to the one commonly in use. © 2014 John Wiley & Sons, Ltd.

  13. Semantics and metaphysics in informatics: toward an ontology of tasks.

    Science.gov (United States)

    Figdor, Carrie

    2011-04-01

    This article clarifies three principles that should guide the development of any cognitive ontology. First, that an adequate cognitive ontology depends essentially on an adequate task ontology; second, that the goal of developing a cognitive ontology is independent of the goal of finding neural implementations of the processes referred to in the ontology; and third, that cognitive ontologies are neutral regarding the metaphysical relationship between cognitive and neural processes. Copyright © 2011 Cognitive Science Society, Inc.

  14. Merged ontology for engineering design: Contrasting empirical and theoretical approaches to develop engineering ontologies

    DEFF Research Database (Denmark)

    Ahmed, Saeema; Storga, M

    2009-01-01

    to developing the ontology engineering design integrated taxonomies (EDIT) with a theoretical approach in which concepts and relations are elicited from engineering design theories ontology (DO) The limitations and advantages of each approach are discussed. The research methodology adopted is to map......This paper presents a comparison of two previous and separate efforts to develop an ontology in the engineering design domain, together with an ontology proposal from which ontologies for a specific application may be derived. The research contrasts an empirical, user-centered approach...

  15. Consortium for Health and Military Performance (CHAMP)

    Data.gov (United States)

    Federal Laboratory Consortium — The Center's work addresses a wide scope of trauma exposure from the consequences of combat, operations other than war, terrorism, natural and humanmade disasters,...

  16. An ontological case base engineering methodology for diabetes management.

    Science.gov (United States)

    El-Sappagh, Shaker H; El-Masri, Samir; Elmogy, Mohammed; Riad, A M; Saddik, Basema

    2014-08-01

    Ontology engineering covers issues related to ontology development and use. In Case Based Reasoning (CBR) system, ontology plays two main roles; the first as case base and the second as domain ontology. However, the ontology engineering literature does not provide adequate guidance on how to build, evaluate, and maintain ontologies. This paper proposes an ontology engineering methodology to generate case bases in the medical domain. It mainly focuses on the research of case representation in the form of ontology to support the case semantic retrieval and enhance all knowledge intensive CBR processes. A case study on diabetes diagnosis case base will be provided to evaluate the proposed methodology.

  17. University of Texas Southwestern Medical Center (UTSW): Functional Signature Ontology Tool: Triplicate Measurements of Reporter Gene Expression in Response to Individual Genetic and Chemical Perturbations in HCT116 Cells | Office of Cancer Genomics

    Science.gov (United States)

    The goal of this project is to use an eight-gene expression profile to define functional signatures for small molecules and natural products with heretofore undefined mechanism of action. Two genes in the eight gene set are used as internal controls and do not vary across gene expression array data collected from the public domain. The remaining six genes are found to vary independently across a large collection of publically available gene expression array datasets.  Read the abstract

  18. University of Texas Southwestern Medical Center: Functional Signature Ontology Tool: Triplicate Measurements of Reporter Gene Expression in Response to Individual Genetic and Chemical Perturbations in HCT116 Cells | Office of Cancer Genomics

    Science.gov (United States)

    The goal of this project is to use an eight-gene expression profile to define functional signatures for small molecules and natural products with heretofore undefined mechanism of action. Two genes in the eight gene set are used as internal controls and do not vary across gene expression array data collected from the public domain. The remaining six genes are found to vary independently across a large collection of publically available gene expression array datasets.  Read the abstract

  19. The eXtensible ontology development (XOD) principles and tool implementation to support ontology interoperability.

    Science.gov (United States)

    He, Yongqun; Xiang, Zuoshuang; Zheng, Jie; Lin, Yu; Overton, James A; Ong, Edison

    2018-01-12

    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. These XOD principles reuse existing terms and semantic relations from reliable ontologies, develop and apply well-established ontology design patterns (ODPs), and involve community efforts to support new ontology development, promoting standardized and interoperable data and knowledge representation and integration. The adoption of the XOD strategy, together with robust XOD tool development, will greatly support ontology interoperability and robust ontology applications to support data to be Findable, Accessible, Interoperable and Reusable (i.e., FAIR).

  20. Introduction to Semantic Web Ontology Languages

    NARCIS (Netherlands)

    Antoniou, Grigoris; Franconi, Enrico; Van Harmelen, Frank

    2005-01-01

    The aim of this chapter is to give a general introduction to some of the ontology languages that play a prominent role on the Semantic Web, and to discuss the formal foundations of these languages. Web ontology languages will be the main carriers of the information that we will want to share and

  1. Ontological Annotation with WordNet

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.; Chappell, Alan R.; Whitney, Paul D.; Posse, Christian; Paulson, Patrick R.; Baddeley, Bob; Hohimer, Ryan E.; White, Amanda M.

    2006-06-06

    Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

  2. Automating Ontological Annotation with WordNet

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.; Chappell, Alan R.; Whitney, Paul D.; Posse, Christian; Paulson, Patrick R.; Baddeley, Bob L.; Hohimer, Ryan E.; White, Amanda M.

    2006-01-22

    Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

  3. Fuzzy knowledge bases integration based on ontology

    OpenAIRE

    Ternovoy, Maksym; Shtogrina, Olena

    2012-01-01

    the paper describes the approach for fuzzy knowledge bases integration with the usage of ontology. This approach is based on metadata-base usage for integration of different knowledge bases with common ontology. The design process of metadata-base is described.

  4. C2 Domain Ontology within Our Lifetime

    Science.gov (United States)

    2009-06-01

    25] Masolo, C., et al: The WonderWeb Library of Foundational Ontologies Prelimary Report, WonderWeb Deliverable D17, ISTC -CNR, May 2003. [26...www.ifomis.org/bfo/BFO  [25] Masolo, C., et al: The WonderWeb Library of Foundational Ontologies Prelimary Report, WonderWeb Deliverable D17, ISTC -CNR

  5. Recent changes in the Building Topology Ontology

    DEFF Research Database (Denmark)

    Rasmussen, Mads Holten; Pauwels, Pieter; Lefrancois, Maxime

    The Building Topology Ontology (BOT) was in early 2017 suggested to the W3C community group for Linked Building Data as a simple ontology covering the core concepts of a building. Since it was first announced it has been extended to cover a building site, elements hosted by other elements, zones...

  6. Critical Ontology for an Enactive Music Pedagogy

    Science.gov (United States)

    van der Schyff, Dylan; Schiavio, Andrea; Elliott, David J.

    2016-01-01

    An enactive approach to music education is explored through the lens of critical ontology. Assumptions central to Western academic music culture are critically discussed; and the concept of "ontological education" is introduced as an alternative framework. We argue that this orientation embraces more primordial ways of knowing and being,…

  7. Integrity and change in modular ontologies

    NARCIS (Netherlands)

    Stuckenschmidt, Heiner; Klein, Michel

    2003-01-01

    The benefits of modular representations arc well known from many areas of computer science. In this paper, we concentrate on the benefits of modular ontologies with respect to local containment of terminological reasoning. We define an architecture for modular ontologies that supports local

  8. Ontologies and Information Systems: A Literature Survey

    Science.gov (United States)

    2011-06-01

    Falcon-AO (LMO + GMO ) [146], and RiMOM [317]. Meta-matching systems include APFEL [76] and eTuner [286]. There also exist frameworks that provide a set...Jian, N., Qu, Y. and Wang, Q. 2005. GMO : A graph matching for ontologies. In Proceedings of the K-CAPWorkshop on Integrating Ontologies, Banff

  9. Collaborative ontology development for the geosciences

    NARCIS (Netherlands)

    Kalbasi Khoramdashti, R.; Janowicz, K.; Reitsma, F.; Boerboom, L.G.J.; Alasheikh, A.

    2014-01-01

    Ontology-based information publishing, retrieval, reuse, and integration have become popular research topics to address the challenges involved in exchanging data between heterogeneous sources. However, in most cases ontologies are still developed in a centralized top-down manner by a few knowledge

  10. An ontology roadmap for crowdsourcing innovation intermediaries

    OpenAIRE

    Silva, Cândida; Ramos, Isabel

    2014-01-01

    Ontologies have proliferated in the last years, essentially justified by the need of achieving a consensus in the multiple representations of reality inside computers, and therefore the accomplishment of interoperability between machines and systems. Ontologies provide an explicit conceptualization that describes the semantics of the data. Crowdsourcing innovation intermediaries are organizations that mediate the communication and relationship between companies that aspire to solv...

  11. Ontology Assisted Formal Specification Extraction from Text

    Directory of Open Access Journals (Sweden)

    Andreea Mihis

    2010-12-01

    Full Text Available In the field of knowledge processing, the ontologies are the most important mean. They make possible for the computer to understand better the natural language and to make judgments. In this paper, a method which use ontologies in the semi-automatic extraction of formal specifications from a natural language text is proposed.

  12. [Towards a structuring fibrillar ontology].

    Science.gov (United States)

    Guimberteau, J-C

    2012-10-01

    Over previous decades and centuries, the difficulty encountered in the manner in which the tissue of our bodies is organised, and structured, is clearly explained by the impossibility of exploring it in detail. Since the creation of the microscope, the perception of the basic unity, which is the cell, has been essential in understanding the functioning of reproduction and of transmission, but has not been able to explain the notion of form; since the cells are not everywhere and are not distributed in an apparently balanced manner. The problems that remain are those of form and volume and also of connection. The concept of multifibrillar architecture, shaping the interfibrillar microvolumes in space, represents a solution to all these questions. The architectural structures revealed, made up of fibres, fibrils and microfibrils, from the mesoscopic to the microscopic level, provide the concept of a living form with structural rationalism that permits the association of psychochemical molecular biodynamics and quantum physics: the form can thus be described and interpreted, and a true structural ontology is elaborated from a basic functional unity, which is the microvacuole, the intra and interfibrillar volume of the fractal organisation, and the chaotic distribution. Naturally, new, less linear, less conclusive, and less specific concepts will be implied by this ontology, leading one to believe that the emergence of life takes place under submission to forces that the original form will have imposed and oriented the adaptive finality. Copyright © 2012. Published by Elsevier SAS.

  13. Knowledge Management Framework for Emerging Infectious Diseases Preparedness and Response: Design and Development of Public Health Document Ontology.

    Science.gov (United States)

    Zhang, Zhizun; Gonzalez, Mila C; Morse, Stephen S; Venkatasubramanian, Venkat

    2017-10-11

    There are increasing concerns about our preparedness and timely coordinated response across the globe to cope with emerging infectious diseases (EIDs). This poses practical challenges that require exploiting novel knowledge management approaches effectively. This work aims to develop an ontology-driven knowledge management framework that addresses the existing challenges in sharing and reusing public health knowledge. We propose a systems engineering-inspired ontology-driven knowledge management approach. It decomposes public health knowledge into concepts and relations and organizes the elements of knowledge based on the teleological functions. Both knowledge and semantic rules are stored in an ontology and retrieved to answer queries regarding EID preparedness and response. A hybrid concept extraction was implemented in this work. The quality of the ontology was evaluated using the formal evaluation method Ontology Quality Evaluation Framework. Our approach is a potentially effective methodology for managing public health knowledge. Accuracy and comprehensiveness of the ontology can be improved as more knowledge is stored. In the future, a survey will be conducted to collect queries from public health practitioners. The reasoning capacity of the ontology will be evaluated using the queries and hypothetical outbreaks. We suggest the importance of developing a knowledge sharing standard like the Gene Ontology for the public health domain. ©Zhizun Zhang, Mila C Gonzalez, Stephen S Morse, Venkat Venkatasubramanian. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 11.10.2017.

  14. Pathways to smoking behaviours : biological insights from the Tobacco and Genetics Consortium meta-analysis

    NARCIS (Netherlands)

    Minicã, C C; Mbarek, H; Pool, R; Dolan, C V; Boomsma, D I; Vink, J M

    By running gene and pathway analyses for several smoking behaviours in the Tobacco and Genetics Consortium (TAG) sample of 74 053 individuals, 21 genes and several chains of biological pathways were implicated. Analyses were carried out using the HYbrid Set-based Test (HYST) as implemented in the

  15. GFVO: the Genomic Feature and Variation Ontology

    KAUST Repository

    Baran, Joachim; Durgahee, Bibi Sehnaaz Begum; Eilbeck, Karen; Antezana, Erick; Hoehndorf, Robert; Dumontier, Michel

    2015-01-01

    Availability and implementation. The latest stable release of the ontology is available via its base URI; previous and development versions are available at the ontology’s GitHub repository: https://github.com/BioInterchange/Ontologies; versions of the ontology are indexed through BioPortal (without external class-/property-equivalences due to BioPortal release 4.10 limitations); examples and reference documentation is provided on a separate web-page: http://www.biointerchange.org/ontologies.html. GFVO version 1.0.2 is licensed under the CC0 1.0 Universal license (https://creativecommons.org/publicdomain/zero/1.0) and therefore de facto within the public domain; the ontology can be appropriated without attribution for commercial and non-commercial use.

  16. Ontology modeling in physical asset integrity management

    CERN Document Server

    Yacout, Soumaya

    2015-01-01

    This book presents cutting-edge applications of, and up-to-date research on, ontology engineering techniques in the physical asset integrity domain. Though a survey of state-of-the-art theory and methods on ontology engineering, the authors emphasize essential topics including data integration modeling, knowledge representation, and semantic interpretation. The book also reflects novel topics dealing with the advanced problems of physical asset integrity applications such as heterogeneity, data inconsistency, and interoperability existing in design and utilization. With a distinctive focus on applications relevant in heavy industry, Ontology Modeling in Physical Asset Integrity Management is ideal for practicing industrial and mechanical engineers working in the field, as well as researchers and graduate concerned with ontology engineering in physical systems life cycles. This book also: Introduces practicing engineers, research scientists, and graduate students to ontology engineering as a modeling techniqu...

  17. Model Driven Engineering with Ontology Technologies

    Science.gov (United States)

    Staab, Steffen; Walter, Tobias; Gröner, Gerd; Parreiras, Fernando Silva

    Ontologies constitute formal models of some aspect of the world that may be used for drawing interesting logical conclusions even for large models. Software models capture relevant characteristics of a software artifact to be developed, yet, most often these software models have limited formal semantics, or the underlying (often graphical) software language varies from case to case in a way that makes it hard if not impossible to fix its semantics. In this contribution, we survey the use of ontology technologies for software modeling in order to carry over advantages from ontology technologies to the software modeling domain. It will turn out that ontology-based metamodels constitute a core means for exploiting expressive ontology reasoning in the software modeling domain while remaining flexible enough to accommodate varying needs of software modelers.

  18. A priorean approach to time ontologies

    DEFF Research Database (Denmark)

    Øhrstrøm, Peter; Schärfe, Henrik

    2004-01-01

    Any non-trivial top-level ontology should take temporal notions into account. The details of how this should be done, however, are frequently debated. In this paper it is argued that "the four grades of tense-logical involvement" suggested by A.N. Prior form a useful framework for discussing how...... various temporal notions are related in a top-level ontology. Furthermore, a number of modern ontologies are analysed with respect to their incorporation of temporal notions. It is argued that all of them correspond to Prior's first and second grade, and that none of them reflect the views which Prior......'s third and fourth grade represent. Finally, the paper deals with Prior's ideas on a tensed ontology and it is argued that a logic based on the third grade and will be useful in the further development of tensed ontology....

  19. Geo-Ontologies Are Scale Dependent

    Science.gov (United States)

    Frank, A. U.

    2009-04-01

    Philosophers aim at a single ontology that describes "how the world is"; for information systems we aim only at ontologies that describe a conceptualization of reality (Guarino 1995; Gruber 2005). A conceptualization of the world implies a spatial and temporal scale: what are the phenomena, the objects and the speed of their change? Few articles (Reitsma et al. 2003) seem to address that an ontology is scale specific (but many articles indicate that ontologies are scale-free in another sense namely that they are scale free in the link densities between concepts). The scale in the conceptualization can be linked to the observation process. The extent of the support of the physical observation instrument and the sampling theorem indicate what level of detail we find in a dataset. These rules apply for remote sensing or sensor networks alike. An ontology of observations must include scale or level of detail, and concepts derived from observations should carry this relation forward. A simple example: in high resolution remote sensing image agricultural plots and roads between them are shown, at lower resolution, only the plots and not the roads are visible. This gives two ontologies, one with plots and roads, the other with plots only. Note that a neighborhood relation in the two different ontologies also yield different results. References Gruber, T. (2005). "TagOntology - a way to agree on the semantics of tagging data." Retrieved October 29, 2005., from http://tomgruber.org/writing/tagontology-tagcapm-talk.pdf. Guarino, N. (1995). "Formal Ontology, Conceptual Analysis and Knowledge Representation." International Journal of Human and Computer Studies. Special Issue on Formal Ontology, Conceptual Analysis and Knowledge Representation, edited by N. Guarino and R. Poli 43(5/6). Reitsma, F. and T. Bittner (2003). Process, Hierarchy, and Scale. Spatial Information Theory. Cognitive and Computational Foundations of Geographic Information ScienceInternational Conference

  20. TermGenie - a web-application for pattern-based ontology class generation.

    Science.gov (United States)

    Dietze, Heiko; Berardini, Tanya Z; Foulger, Rebecca E; Hill, David P; Lomax, Jane; Osumi-Sutherland, David; Roncaglia, Paola; Mungall, Christopher J

    2014-01-01

    Biological ontologies are continually growing and improving from requests for new classes (terms) by biocurators. These ontology requests can frequently create bottlenecks in the biocuration process, as ontology developers struggle to keep up, while manually processing these requests and create classes. TermGenie allows biocurators to generate new classes based on formally specified design patterns or templates. The system is web-based and can be accessed by any authorized curator through a web browser. Automated rules and reasoning engines are used to ensure validity, uniqueness and relationship to pre-existing classes. In the last 4 years the Gene Ontology TermGenie generated 4715 new classes, about 51.4% of all new classes created. The immediate generation of permanent identifiers proved not to be an issue with only 70 (1.4%) obsoleted classes. TermGenie is a web-based class-generation system that complements traditional ontology development tools. All classes added through pre-defined templates are guaranteed to have OWL equivalence axioms that are used for automatic classification and in some cases inter-ontology linkage. At the same time, the system is simple and intuitive and can be used by most biocurators without extensive training.

  1. OMIT: dynamic, semi-automated ontology development for the microRNA domain.

    Directory of Open Access Journals (Sweden)

    Jingshan Huang

    Full Text Available As a special class of short non-coding RNAs, microRNAs (a.k.a. miRNAs or miRs have been reported to perform important roles in various biological processes by regulating respective target genes. However, significant barriers exist during biologists' conventional miR knowledge discovery. Emerging semantic technologies, which are based upon domain ontologies, can render critical assistance to this problem. Our previous research has investigated the construction of a miR ontology, named Ontology for MIcroRNA Target Prediction (OMIT, the very first of its kind that formally encodes miR domain knowledge. Although it is unavoidable to have a manual component contributed by domain experts when building ontologies, many challenges have been identified for a completely manual development process. The most significant issue is that a manual development process is very labor-intensive and thus extremely expensive. Therefore, we propose in this paper an innovative ontology development methodology. Our contributions can be summarized as: (i We have continued the development and critical improvement of OMIT, solidly based on our previous research outcomes. (ii We have explored effective and efficient algorithms with which the ontology development can be seamlessly combined with machine intelligence and be accomplished in a semi-automated manner, thus significantly reducing large amounts of human efforts. A set of experiments have been conducted to thoroughly evaluate our proposed methodology.

  2. OMIT: dynamic, semi-automated ontology development for the microRNA domain.

    Science.gov (United States)

    Huang, Jingshan; Dang, Jiangbo; Borchert, Glen M; Eilbeck, Karen; Zhang, He; Xiong, Min; Jiang, Weijian; Wu, Hao; Blake, Judith A; Natale, Darren A; Tan, Ming

    2014-01-01

    As a special class of short non-coding RNAs, microRNAs (a.k.a. miRNAs or miRs) have been reported to perform important roles in various biological processes by regulating respective target genes. However, significant barriers exist during biologists' conventional miR knowledge discovery. Emerging semantic technologies, which are based upon domain ontologies, can render critical assistance to this problem. Our previous research has investigated the construction of a miR ontology, named Ontology for MIcroRNA Target Prediction (OMIT), the very first of its kind that formally encodes miR domain knowledge. Although it is unavoidable to have a manual component contributed by domain experts when building ontologies, many challenges have been identified for a completely manual development process. The most significant issue is that a manual development process is very labor-intensive and thus extremely expensive. Therefore, we propose in this paper an innovative ontology development methodology. Our contributions can be summarized as: (i) We have continued the development and critical improvement of OMIT, solidly based on our previous research outcomes. (ii) We have explored effective and efficient algorithms with which the ontology development can be seamlessly combined with machine intelligence and be accomplished in a semi-automated manner, thus significantly reducing large amounts of human efforts. A set of experiments have been conducted to thoroughly evaluate our proposed methodology.

  3. OMIT: Dynamic, Semi-Automated Ontology Development for the microRNA Domain

    Science.gov (United States)

    Huang, Jingshan; Dang, Jiangbo; Borchert, Glen M.; Eilbeck, Karen; Zhang, He; Xiong, Min; Jiang, Weijian; Wu, Hao; Blake, Judith A.; Natale, Darren A.; Tan, Ming

    2014-01-01

    As a special class of short non-coding RNAs, microRNAs (a.k.a. miRNAs or miRs) have been reported to perform important roles in various biological processes by regulating respective target genes. However, significant barriers exist during biologists' conventional miR knowledge discovery. Emerging semantic technologies, which are based upon domain ontologies, can render critical assistance to this problem. Our previous research has investigated the construction of a miR ontology, named Ontology for MIcroRNA Target Prediction (OMIT), the very first of its kind that formally encodes miR domain knowledge. Although it is unavoidable to have a manual component contributed by domain experts when building ontologies, many challenges have been identified for a completely manual development process. The most significant issue is that a manual development process is very labor-intensive and thus extremely expensive. Therefore, we propose in this paper an innovative ontology development methodology. Our contributions can be summarized as: (i) We have continued the development and critical improvement of OMIT, solidly based on our previous research outcomes. (ii) We have explored effective and efficient algorithms with which the ontology development can be seamlessly combined with machine intelligence and be accomplished in a semi-automated manner, thus significantly reducing large amounts of human efforts. A set of experiments have been conducted to thoroughly evaluate our proposed methodology. PMID:25025130

  4. Ontology-based, Tissue MicroArray oriented, image centered tissue bank

    Directory of Open Access Journals (Sweden)

    Viti Federica

    2008-04-01

    Full Text Available Abstract Background Tissue MicroArray technique is becoming increasingly important in pathology for the validation of experimental data from transcriptomic analysis. This approach produces many images which need to be properly managed, if possible with an infrastructure able to support tissue sharing between institutes. Moreover, the available frameworks oriented to Tissue MicroArray provide good storage for clinical patient, sample treatment and block construction information, but their utility is limited by the lack of data integration with biomolecular information. Results In this work we propose a Tissue MicroArray web oriented system to support researchers in managing bio-samples and, through the use of ontologies, enables tissue sharing aimed at the design of Tissue MicroArray experiments and results evaluation. Indeed, our system provides ontological description both for pre-analysis tissue images and for post-process analysis image results, which is crucial for information exchange. Moreover, working on well-defined terms it is then possible to query web resources for literature articles to integrate both pathology and bioinformatics data. Conclusions Using this system, users associate an ontology-based description to each image uploaded into the database and also integrate results with the ontological description of biosequences identified in every tissue. Moreover, it is possible to integrate the ontological description provided by the user with a full compliant gene ontology definition, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes.

  5. The Software Ontology (SWO): a resource for reproducibility in biomedical data analysis, curation and digital preservation.

    Science.gov (United States)

    Malone, James; Brown, Andy; Lister, Allyson L; Ison, Jon; Hull, Duncan; Parkinson, Helen; Stevens, Robert

    2014-01-01

    Biomedical ontologists to date have concentrated on ontological descriptions of biomedical entities such as gene products and their attributes, phenotypes and so on. Recently, effort has diversified to descriptions of the laboratory investigations by which these entities were produced. However, much biological insight is gained from the analysis of the data produced from these investigations, and there is a lack of adequate descriptions of the wide range of software that are central to bioinformatics. We need to describe how data are analyzed for discovery, audit trails, provenance and reproducibility. The Software Ontology (SWO) is a description of software used to store, manage and analyze data. Input to the SWO has come from beyond the life sciences, but its main focus is the life sciences. We used agile techniques to gather input for the SWO and keep engagement with our users. The result is an ontology that meets the needs of a broad range of users by describing software, its information processing tasks, data inputs and outputs, data formats versions and so on. Recently, the SWO has incorporated EDAM, a vocabulary for describing data and related concepts in bioinformatics. The SWO is currently being used to describe software used in multiple biomedical applications. The SWO is another element of the biomedical ontology landscape that is necessary for the description of biomedical entities and how they were discovered. An ontology of software used to analyze data produced by investigations in the life sciences can be made in such a way that it covers the important features requested and prioritized by its users. The SWO thus fits into the landscape of biomedical ontologies and is produced using techniques designed to keep it in line with user's needs. The Software Ontology is available under an Apache 2.0 license at http://theswo.sourceforge.net/; the Software Ontology blog can be read at http://softwareontology.wordpress.com.

  6. A Prototype Ontology Tool and Interface for Coastal Atlas Interoperability

    Science.gov (United States)

    Wright, D. J.; Bermudez, L.; O'Dea, L.; Haddad, T.; Cummins, V.

    2007-12-01

    While significant capacity has been built in the field of web-based coastal mapping and informatics in the last decade, little has been done to take stock of the implications of these efforts or to identify best practice in terms of taking lessons learned into consideration. This study reports on the second of two transatlantic workshops that bring together key experts from Europe, the United States and Canada to examine state-of-the-art developments in coastal web atlases (CWA), based on web enabled geographic information systems (GIS), along with future needs in mapping and informatics for the coastal practitioner community. While multiple benefits are derived from these tailor-made atlases (e.g. speedy access to multiple sources of coastal data and information; economic use of time by avoiding individual contact with different data holders), the potential exists to derive added value from the integration of disparate CWAs, to optimize decision-making at a variety of levels and across themes. The second workshop focused on the development of a strategy to make coastal web atlases interoperable by way of controlled vocabularies and ontologies. The strategy is based on web service oriented architecture and an implementation of Open Geospatial Consortium (OGC) web services, such as Web Feature Services (WFS) and Web Map Service (WMS). Atlases publishes Catalog Web Services (CSW) using ISO 19115 metadata and controlled vocabularies encoded as Uniform Resource Identifiers (URIs). URIs allows the terminology of each atlas to be uniquely identified and facilitates mapping of terminologies using semantic web technologies. A domain ontology was also created to formally represent coastal erosion terminology as a use case, and with a test linkage of those terms between the Marine Irish Digital Atlas and the Oregon Coastal Atlas. A web interface is being developed to discover coastal hazard themes in distributed coastal atlases as part of a broader International Coastal

  7. Ontologies and tag-statistics

    Science.gov (United States)

    Tibély, Gergely; Pollner, Péter; Vicsek, Tamás; Palla, Gergely

    2012-05-01

    Due to the increasing popularity of collaborative tagging systems, the research on tagged networks, hypergraphs, ontologies, folksonomies and other related concepts is becoming an important interdisciplinary area with great potential and relevance for practical applications. In most collaborative tagging systems the tagging by the users is completely ‘flat’, while in some cases they are allowed to define a shallow hierarchy for their own tags. However, usually no overall hierarchical organization of the tags is given, and one of the interesting challenges of this area is to provide an algorithm generating the ontology of the tags from the available data. In contrast, there are also other types of tagged networks available for research, where the tags are already organized into a directed acyclic graph (DAG), encapsulating the ‘is a sub-category of’ type of hierarchy between each other. In this paper, we study how this DAG affects the statistical distribution of tags on the nodes marked by the tags in various real networks. The motivation for this research was the fact that understanding the tagging based on a known hierarchy can help in revealing the hidden hierarchy of tags in collaborative tagging systems. We analyse the relation between the tag-frequency and the position of the tag in the DAG in two large sub-networks of the English Wikipedia and a protein-protein interaction network. We also study the tag co-occurrence statistics by introducing a two-dimensional (2D) tag-distance distribution preserving both the difference in the levels and the absolute distance in the DAG for the co-occurring pairs of tags. Our most interesting finding is that the local relevance of tags in the DAG (i.e. their rank or significance as characterized by, e.g., the length of the branches starting from them) is much more important than their global distance from the root. Furthermore, we also introduce a simple tagging model based on random walks on the DAG, capable of

  8. Ontologies and tag-statistics

    International Nuclear Information System (INIS)

    Tibély, Gergely; Vicsek, Tamás; Pollner, Péter; Palla, Gergely

    2012-01-01

    Due to the increasing popularity of collaborative tagging systems, the research on tagged networks, hypergraphs, ontologies, folksonomies and other related concepts is becoming an important interdisciplinary area with great potential and relevance for practical applications. In most collaborative tagging systems the tagging by the users is completely ‘flat’, while in some cases they are allowed to define a shallow hierarchy for their own tags. However, usually no overall hierarchical organization of the tags is given, and one of the interesting challenges of this area is to provide an algorithm generating the ontology of the tags from the available data. In contrast, there are also other types of tagged networks available for research, where the tags are already organized into a directed acyclic graph (DAG), encapsulating the ‘is a sub-category of’ type of hierarchy between each other. In this paper, we study how this DAG affects the statistical distribution of tags on the nodes marked by the tags in various real networks. The motivation for this research was the fact that understanding the tagging based on a known hierarchy can help in revealing the hidden hierarchy of tags in collaborative tagging systems. We analyse the relation between the tag-frequency and the position of the tag in the DAG in two large sub-networks of the English Wikipedia and a protein-protein interaction network. We also study the tag co-occurrence statistics by introducing a two-dimensional (2D) tag-distance distribution preserving both the difference in the levels and the absolute distance in the DAG for the co-occurring pairs of tags. Our most interesting finding is that the local relevance of tags in the DAG (i.e. their rank or significance as characterized by, e.g., the length of the branches starting from them) is much more important than their global distance from the root. Furthermore, we also introduce a simple tagging model based on random walks on the DAG, capable of

  9. Anthropological Component of Descartes’ Ontology

    Directory of Open Access Journals (Sweden)

    Anatolii M. Malivskyi

    2014-06-01

    Full Text Available The purpose of the article is to outline and comprehend the Descartes’ theory about anthropological component of ontology as the most important part of his philosophy. The accomplishment of this purpose covers the successive solution of the following tasks: 1 review of the research literature concerning the problem of human’s presence and the individual nature of truth; 2 emphasize the ambivalence of the basic intention of his legacy; 3 justify the thesis about constitutivity of human’s presence and comprehend passions as the form of disclosure of ontology’s anthropological component. Methodology. The use of the euristic potential of phenomenology, postpositivism and postmodernism makes it possible to emphasize the multiple-layer and multiple-meaning classical philosophy works, to comprehend the limitation and scarcity of the naïve-enlightening vision of human nature and to look for a new reception of European classics that provides the overcoming of established nihilism and pessimism concerning the interpretation of human nature. Scientific novelty. It is the first time that anthropological component of Descartes’ ontology became an object of particular attention. It previously lacked attention because of following main reasons: 1 traditional underestimating of the fact of Descartes’ legacy incompleteness as an unrealized anthropological project and 2 lack of proper attention to the individual nature of truth. The premise for its constructive overcoming is the attention to ambivalence of the basic intention and the significance of ethics in the philosopher’s legacy. His texts and research literature allow confirming the constitutive nature of human’s presence and passions as the key form of disclosure of the ontology anthropological component. Conclusions. The established tradition of interpretation the Descartes’ philosophizing nature as the filiation process of impersonal knowledge loses its cogency these days. The

  10. ANTHROPOLOGICAL COMPONENT OF DESCARTES’ ONTOLOGY

    Directory of Open Access Journals (Sweden)

    Anatolii M. Malivskyi

    2014-06-01

    Full Text Available The purpose of the article is to outline and comprehend the Descartes’ theory about anthropological component of ontology as the most important part of his philosophy. The accomplishment of this purpose covers the successive solution of the following tasks: 1 review of the research literature concerning the problem of human’s presence and the individual nature of truth; 2 emphasize the ambivalence of the basic intention of his legacy; 3 justify the thesis about constitutivity of human’s presence and comprehend passions as the form of disclosure of ontology’s anthropological component. Methodology. The use of the euristic potential of phenomenology, postpositivism and postmodernism makes it possible to emphasize the multiple-layer and multiple-meaning classical philosophy works, to comprehend the limitation and scarcity of the naïve-enlightening vision of human nature and to look for a new reception of European classics that provides the overcoming of established nihilism and pessimism concerning the interpretation of human nature. Scientific novelty. It is the first time that anthropological component of Descartes’ ontology became an object of particular attention. It previously lacked attention because of following main reasons: 1 traditional underestimating of the fact of Descartes’ legacy incompleteness as an unrealized anthropological project and 2 lack of proper attention to the individual nature of truth. The premise for its constructive overcoming is the attention to ambivalence of the basic intention and the significance of ethics in the philosopher’s legacy. His texts and research literature allow confirming the constitutive nature of human’s presence and passions as the key form of disclosure of the ontology anthropological component. Conclusions. The established tradition of interpretation the Descartes’ philosophizing nature as the filiation process of impersonal knowledge loses its cogency these days. The

  11. Tri-District Arts Consortium Summer Program.

    Science.gov (United States)

    Kirby, Charlotte O.

    1990-01-01

    The Tri-District Arts Consortium in South Carolina was formed to serve artistically gifted students in grades six-nine. The consortium developed a summer program offering music, dance, theatre, and visual arts instruction through a curriculum of intense training, performing, and hands-on experiences with faculty members and guest artists. (JDD)

  12. Increasing Sales by Developing Production Consortiums.

    Science.gov (United States)

    Smith, Christopher A.; Russo, Robert

    Intended to help rehabilitation facility administrators increase organizational income from manufacturing and/or contracted service sources, this document provides a decision-making model for the development of a production consortium. The document consists of five chapters and two appendices. Chapter 1 defines the consortium concept, explains…

  13. SPONGY (SPam ONtoloGY: Email Classification Using Two-Level Dynamic Ontology

    Directory of Open Access Journals (Sweden)

    Seongwook Youn

    2014-01-01

    Full Text Available Email is one of common communication methods between people on the Internet. However, the increase of email misuse/abuse has resulted in an increasing volume of spam emails over recent years. An experimental system has been designed and implemented with the hypothesis that this method would outperform existing techniques, and the experimental results showed that indeed the proposed ontology-based approach improves spam filtering accuracy significantly. In this paper, two levels of ontology spam filters were implemented: a first level global ontology filter and a second level user-customized ontology filter. The use of the global ontology filter showed about 91% of spam filtered, which is comparable with other methods. The user-customized ontology filter was created based on the specific user’s background as well as the filtering mechanism used in the global ontology filter creation. The main contributions of the paper are (1 to introduce an ontology-based multilevel filtering technique that uses both a global ontology and an individual filter for each user to increase spam filtering accuracy and (2 to create a spam filter in the form of ontology, which is user-customized, scalable, and modularized, so that it can be embedded to many other systems for better performance.

  14. SPONGY (SPam ONtoloGY): email classification using two-level dynamic ontology.

    Science.gov (United States)

    Youn, Seongwook

    2014-01-01

    Email is one of common communication methods between people on the Internet. However, the increase of email misuse/abuse has resulted in an increasing volume of spam emails over recent years. An experimental system has been designed and implemented with the hypothesis that this method would outperform existing techniques, and the experimental results showed that indeed the proposed ontology-based approach improves spam filtering accuracy significantly. In this paper, two levels of ontology spam filters were implemented: a first level global ontology filter and a second level user-customized ontology filter. The use of the global ontology filter showed about 91% of spam filtered, which is comparable with other methods. The user-customized ontology filter was created based on the specific user's background as well as the filtering mechanism used in the global ontology filter creation. The main contributions of the paper are (1) to introduce an ontology-based multilevel filtering technique that uses both a global ontology and an individual filter for each user to increase spam filtering accuracy and (2) to create a spam filter in the form of ontology, which is user-customized, scalable, and modularized, so that it can be embedded to many other systems for better performance.

  15. SPONGY (SPam ONtoloGY): Email Classification Using Two-Level Dynamic Ontology

    Science.gov (United States)

    2014-01-01

    Email is one of common communication methods between people on the Internet. However, the increase of email misuse/abuse has resulted in an increasing volume of spam emails over recent years. An experimental system has been designed and implemented with the hypothesis that this method would outperform existing techniques, and the experimental results showed that indeed the proposed ontology-based approach improves spam filtering accuracy significantly. In this paper, two levels of ontology spam filters were implemented: a first level global ontology filter and a second level user-customized ontology filter. The use of the global ontology filter showed about 91% of spam filtered, which is comparable with other methods. The user-customized ontology filter was created based on the specific user's background as well as the filtering mechanism used in the global ontology filter creation. The main contributions of the paper are (1) to introduce an ontology-based multilevel filtering technique that uses both a global ontology and an individual filter for each user to increase spam filtering accuracy and (2) to create a spam filter in the form of ontology, which is user-customized, scalable, and modularized, so that it can be embedded to many other systems for better performance. PMID:25254240

  16. Semantic Web Ontology and Data Integration: a Case Study in Aiding Psychiatric Drug Repurposing.

    Science.gov (United States)

    Liang, Chen; Sun, Jingchun; Tao, Cui

    2015-01-01

    There remain significant difficulties selecting probable candidate drugs from existing databases. We describe an ontology-oriented approach to represent the nexus between genes, drugs, phenotypes, symptoms, and diseases from multiple information sources. We also report a case study in which we attempted to explore candidate drugs effective for bipolar disorder and epilepsy. We constructed an ontology incorporating knowledge between the two diseases and performed semantic reasoning tasks with the ontology. The results suggested 48 candidate drugs that hold promise for further breakthrough. The evaluation demonstrated the validity our approach. Our approach prioritizes the candidate drugs that have potential associations among genes, phenotypes and symptoms, and thus facilitates the data integration and drug repurposing in psychiatric disorders.

  17. Consortium for military LCD display procurement

    Science.gov (United States)

    Echols, Gregg

    2002-08-01

    International Display Consortium (IDC) is the joining together of display companies to combined their buying power and obtained favorable terms with a major LCD manufacturer. Consolidating the buying power and grouping the demand enables the rugged display industry of avionics, ground vehicles, and ship based display manufacturers to have unencumbered access to high performance AMLCDs while greatly reducing risk and lowering cost. With an unrestricted supply of AMLCD displays, the consortium members have total control of their risk, cost, deliveries and added value partners. Every display manufacturer desires a very close relationship with a display vender. With IDC each consortium member achieves a close relationship. Consortium members enjoy cost effective access to high performance, industry standard sized LCD panels, and modified commercial displays with 100 degree C clearing points and portrait configurations. Consortium members also enjoy proposal support, technical support and long-term support.

  18. The MGED Ontology: a resource for semantics-based description of microarray experiments.

    Science.gov (United States)

    Whetzel, Patricia L; Parkinson, Helen; Causton, Helen C; Fan, Liju; Fostel, Jennifer; Fragoso, Gilberto; Game, Laurence; Heiskanen, Mervi; Morrison, Norman; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Taylor, Chris; White, Joseph; Stoeckert, Christian J

    2006-04-01

    The generation of large amounts of microarray data and the need to share these data bring challenges for both data management and annotation and highlights the need for standards. MIAME specifies the minimum information needed to describe a microarray experiment and the Microarray Gene Expression Object Model (MAGE-OM) and resulting MAGE-ML provide a mechanism to standardize data representation for data exchange, however a common terminology for data annotation is needed to support these standards. Here we describe the MGED Ontology (MO) developed by the Ontology Working Group of the Microarray Gene Expression Data (MGED) Society. The MO provides terms for annotating all aspects of a microarray experiment from the design of the experiment and array layout, through to the preparation of the biological sample and the protocols used to hybridize the RNA and analyze the data. The MO was developed to provide terms for annotating experiments in line with the MIAME guidelines, i.e. to provide the semantics to describe a microarray experiment according to the concepts specified in MIAME. The MO does not attempt to incorporate terms from existing ontologies, e.g. those that deal with anatomical parts or developmental stages terms, but provides a framework to reference terms in other ontologies and therefore facilitates the use of ontologies in microarray data annotation. The MGED Ontology version.1.2.0 is available as a file in both DAML and OWL formats at http://mged.sourceforge.net/ontologies/index.php. Release notes and annotation examples are provided. The MO is also provided via the NCICB's Enterprise Vocabulary System (http://nciterms.nci.nih.gov/NCIBrowser/Dictionary.do). Stoeckrt@pcbi.upenn.edu Supplementary data are available at Bioinformatics online.

  19. Ontology-based representation and analysis of host-Brucella interactions.

    Science.gov (United States)

    Lin, Yu; Xiang, Zuoshuang; He, Yongqun

    2015-01-01

    Biomedical ontologies are representations of classes of entities in the biomedical domain and how these classes are related in computer- and human-interpretable formats. Ontologies support data standardization and exchange and provide a basis for computer-assisted automated reasoning. IDOBRU is an ontology in the domain of Brucella and brucellosis. Brucella is a Gram-negative intracellular bacterium that causes brucellosis, the most common zoonotic disease in the world. In this study, IDOBRU is used as a platform to model and analyze how the hosts, especially host macrophages, interact with virulent Brucella strains or live attenuated Brucella vaccine strains. Such a study allows us to better integrate and understand intricate Brucella pathogenesis and host immunity mechanisms. Different levels of host-Brucella interactions based on different host cell types and Brucella strains were first defined ontologically. Three important processes of virulent Brucella interacting with host macrophages were represented: Brucella entry into macrophage, intracellular trafficking, and intracellular replication. Two Brucella pathogenesis mechanisms were ontologically represented: Brucella Type IV secretion system that supports intracellular trafficking and replication, and Brucella erythritol metabolism that participates in Brucella intracellular survival and pathogenesis. The host cell death pathway is critical to the outcome of host-Brucella interactions. For better survival and replication, virulent Brucella prevents macrophage cell death. However, live attenuated B. abortus vaccine strain RB51 induces caspase-2-mediated proinflammatory cell death. Brucella-associated cell death processes are represented in IDOBRU. The gene and protein information of 432 manually annotated Brucella virulence factors were represented using the Ontology of Genes and Genomes (OGG) and Protein Ontology (PRO), respectively. Seven inference rules were defined to capture the knowledge of host

  20. Nuclear Nonproliferation Ontology Assessment Team Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Strasburg, Jana D.; Hohimer, Ryan E.

    2012-01-01

    Final Report for the NA22 Simulations, Algorithm and Modeling (SAM) Ontology Assessment Team's efforts from FY09-FY11. The Ontology Assessment Team began in May 2009 and concluded in September 2011. During this two-year time frame, the Ontology Assessment team had two objectives: (1) Assessing the utility of knowledge representation and semantic technologies for addressing nuclear nonproliferation challenges; and (2) Developing ontological support tools that would provide a framework for integrating across the Simulation, Algorithm and Modeling (SAM) program. The SAM Program was going through a large assessment and strategic planning effort during this time and as a result, the relative importance of these two objectives changed, altering the focus of the Ontology Assessment Team. In the end, the team conducted an assessment of the state of art, created an annotated bibliography, and developed a series of ontological support tools, demonstrations and presentations. A total of more than 35 individuals from 12 different research institutions participated in the Ontology Assessment Team. These included subject matter experts in several nuclear nonproliferation-related domains as well as experts in semantic technologies. Despite the diverse backgrounds and perspectives, the Ontology Assessment team functioned very well together and aspects could serve as a model for future inter-laboratory collaborations and working groups. While the team encountered several challenges and learned many lessons along the way, the Ontology Assessment effort was ultimately a success that led to several multi-lab research projects and opened up a new area of scientific exploration within the Office of Nuclear Nonproliferation and Verification.

  1. Assessing the practice of biomedical ontology evaluation: Gaps and opportunities.

    Science.gov (United States)

    Amith, Muhammad; He, Zhe; Bian, Jiang; Lossio-Ventura, Juan Antonio; Tao, Cui

    2018-04-01

    With the proliferation of heterogeneous health care data in the last three decades, biomedical ontologies and controlled biomedical terminologies play a more and more important role in knowledge representation and management, data integration, natural language processing, as well as decision support for health information systems and biomedical research. Biomedical ontologies and controlled terminologies are intended to assure interoperability. Nevertheless, the quality of biomedical ontologies has hindered their applicability and subsequent adoption in real-world applications. Ontology evaluation is an integral part of ontology development and maintenance. In the biomedicine domain, ontology evaluation is often conducted by third parties as a quality assurance (or auditing) effort that focuses on identifying modeling errors and inconsistencies. In this work, we first organized four categorical schemes of ontology evaluation methods in the existing literature to create an integrated taxonomy. Further, to understand the ontology evaluation practice in the biomedicine domain, we reviewed a sample of 200 ontologies from the National Center for Biomedical Ontology (NCBO) BioPortal-the largest repository for biomedical ontologies-and observed that only 15 of these ontologies have documented evaluation in their corresponding inception papers. We then surveyed the recent quality assurance approaches for biomedical ontologies and their use. We also mapped these quality assurance approaches to the ontology evaluation criteria. It is our anticipation that ontology evaluation and quality assurance approaches will be more widely adopted in the development life cycle of biomedical ontologies. Copyright © 2018 Elsevier Inc. All rights reserved.

  2. Ontology Versioning and Change Detection on the Web

    NARCIS (Netherlands)

    Klein, Michel; Fensel, Dieter; Kiryakov, Atanas; Ognyanov, Damyan

    2002-01-01

    To effectively use ontologies on the Web, it is essential that changes in ontologies are managed well. This paper analyzes the topic of ontology versioning in the context of the Web by looking at the characteristics of the version relation between ontologies and at the identification of online

  3. A Knowledge Engineering Approach to Develop Domain Ontology

    Science.gov (United States)

    Yun, Hongyan; Xu, Jianliang; Xiong, Jing; Wei, Moji

    2011-01-01

    Ontologies are one of the most popular and widespread means of knowledge representation and reuse. A few research groups have proposed a series of methodologies for developing their own standard ontologies. However, because this ontological construction concerns special fields, there is no standard method to build domain ontology. In this paper,…

  4. St. Thomas and the hilemorfic ontology

    Directory of Open Access Journals (Sweden)

    Lawrence Dewan, O.P.

    2009-06-01

    Full Text Available This article presents the relevancy of Aristotle’s hylemorphic ontology.Aristotle himself highlighted the importance and astonishing complexityof the problem of prime matter’s ontological status and he presenting thesolution in his doctrine of hylemorphism. As Saint Thomas Aquinasnoted, it is a crucial issue for philosophy because all four, hilemorfism,logic, physics and metaphysics, stand or fall depending on a correctunderstanding of the ontology of prime matter and of the kind of causalrelationship which exist between prime matter and substantial form ingenerable and corruptible substance.

  5. Hierarchical Analysis of the Omega Ontology

    Energy Technology Data Exchange (ETDEWEB)

    Joslyn, Cliff A.; Paulson, Patrick R.

    2009-12-01

    Initial delivery for mathematical analysis of the Omega Ontology. We provide an analysis of the hierarchical structure of a version of the Omega Ontology currently in use within the US Government. After providing an initial statistical analysis of the distribution of all link types in the ontology, we then provide a detailed order theoretical analysis of each of the four main hierarchical links present. This order theoretical analysis includes the distribution of components and their properties, their parent/child and multiple inheritance structure, and the distribution of their vertical ranks.

  6. Formalization of taxon-based constraints to detect inconsistencies in annotation and ontology development

    Directory of Open Access Journals (Sweden)

    Mungall Christopher J

    2010-10-01

    Full Text Available Abstract Background The Gene Ontology project supports categorization of gene products according to their location of action, the molecular functions that they carry out, and the processes that they are involved in. Although the ontologies are intentionally developed to be taxon neutral, and to cover all species, there are inherent taxon specificities in some branches. For example, the process 'lactation' is specific to mammals and the location 'mitochondrion' is specific to eukaryotes. The lack of an explicit formalization of these constraints can lead to errors and inconsistencies in automated and manual annotation. Results We have formalized the taxonomic constraints implicit in some GO classes, and specified these at various levels in the ontology. We have also developed an inference system that can be used to check for violations of these constraints in annotations. Using the constraints in conjunction with the inference system, we have detected and removed errors in annotations and improved the structure of the ontology. Conclusions Detection of inconsistencies in taxon-specificity enables gradual improvement of the ontologies, the annotations, and the formalized constraints. This is progressively improving the quality of our data. The full system is available for download, and new constraints or proposed changes to constraints can be submitted online at https://sourceforge.net/tracker/?atid=605890&group_id=36855.

  7. A Hydrological Sensor Web Ontology Based on the SSN Ontology: A Case Study for a Flood

    Directory of Open Access Journals (Sweden)

    Chao Wang

    2017-12-01

    Full Text Available Accompanying the continuous development of sensor network technology, sensors worldwide are constantly producing observation data. However, the sensors and their data from different observation platforms are sometimes difficult to use collaboratively in response to natural disasters such as floods for the lack of semantics. In this paper, a hydrological sensor web ontology based on SSN ontology is proposed to describe the heterogeneous hydrological sensor web resources by importing the time and space ontology, instantiating the hydrological classes, and establishing reasoning rules. This work has been validated by semantic querying and knowledge acquiring experiments. The results demonstrate the feasibility and effectiveness of the proposed ontology and its potential to grow into a more comprehensive ontology for hydrological monitoring collaboratively. In addition, this method of ontology modeling is generally applicable to other applications and domains.

  8. Fiscal 2000 regional consortium research and development project - regional new technology creation research and development. Massive rapid identification of gene functions; 2000 nendo chiiki consortium kenkyu kaihatsu jigyo - chiiki shingijutsu soshutsu kenkyu kaihatsu seika hokokusho. Idenshi kino no tairyo jinsoku dotei ni kansuru kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-03-01

    Efforts are exerted to develop a system for massive and rapid identification of unknown genes through the utilization of techniques based on the unusual membrane fusion characteristics of HVJ (hemagglutinating virus of Japan), which enables the introduction of genes efficiently and uniformly into cultured cells and living organs (development into a kit). Activities are conducted in the three fields of (1) the development of a method for introducing genes using an HVJ envelop vector, (2) a survey of kit marketing and cold storage facilities in the selling and distribution of the kit, and (3) a comprehensive survey. In the field of (1), studies are conducted for the establishment of methods for HVJ envelop vector production and refining, the establishment of an optimized method for encapsulating genes into the HVJ envelop vector, and the introduction of genes into cultured central neurons using the HVJ envelop vector system. A refining method has been established, which comprises the inoculation of HVJ into eggs, 4-day culture, egg cutting, liquid sampling (chorioallantoic liquid), inactivation (addition of alkylating agent), filtration, enrichment (ultrafiltration), and an anion exchange chromatogram. (NEDO)

  9. An empirical analysis of ontology reuse in BioPortal.

    Science.gov (United States)

    Ochs, Christopher; Perl, Yehoshua; Geller, James; Arabandi, Sivaram; Tudorache, Tania; Musen, Mark A

    2017-07-01

    Biomedical ontologies often reuse content (i.e., classes and properties) from other ontologies. Content reuse enables a consistent representation of a domain and reusing content can save an ontology author significant time and effort. Prior studies have investigated the existence of reused terms among the ontologies in the NCBO BioPortal, but as of yet there has not been a study investigating how the ontologies in BioPortal utilize reused content in the modeling of their own content. In this study we investigate how 355 ontologies hosted in the NCBO BioPortal reuse content from other ontologies for the purposes of creating new ontology content. We identified 197 ontologies that reuse content. Among these ontologies, 108 utilize reused classes in the modeling of their own classes and 116 utilize reused properties in class restrictions. Current utilization of reuse and quality issues related to reuse are discussed. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. The ontology-based answers (OBA) service: a connector for embedded usage of ontologies in applications.

    Science.gov (United States)

    Dönitz, Jürgen; Wingender, Edgar

    2012-01-01

    The semantic web depends on the use of ontologies to let electronic systems interpret contextual information. Optimally, the handling and access of ontologies should be completely transparent to the user. As a means to this end, we have developed a service that attempts to bridge the gap between experts in a certain knowledge domain, ontologists, and application developers. The ontology-based answers (OBA) service introduced here can be embedded into custom applications to grant access to the classes of ontologies and their relations as most important structural features as well as to information encoded in the relations between ontology classes. Thus computational biologists can benefit from ontologies without detailed knowledge about the respective ontology. The content of ontologies is mapped to a graph of connected objects which is compatible to the object-oriented programming style in Java. Semantic functions implement knowledge about the complex semantics of an ontology beyond the class hierarchy and "partOf" relations. By using these OBA functions an application can, for example, provide a semantic search function, or (in the examples outlined) map an anatomical structure to the organs it belongs to. The semantic functions relieve the application developer from the necessity of acquiring in-depth knowledge about the semantics and curation guidelines of the used ontologies by implementing the required knowledge. The architecture of the OBA service encapsulates the logic to process ontologies in order to achieve a separation from the application logic. A public server with the current plugins is available and can be used with the provided connector in a custom application in scenarios analogous to the presented use cases. The server and the client are freely available if a project requires the use of custom plugins or non-public ontologies. The OBA service and further documentation is available at http://www.bioinf.med.uni-goettingen.de/projects/oba.

  11. OntoMaven: Maven-based Ontology Development and Management of Distributed Ontology Repositories

    OpenAIRE

    Paschke, Adrian

    2013-01-01

    In collaborative agile ontology development projects support for modular reuse of ontologies from large existing remote repositories, ontology project life cycle management, and transitive dependency management are important needs. The Apache Maven approach has proven its success in distributed collaborative Software Engineering by its widespread adoption. The contribution of this paper is a new design artifact called OntoMaven. OntoMaven adopts the Maven-based development methodology and ada...

  12. PHENOstruct: Prediction of human phenotype ontology terms using heterogeneous data sources.

    Science.gov (United States)

    Kahanda, Indika; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa

    2015-01-01

    The human phenotype ontology (HPO) was recently developed as a standardized vocabulary for describing the phenotype abnormalities associated with human diseases. At present, only a small fraction of human protein coding genes have HPO annotations. But, researchers believe that a large portion of currently unannotated genes are related to disease phenotypes. Therefore, it is important to predict gene-HPO term associations using accurate computational methods. In this work we demonstrate the performance advantage of the structured SVM approach which was shown to be highly effective for Gene Ontology term prediction in comparison to several baseline methods. Furthermore, we highlight a collection of informative data sources suitable for the problem of predicting gene-HPO associations, including large scale literature mining data.

  13. Ontology-based multi-agent systems

    Energy Technology Data Exchange (ETDEWEB)

    Hadzic, Maja; Wongthongtham, Pornpit; Dillon, Tharam; Chang, Elizabeth [Digital Ecosystems and Business Intelligence Institute, Perth, WA (Australia)

    2009-07-01

    The Semantic web has given a great deal of impetus to the development of ontologies and multi-agent systems. Several books have appeared which discuss the development of ontologies or of multi-agent systems separately on their own. The growing interaction between agents and ontologies has highlighted the need for integrated development of these. This book is unique in being the first to provide an integrated treatment of the modeling, design and implementation of such combined ontology/multi-agent systems. It provides clear exposition of this integrated modeling and design methodology. It further illustrates this with two detailed case studies in (a) the biomedical area and (b) the software engineering area. The book is, therefore, of interest to researchers, graduate students and practitioners in the semantic web and web science area. (orig.)

  14. Learning Ontology from Object-Relational Database

    Directory of Open Access Journals (Sweden)

    Kaulins Andrejs

    2015-12-01

    Full Text Available This article describes a method of transformation of object-relational model into ontology. The offered method uses learning rules for such complex data types as object tables and collections – arrays of a variable size, as well as nested tables. Object types and their transformation into ontologies are insufficiently considered in scientific literature. This fact served as motivation for the authors to investigate this issue and to write the article on this matter. In the beginning, we acquaint the reader with complex data types and object-oriented databases. Then we describe an algorithm of transformation of complex data types into ontologies. At the end of the article, some examples of ontologies described in the OWL language are given.

  15. Randomised controlled trials in educational research: Ontological ...

    African Journals Online (AJOL)

    based practice in medical and clinical settings because they are associated with a particular ontological and epistemological perspective that is situated within a positivist world view. It assumes that environments and variables can be controlled ...

  16. Interoperability between phenotype and anatomy ontologies.

    Science.gov (United States)

    Hoehndorf, Robert; Oellrich, Anika; Rebholz-Schuhmann, Dietrich

    2010-12-15

    Phenotypic information is important for the analysis of the molecular mechanisms underlying disease. A formal ontological representation of phenotypic information can help to identify, interpret and infer phenotypic traits based on experimental findings. The methods that are currently used to represent data and information about phenotypes fail to make the semantics of the phenotypic trait explicit and do not interoperate with ontologies of anatomy and other domains. Therefore, valuable resources for the analysis of phenotype studies remain unconnected and inaccessible to automated analysis and reasoning. We provide a framework to formalize phenotypic descriptions and make their semantics explicit. Based on this formalization, we provide the means to integrate phenotypic descriptions with ontologies of other domains, in particular anatomy and physiology. We demonstrate how our framework leads to the capability to represent disease phenotypes, perform powerful queries that were not possible before and infer additional knowledge. http://bioonto.de/pmwiki.php/Main/PheneOntology.

  17. Using an ontology for network attack planning

    CSIR Research Space (South Africa)

    Van Heerden, R

    2016-09-01

    Full Text Available The modern complexity of network attacks and their counter-measures (cyber operations) requires detailed planning. This paper presents a Network Attack Planning ontology which is aimed at providing support for planning such network operations within...

  18. Ontology Enabled Generation of Embedded Web Services

    DEFF Research Database (Denmark)

    Hansen, Klaus Marius; Zhang, Weishan; Soares, Goncalo Teofilo Afonso Pinheiro

    2008-01-01

    Web services are increasingly adopted as a service provision mechanism in pervasive computing environments. Implementing web services on networked, embedded devices raises a number of challenges, for example efficiency of web services, handling of variability and dependencies of hardware...... and software platforms, and of devices state and context changes. To address these challenges, we developed a Web service compiler, Limbo, in which Web Ontology Language (OWL) ontologies are used to make the Limbo compiler aware of its compilation context, such as targeted hardware and software. At the same...... time, knowledge on device details, platform dependencies, and resource/power consumption is built into the supporting ontologies, which are used to configure Limbo for generating resource efficient web service code. A state machine ontology is used to generate stub code to facilitate handling of state...

  19. Metadata and Ontologies in Learning Resources Design

    Science.gov (United States)

    Vidal C., Christian; Segura Navarrete, Alejandra; Menéndez D., Víctor; Zapata Gonzalez, Alfredo; Prieto M., Manuel

    Resource design and development requires knowledge about educational goals, instructional context and information about learner's characteristics among other. An important information source about this knowledge are metadata. However, metadata by themselves do not foresee all necessary information related to resource design. Here we argue the need to use different data and knowledge models to improve understanding the complex processes related to e-learning resources and their management. This paper presents the use of semantic web technologies, as ontologies, supporting the search and selection of resources used in design. Classification is done, based on instructional criteria derived from a knowledge acquisition process, using information provided by IEEE-LOM metadata standard. The knowledge obtained is represented in an ontology using OWL and SWRL. In this work we give evidence of the implementation of a Learning Object Classifier based on ontology. We demonstrate that the use of ontologies can support the design activities in e-learning.

  20. A Bayesian Network Approach to Ontology Mapping

    National Research Council Canada - National Science Library

    Pan, Rong; Ding, Zhongli; Yu, Yang; Peng, Yun

    2005-01-01

    This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling uncertainty in semantic web...

  1. Language and embodied consciousness: A Peircean ontological ...

    African Journals Online (AJOL)

    An ontology of language: its source and place in First Language ... knowledge they supposedly gain in school with their immediate environment and their lived .... looking stick in space looks bent at the point it enters the medium of water.

  2. Making methodology a matter of process ontology

    DEFF Research Database (Denmark)

    Revsbæk, Line

    2016-01-01

    This paper presents a practice of doing qualitative interview analysis from the insights of the process ontology in G. H. Mead’s Philosophy of the Present (1932). The paper presents two cases of analyzing in the present while listening to recorded interview material eliciting researcher’s case...... study and otherwise related experiences creating case narratives inclusive of researcher’s reflexive voice. The paper presents an auto-ethnographic approach to data analysis based on process theory ontology....

  3. On the ontological emergence from quantum regime

    Energy Technology Data Exchange (ETDEWEB)

    Luty, Damian [Adam Mickiewicz University, Poznan (Poland)

    2014-07-01

    There are several views on the relation between quantum physics and theory of relativity (especially General Relativity, GR). A popular perspective is this: GR with its macroscopic gravitational effects will turn out to be a limit of a more fundamental theory which should consider discrete physics and not deal with continuity (like theory of relativity). Thus, GR will emerge from a more basic theory, which should be quantum-like. One could call this an epistemic emergence view towards fundamental theories. The question is, given that scientific realism is valid: should emergence be a fundamental notion in our ontological view about the evolving, physical Universe? Is there an ontological emergence fully compatible with the notion of fundamentality? I argue that if we want to defend ontological emergence (from quantum to macroscopic regime) as something fundamental, we will arrive at the position of metaphysics of dispositions (and I argue, why this is undesirable), or conclude, that we cannot square fully fundamental ontology with the notion of emergence, and that we have to accept an ontological pluralism relativised to a certain scale. I defend the latter proposition, showing, that epistemic emergence doesn't entail (logically) ontological emergence.

  4. An ontology for major histocompatibility restriction.

    Science.gov (United States)

    Vita, Randi; Overton, James A; Seymour, Emily; Sidney, John; Kaufman, Jim; Tallmadge, Rebecca L; Ellis, Shirley; Hammond, John; Butcher, Geoff W; Sette, Alessandro; Peters, Bjoern

    2016-01-01

    MHC molecules are a highly diverse family of proteins that play a key role in cellular immune recognition. Over time, different techniques and terminologies have been developed to identify the specific type(s) of MHC molecule involved in a specific immune recognition context. No consistent nomenclature exists across different vertebrate species. To correctly represent MHC related data in The Immune Epitope Database (IEDB), we built upon a previously established MHC ontology and created an ontology to represent MHC molecules as they relate to immunological experiments. This ontology models MHC protein chains from 16 species, deals with different approaches used to identify MHC, such as direct sequencing verses serotyping, relates engineered MHC molecules to naturally occurring ones, connects genetic loci, alleles, protein chains and multi-chain proteins, and establishes evidence codes for MHC restriction. Where available, this work is based on existing ontologies from the OBO foundry. Overall, representing MHC molecules provides a challenging and practically important test case for ontology building, and could serve as an example of how to integrate other ontology building efforts into web resources.

  5. The Development of Ontology from Multiple Databases

    Science.gov (United States)

    Kasim, Shahreen; Aswa Omar, Nurul; Fudzee, Mohd Farhan Md; Azhar Ramli, Azizul; Aizi Salamat, Mohamad; Mahdin, Hairulnizam

    2017-08-01

    The area of halal industry is the fastest growing global business across the world. The halal food industry is thus crucial for Muslims all over the world as it serves to ensure them that the food items they consume daily are syariah compliant. Currently, ontology has been widely used in computer sciences area such as web on the heterogeneous information processing, semantic web, and information retrieval. However, ontology has still not been used widely in the halal industry. Today, Muslim community still have problem to verify halal status for products in the market especially foods consisting of E number. This research tried to solve problem in validating the halal status from various halal sources. There are various chemical ontology from multilple databases found to help this ontology development. The E numbers in this chemical ontology are codes for chemicals that can be used as food additives. With this E numbers ontology, Muslim community could identify and verify the halal status effectively for halal products in the market.

  6. COHeRE: Cross-Ontology Hierarchical Relation Examination for Ontology Quality Assurance.

    Science.gov (United States)

    Cui, Licong

    Biomedical ontologies play a vital role in healthcare information management, data integration, and decision support. Ontology quality assurance (OQA) is an indispensable part of the ontology engineering cycle. Most existing OQA methods are based on the knowledge provided within the targeted ontology. This paper proposes a novel cross-ontology analysis method, Cross-Ontology Hierarchical Relation Examination (COHeRE), to detect inconsistencies and possible errors in hierarchical relations across multiple ontologies. COHeRE leverages the Unified Medical Language System (UMLS) knowledge source and the MapReduce cloud computing technique for systematic, large-scale ontology quality assurance work. COHeRE consists of three main steps with the UMLS concepts and relations as the input. First, the relations claimed in source vocabularies are filtered and aggregated for each pair of concepts. Second, inconsistent relations are detected if a concept pair is related by different types of relations in different source vocabularies. Finally, the uncovered inconsistent relations are voted according to their number of occurrences across different source vocabularies. The voting result together with the inconsistent relations serve as the output of COHeRE for possible ontological change. The highest votes provide initial suggestion on how such inconsistencies might be fixed. In UMLS, 138,987 concept pairs were found to have inconsistent relationships across multiple source vocabularies. 40 inconsistent concept pairs involving hierarchical relationships were randomly selected and manually reviewed by a human expert. 95.8% of the inconsistent relations involved in these concept pairs indeed exist in their source vocabularies rather than being introduced by mistake in the UMLS integration process. 73.7% of the concept pairs with suggested relationship were agreed by the human expert. The effectiveness of COHeRE indicates that UMLS provides a promising environment to enhance

  7. Evaluation of the XRCC1 gene as a phenotypic modifier in BRCA1/2 mutation carriers. Results from the consortium of investigators of modifiers of BRCA1/BRCA2

    NARCIS (Netherlands)

    Osorio, A.; Milne, R. L.; Alonso, R.; Pita, G.; Peterlongo, P.; Teulé, A.; Nathanson, K. L.; Domchek, S. M.; Rebbeck, T.; Lasa, A.; Konstantopoulou, I.; Hogervorst, F. B.; Verhoef, S.; van Dooren, M. F.; Jager, A.; Ausems, M. G. E. M.; Aalfs, C. M.; van Asperen, C. J.; Vreeswijk, M.; Waisfisz, Q.; van Roozendaal, C. E.; Ligtenberg, M. J.; Easton, D. F.; Peock, S.; Cook, M.; Oliver, C. T.; Frost, D.; Curzon, B.; Evans, D. G.; Lalloo, F.; Eeles, R.; Izatt, L.; Davidson, R.; Adlard, J.; Eccles, D.; Ong, K.-r; Douglas, F.; Downing, S.; Brewer, C.; Walker, L.; Nevanlinna, H.; Aittomäki, K.; Couch, F. J.; Fredericksen, Z.; Lindor, N. M.; Godwin, A.; Isaacs, C.; Caligo, M. A.; Loman, N.; Jernström, H.; Barbany-Bustinza, G.; Liljegren, A.; Ehrencrona, H.; Stenmark-Askmalm, M.; Feliubadaló, L.; Manoukian, S.; Peissel, B.; Zaffaroni, D.; Bonanni, B.; Fortuzzi, S.; Johannsson, O. T.; Chenevix-Trench, G.; Chen, X.-C.; Beesley, J.; Spurdle, A. B.; Sinilnikova, O. M.; Healey, S.; McGuffog, L.; Antoniou, A. C.; Brunet, J.; Radice, P.; Benítez, J.; Hogervorst, F. B. L.; Verheus, M.; van 't Veer, L. J.; van Leeuwen, F. E.; Rookus, M. A.; Collée, M.; van den Ouweland, A. M. W.; Hooning, M. J.; Tilanus-Linthorst, M. M. A.; Seynaeve, C.; Wijnen, J. T.; Vreeswijk, M. P.; Tollenaar, R. A.; Devilee, P.; Hoogerbrugge, N.; Ausems, M. G.; van der Luijt, R. B.; van Os, T. A.; Gille, J. J. P.; Meijers-Heijboer, H. E. J.; Gomez-Garcia, E. B.; Blok, Marinus J.; Caanen, B.; Oosterwijk, J. C.; van der Hout, A. H.; Mourits, M. J.; Vasen, H. F.; Peock, Susan; Cook, Margaret; Oliver, Clare; Frost, Debra; Miedzybrodzka, Zosia; Gregory, Helen; Morrison, Patrick; Jeffers, Lisa; Cole, Trevor; McKeown, Carole; Ong, Kai-Ren; Hoffman, Jonathan; Donaldson, Alan; Paterson, Joan; Downing, Sarah; Taylor, Amy; Murray, Alexandra; Rogers, Mark T.; McCann, Emma; Kennedy, M. John; Barton, David; East, South; Porteous, Mary; Drummond, Sarah; Brewer, Carole; Kivuva, Emma; Searle, Anne; Goodman, Selina; Hill, Kathryn; Davidson, Rosemarie; Bradshaw, Nicola; Snadden, Lesley; Longmuir, Mark; Watt, Catherine; Gibson, Sarah; Izatt, Louise; Jacobs, Chris; Langman, Caroline; Whaite, Anna; Dorkins, Huw; Barwell, Julian; Adlard, Julian; Chu, Carol; Miller, Julie; Ellis, Ian; Evans, D. Gareth; Lalloo, Fiona; Taylor, Jane; Side, Lucy; Male, Alison; Berlin, Cheryl; Eason, Jacqueline; Collier, Rebecca; Douglas, Fiona; Claber, Oonagh; Walker, Lisa; McLeod, Diane; Halliday, Dorothy; Durell, Sarah; Stayner, Barbara; Eeles, Ros; Shanley, Susan; Rahman, Nazneen; Houlston, Richard; Bancroft, Elizabeth; D'Mello, Lucia; Page, Elizabeth; Ardern-Jones, Audrey; Kohut, Kelly; Wiggins, Jennifer; Castro, Elena; Mitra, Anitra; Robertson, Lisa; Cook, Jackie; Quarrell, Oliver; Bardsley, Cathryn; Hodgson, Shirley; Goff, Sheila; Brice, Glen; Winchester, Lizzie; Eddy, Charlotte; Tripathi, Vishakha; Attard, Virginia; Eccles, Diana; Lucassen, Anneke; Crawford, Gillian; McBride, Donna; Smalley, Sarah; Godwin, A. K.; Karlsson, Per; Nordling, Margareta; Bergman, Annika; Einbeigi, Zakaria; Stenmark- Askmalm, Marie; Liedgren, Sigrun; Borg, Ake; Loman, Niklas; Olsson, Håkan; Kristoffersson, Ulf; Jernström, Helena; Harbst, Katja; Henriksson, Karin; Lindblom, Annika; Arver, Brita; Wachenfeldt, Anna von; Liljegren, Annelie; Barbany-Bustinza, Gisela; Rantala, Johanna; Melin, Beatrice; Grönberg, Henrik; Stattin, Eva-Lena; Emanuelsson, Monica; Ehrencrona, Hans; Rosenquist Brandell, Richard; Dahl, Niklas

    2011-01-01

    Single-nucleotide polymorphisms (SNPs) in genes involved in DNA repair are good candidates to be tested as phenotypic modifiers for carriers of mutations in the high-risk susceptibility genes BRCA1 and BRCA2. The base excision repair (BER) pathway could be particularly interesting given the relation

  8. Using Ontologies in Cybersecurity Field

    Directory of Open Access Journals (Sweden)

    Tiberiu Marian GEORGESCU

    2017-01-01

    Full Text Available This paper is an exploratory research which aims to improve the cybersecurity field by means of semantic web technologies. The authors present a framework which uses Semantic Web technologies to automatically extract and analyse text in natural language available online. The system provides results that are further analysed by cybersecurity experts to detect black hat hackers’ activities. The authors examine several characteristics of how hacking communities communicate and collaborate online and how much information can be obtained by analysing different types of internet text communication channels. Having online sources as input data, the model proposed extracts and analyses natural language that relates with cybersecurity field, with the aid of ontologies. The main objective is to generate information about possible black hat hacking actions, which later can be analysed punctually by experts. This paper describes the data flow of the framework and it proposes technological solutions so that the model can be applied. In their future work, the authors plan to implement the framework described as a system software application.

  9. The bioleaching potential of a bacterial consortium.

    Science.gov (United States)

    Latorre, Mauricio; Cortés, María Paz; Travisany, Dante; Di Genova, Alex; Budinich, Marko; Reyes-Jara, Angélica; Hödar, Christian; González, Mauricio; Parada, Pilar; Bobadilla-Fazzini, Roberto A; Cambiazo, Verónica; Maass, Alejandro

    2016-10-01

    This work presents the molecular foundation of a consortium of five efficient bacteria strains isolated from copper mines currently used in state of the art industrial-scale biotechnology. The strains Acidithiobacillus thiooxidans Licanantay, Acidiphilium multivorum Yenapatur, Leptospirillum ferriphilum Pañiwe, Acidithiobacillus ferrooxidans Wenelen and Sulfobacillus thermosulfidooxidans Cutipay were selected for genome sequencing based on metal tolerance, oxidation activity and bioleaching of copper efficiency. An integrated model of metabolic pathways representing the bioleaching capability of this consortium was generated. Results revealed that greater efficiency in copper recovery may be explained by the higher functional potential of L. ferriphilum Pañiwe and At. thiooxidans Licanantay to oxidize iron and reduced inorganic sulfur compounds. The consortium had a greater capacity to resist copper, arsenic and chloride ion compared to previously described biomining strains. Specialization and particular components in these bacteria provided the consortium a greater ability to bioleach copper sulfide ores. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Update on the US Government's Biometric Consortium

    National Research Council Canada - National Science Library

    Campbell, Joseph

    1997-01-01

    .... The goals of the consortium remain largely the same under this new leadership. The current emphasis is on the formal approval of our charter and on the establishment of a national biometric test and evaluation laboratory.

  11. NASA space radiation transport code development consortium

    International Nuclear Information System (INIS)

    Townsend, L. W.

    2005-01-01

    Recently, NASA established a consortium involving the Univ. of Tennessee (lead institution), the Univ. of Houston, Roanoke College and various government and national laboratories, to accelerate the development of a standard set of radiation transport computer codes for NASA human exploration applications. This effort involves further improvements of the Monte Carlo codes HETC and FLUKA and the deterministic code HZETRN, including developing nuclear reaction databases necessary to extend the Monte Carlo codes to carry out heavy ion transport, and extending HZETRN to three dimensions. The improved codes will be validated by comparing predictions with measured laboratory transport data, provided by an experimental measurements consortium, and measurements in the upper atmosphere on the balloon-borne Deep Space Test Bed (DSTB). In this paper, we present an overview of the consortium members and the current status and future plans of consortium efforts to meet the research goals and objectives of this extensive undertaking. (authors)

  12. The LBNL/JSU/AGMUS Science Consortium

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-04-01

    This report discusses the 11 year of accomplishments of the science consortium of minority graduates from Jackson State University and Ana G. Mendez University at the Lawrence Berkeley National Laboratory.

  13. International Radical Cystectomy Consortium: A way forward

    Directory of Open Access Journals (Sweden)

    Syed Johar Raza

    2014-01-01

    Full Text Available Robot-assisted radical cystectomy (RARC is an emerging operative alternative to open surgery for the management of invasive bladder cancer. Studies from single institutions provide limited data due to the small number of patients. In order to better understand the related outcomes, a world-wide consortium was established in 2006 of patients undergoing RARC, called the International Robotic Cystectomy Consortium (IRCC. Thus far, the IRCC has reported its findings on various areas of operative interest and continues to expand its capacity to include other operative modalities and transform it into the International Radical Cystectomy Consortium. This article summarizes the findings of the IRCC and highlights the future direction of the consortium.

  14. International Lymphoma Epidemiology Consortium (InterLymph)

    Science.gov (United States)

    A consortium designed to enhance collaboration among epidemiologists studying lymphoma, to provide a forum for the exchange of research ideas, and to create a framework for collaborating on analyses that pool data from multiple studies

  15. ONTOGRABBING: Extracting Information from Texts Using Generative Ontologies

    DEFF Research Database (Denmark)

    Nilsson, Jørgen Fischer; Szymczak, Bartlomiej Antoni; Jensen, P.A.

    2009-01-01

    We describe principles for extracting information from texts using a so-called generative ontology in combination with syntactic analysis. Generative ontologies are introduced as semantic domains for natural language phrases. Generative ontologies extend ordinary finite ontologies with rules...... for producing recursively shaped terms representing the ontological content (ontological semantics) of NL noun phrases and other phrases. We focus here on achieving a robust, often only partial, ontology-driven parsing of and ascription of semantics to a sentence in the text corpus. The aim of the ontological...... analysis is primarily to identify paraphrases, thereby achieving a search functionality beyond mere keyword search with synsets. We further envisage use of the generative ontology as a phrase-based rather than word-based browser into text corpora....

  16. Ontology Mapping Neural Network: An Approach to Learning and Inferring Correspondences among Ontologies

    Science.gov (United States)

    Peng, Yefei

    2010-01-01

    An ontology mapping neural network (OMNN) is proposed in order to learn and infer correspondences among ontologies. It extends the Identical Elements Neural Network (IENN)'s ability to represent and map complex relationships. The learning dynamics of simultaneous (interlaced) training of similar tasks interact at the shared connections of the…

  17. OIntEd: online ontology instance editor enabling a new approach to ontology development

    NARCIS (Netherlands)

    Wibisono, A.; Koning, R.; Grosso, P.; Belloum, A.; Bubak, M.; de Laat, C.

    2013-01-01

    Ontology development involves people with different background knowledge and expertise. It is an elaborate process, where sophisticated tools for experienced knowledge engineers are available. However, domain experts need simple tools that they can use to focus on ontology instantiation. In this

  18. Using an ontology pattern stack to engineer a core ontology of Accounting Information Systems

    NARCIS (Netherlands)

    Blums, Ivar; Weigand, Hans

    Although the field of Accounting Information Systems (AIS) has a long tradition, there is still a lack of a widely adopted conceptualization. In this paper, The UFO ontology patterns are regarded for application by analogy and extension in the engineering of a core ontology for AIS. The new IASB

  19. An Ontology-Based GIS for Genomic Data Management of Rumen Microbes.

    Science.gov (United States)

    Jelokhani-Niaraki, Saber; Tahmoorespur, Mojtaba; Minuchehr, Zarrin; Nassiri, Mohammad Reza

    2015-03-01

    During recent years, there has been exponential growth in biological information. With the emergence of large datasets in biology, life scientists are encountering bottlenecks in handling the biological data. This study presents an integrated geographic information system (GIS)-ontology application for handling microbial genome data. The application uses a linear referencing technique as one of the GIS functionalities to represent genes as linear events on the genome layer, where users can define/change the attributes of genes in an event table and interactively see the gene events on a genome layer. Our application adopted ontology to portray and store genomic data in a semantic framework, which facilitates data-sharing among biology domains, applications, and experts. The application was developed in two steps. In the first step, the genome annotated data were prepared and stored in a MySQL database. The second step involved the connection of the database to both ArcGIS and Protégé as the GIS engine and ontology platform, respectively. We have designed this application specifically to manage the genome-annotated data of rumen microbial populations. Such a GIS-ontology application offers powerful capabilities for visualizing, managing, reusing, sharing, and querying genome-related data.

  20. An Ontology-Based GIS for Genomic Data Management of Rumen Microbes

    Directory of Open Access Journals (Sweden)

    Saber Jelokhani-Niaraki

    2015-03-01

    Full Text Available During recent years, there has been exponential growth in biological information. With the emergence of large datasets in biology, life scientists are encountering bottlenecks in handling the biological data. This study presents an integrated geographic information system (GIS-ontology application for handling microbial genome data. The application uses a linear referencing technique as one of the GIS functionalities to represent genes as linear events on the genome layer, where users can define/change the attributes of genes in an event table and interactively see the gene events on a genome layer. Our application adopted ontology to portray and store genomic data in a semantic framework, which facilitates data-sharing among biology domains, applications, and experts. The application was developed in two steps. In the first step, the genome annotated data were prepared and stored in a MySQL database. The second step involved the connection of the database to both ArcGIS and Protégé as the GIS engine and ontology platform, respectively. We have designed this application specifically to manage the genome-annotated data of rumen microbial populations. Such a GIS-ontology application offers powerful capabilities for visualizing, managing, reusing, sharing, and querying genome-related data.

  1. Documenting the emergence of bio-ontologies: or, why researching bioinformatics requires HPSSB.

    Science.gov (United States)

    Leonelli, Sabina

    2010-01-01

    This paper reflects on the analytic challenges emerging from the study of bioinformatic tools recently created to store and disseminate biological data, such as databases, repositories, and bio-ontologies. I focus my discussion on the Gene Ontology, a term that defines three entities at once: a classification system facilitating the distribution and use of genomic data as evidence towards new insights; an expert community specialised in the curation of those data; and a scientific institution promoting the use of this tool among experimental biologists. These three dimensions of the Gene Ontology can be clearly distinguished analytically, but are tightly intertwined in practice. I suggest that this is true of all bioinformatic tools: they need to be understood simultaneously as epistemic, social, and institutional entities, since they shape the knowledge extracted from data and at the same time regulate the organisation, development, and communication of research. This viewpoint has one important implication for the methodologies used to study these tools; that is, the need to integrate historical, philosophical, and sociological approaches. I illustrate this claim through examples of misunderstandings that may result from a narrowly disciplinary study of the Gene Ontology, as I experienced them in my own research.

  2. An Ontology-Based GIS for Genomic Data Management of Rumen Microbes

    Science.gov (United States)

    Jelokhani-Niaraki, Saber; Minuchehr, Zarrin; Nassiri, Mohammad Reza

    2015-01-01

    During recent years, there has been exponential growth in biological information. With the emergence of large datasets in biology, life scientists are encountering bottlenecks in handling the biological data. This study presents an integrated geographic information system (GIS)-ontology application for handling microbial genome data. The application uses a linear referencing technique as one of the GIS functionalities to represent genes as linear events on the genome layer, where users can define/change the attributes of genes in an event table and interactively see the gene events on a genome layer. Our application adopted ontology to portray and store genomic data in a semantic framework, which facilitates data-sharing among biology domains, applications, and experts. The application was developed in two steps. In the first step, the genome annotated data were prepared and stored in a MySQL database. The second step involved the connection of the database to both ArcGIS and Protégé as the GIS engine and ontology platform, respectively. We have designed this application specifically to manage the genome-annotated data of rumen microbial populations. Such a GIS-ontology application offers powerful capabilities for visualizing, managing, reusing, sharing, and querying genome-related data. PMID:25873847

  3. Bacterial community composition characterization of a lead-contaminated Microcoleus sp. consortium.

    Science.gov (United States)

    Giloteaux, Ludovic; Solé, Antoni; Esteve, Isabel; Duran, Robert

    2011-08-01

    A Microcoleus sp. consortium, obtained from the Ebro delta microbial mat, was maintained under different conditions including uncontaminated, lead-contaminated, and acidic conditions. Terminal restriction fragment length polymorphism and 16S rRNA gene library analyses were performed in order to determine the effect of lead and culture conditions on the Microcoleus sp. consortium. The bacterial composition inside the consortium revealed low diversity and the presence of specific terminal-restriction fragments under lead conditions. 16S rRNA gene library analyses showed that members of the consortium were affiliated to the Alpha, Beta, and Gammaproteobacteria and Cyanobacteria. Sequences closely related to Achromobacter spp., Alcaligenes faecalis, and Thiobacillus species were exclusively found under lead conditions while sequences related to Geitlerinema sp., a cyanobacterium belonging to the Oscillatoriales, were not found in presence of lead. This result showed a strong lead selection of the bacterial members present in the Microcoleus sp. consortium. Several of the 16S rRNA sequences were affiliated to nitrogen-fixing microorganisms including members of the Rhizobiaceae and the Sphingomonadaceae. Additionally, confocal laser scanning microscopy and scanning and transmission electron microscopy showed that under lead-contaminated condition Microcoleus sp. cells were grouped and the number of electrodense intracytoplasmic inclusions was increased.

  4. The Cognitive Paradigm Ontology: Design and Application

    Science.gov (United States)

    Laird, Angela R.

    2013-01-01

    We present the basic structure of the Cognitive Paradigm Ontology (CogPO) for human behavioral experiments. While the experimental psychology and cognitive neuroscience literature may refer to certain behavioral tasks by name (e.g., the Stroop paradigm or the Sternberg paradigm) or by function (a working memory task, a visual attention task), these paradigms can vary tremendously in the stimuli that are presented to the subject, the response expected from the subject, and the instructions given to the subject. Drawing from the taxonomy developed and used by the BrainMap project (www.brainmap.org) for almost two decades to describe key components of published functional imaging results, we have developed an ontology capable of representing certain characteristics of the cognitive paradigms used in the fMRI and PET literature. The Cognitive Paradigm Ontology is being developed to be compliant with the Basic Formal Ontology (BFO), and to harmonize where possible with larger ontologies such as RadLex, NeuroLex, or the Ontology of Biomedical Investigations (OBI). The key components of CogPO include the representation of experimental conditions focused on the stimuli presented, the instructions given, and the responses requested. The use of alternate and even competitive terminologies can often impede scientific discoveries. Categorization of paradigms according to stimulus, response, and instruction has been shown to allow advanced data retrieval techniques by searching for similarities and contrasts across multiple paradigm levels. The goal of CogPO is to develop, evaluate, and distribute a domain ontology of cognitive paradigms for application and use in the functional neuroimaging community. PMID:21643732

  5. GFVO: the Genomic Feature and Variation Ontology

    KAUST Repository

    Baran, Joachim

    2015-05-05

    Falling costs in genomic laboratory experiments have led to a steady increase of genomic feature and variation data. Multiple genomic data formats exist for sharing these data, and whilst they are similar, they are addressing slightly different data viewpoints and are consequently not fully compatible with each other. The fragmentation of data format specifications makes it hard to integrate and interpret data for further analysis with information from multiple data providers. As a solution, a new ontology is presented here for annotating and representing genomic feature and variation dataset contents. The Genomic Feature and Variation Ontology (GFVO) specifically addresses genomic data as it is regularly shared using the GFF3 (incl. FASTA), GTF, GVF and VCF file formats. GFVO simplifies data integration and enables linking of genomic annotations across datasets through common semantics of genomic types and relations. Availability and implementation. The latest stable release of the ontology is available via its base URI; previous and development versions are available at the ontology’s GitHub repository: https://github.com/BioInterchange/Ontologies; versions of the ontology are indexed through BioPortal (without external class-/property-equivalences due to BioPortal release 4.10 limitations); examples and reference documentation is provided on a separate web-page: http://www.biointerchange.org/ontologies.html. GFVO version 1.0.2 is licensed under the CC0 1.0 Universal license (https://creativecommons.org/publicdomain/zero/1.0) and therefore de facto within the public domain; the ontology can be appropriated without attribution for commercial and non-commercial use.

  6. Process attributes in bio-ontologies

    Directory of Open Access Journals (Sweden)

    Andrade André Q

    2012-08-01

    Full Text Available Abstract Background Biomedical processes can provide essential information about the (mal- functioning of an organism and are thus frequently represented in biomedical terminologies and ontologies, including the GO Biological Process branch. These processes often need to be described and categorised in terms of their attributes, such as rates or regularities. The adequate representation of such process attributes has been a contentious issue in bio-ontologies recently; and domain ontologies have correspondingly developed ad hoc workarounds that compromise interoperability and logical consistency. Results We present a design pattern for the representation of process attributes that is compatible with upper ontology frameworks such as BFO and BioTop. Our solution rests on two key tenets: firstly, that many of the sorts of process attributes which are biomedically interesting can be characterised by the ways that repeated parts of such processes constitute, in combination, an overall process; secondly, that entities for which a full logical definition can be assigned do not need to be treated as primitive within a formal ontology framework. We apply this approach to the challenge of modelling and automatically classifying examples of normal and abnormal rates and patterns of heart beating processes, and discuss the expressivity required in the underlying ontology representation language. We provide full definitions for process attributes at increasing levels of domain complexity. Conclusions We show that a logical definition of process attributes is feasible, though limited by the expressivity of DL languages so that the creation of primitives is still necessary. This finding may endorse current formal upper-ontology frameworks as a way of ensuring consistency, interoperability and clarity.

  7. Application of Ontologies for Big Earth Data

    Science.gov (United States)

    Huang, T.; Chang, G.; Armstrong, E. M.; Boening, C.

    2014-12-01

    Connected data is smarter data! Earth Science research infrastructure must do more than just being able to support temporal, geospatial discovery of satellite data. As the Earth Science data archives continue to expand across NASA data centers, the research communities are demanding smarter data services. A successful research infrastructure must be able to present researchers the complete picture, that is, datasets with linked citations, related interdisciplinary data, imageries, current events, social media discussions, and scientific data tools that are relevant to the particular dataset. The popular Semantic Web for Earth and Environmental Terminology (SWEET) ontologies is a collection of ontologies and concepts designed to improve discovery and application of Earth Science data. The SWEET ontologies collection was initially developed to capture the relationships between keywords in the NASA Global Change Master Directory (GCMD). Over the years this popular ontologies collection has expanded to cover over 200 ontologies and 6000 concepts to enable scalable classification of Earth system science concepts and Space science. This presentation discusses the semantic web technologies as the enabling technology for data-intensive science. We will discuss the application of the SWEET ontologies as a critical component in knowledge-driven research infrastructure for some of the recent projects, which include the DARPA Ontological System for Context Artifact and Resources (OSCAR), 2013 NASA ACCESS Virtual Quality Screening Service (VQSS), and the 2013 NASA Sea Level Change Portal (SLCP) projects. The presentation will also discuss the benefits in using semantic web technologies in developing research infrastructure for Big Earth Science Data in an attempt to "accommodate all domains and provide the necessary glue for information to be cross-linked, correlated, and discovered in a semantically rich manner." [1] [1] Savas Parastatidis: A platform for all that we know

  8. Ion Channel ElectroPhysiology Ontology (ICEPO) - a case study of text mining assisted ontology development.

    Science.gov (United States)

    Elayavilli, Ravikumar Komandur; Liu, Hongfang

    2016-01-01

    Computational modeling of biological cascades is of great interest to quantitative biologists. Biomedical text has been a rich source for quantitative information. Gathering quantitative parameters and values from biomedical text is one significant challenge in the early steps of computational modeling as it involves huge manual effort. While automatically extracting such quantitative information from bio-medical text may offer some relief, lack of ontological representation for a subdomain serves as impedance in normalizing textual extractions to a standard representation. This may render textual extractions less meaningful to the domain experts. In this work, we propose a rule-based approach to automatically extract relations involving quantitative data from biomedical text describing ion channel electrophysiology. We further translated the quantitative assertions extracted through text mining to a formal representation that may help in constructing ontology for ion channel events using a rule based approach. We have developed Ion Channel ElectroPhysiology Ontology (ICEPO) by integrating the information represented in closely related ontologies such as, Cell Physiology Ontology (CPO), and Cardiac Electro Physiology Ontology (CPEO) and the knowledge provided by domain experts. The rule-based system achieved an overall F-measure of 68.93% in extracting the quantitative data assertions system on an independently annotated blind data set. We further made an initial attempt in formalizing the quantitative data assertions extracted from the biomedical text into a formal representation that offers potential to facilitate the integration of text mining into ontological workflow, a novel aspect of this study. This work is a case study where we created a platform that provides formal interaction between ontology development and text mining. We have achieved partial success in extracting quantitative assertions from the biomedical text and formalizing them in ontological

  9. Leave-two-out stability of ontology learning algorithm

    International Nuclear Information System (INIS)

    Wu, Jianzhang; Yu, Xiao; Zhu, Linli; Gao, Wei

    2016-01-01

    Ontology is a semantic analysis and calculation model, which has been applied to many subjects. Ontology similarity calculation and ontology mapping are employed as machine learning approaches. The purpose of this paper is to study the leave-two-out stability of ontology learning algorithm. Several leave-two-out stabilities are defined in ontology learning setting and the relationship among these stabilities are presented. Furthermore, the results manifested reveal that leave-two-out stability is a sufficient and necessary condition for ontology learning algorithm.

  10. Product line based ontology development for semantic web service

    DEFF Research Database (Denmark)

    Zhang, Weishan; Kunz, Thomas

    2006-01-01

    Ontology is recognized as a key technology for the success of the Semantic Web. Building reusable and evolve-able ontologies in order to cope with ontology evolution and requirement changes is increasingly important. But the existing methodologies and tools fail to support effective ontology reuse...... will lead to the initial implementation of the meta-onotologies using design by reuse and with the objective of design for reuse. After that step new ontologies could be generated by reusing these meta-ontologies. We demonstrate our approach with a Semantic Web Service application to show how to build...

  11. A methodology for creating ontologies for engineering design

    DEFF Research Database (Denmark)

    Ahmed, Saeema; Kim, S.; Wallace, K.M.

    2007-01-01

    This paper describes a six-stage methodology for developing ontologies for engineering design, together with the research methods and evaluation of each stage. The methodology focuses upon understanding a user's domain models through empirical research. A case study of an ontology for searching......, indexing, and retrieving engineering knowledge is described. The root concepts of the ontology were elicited from engineering designers. Relationships between concepts are extracted as the ontology is populated. The contribution of this research is a methodology to allow researchers. and industry to create...... ontologies for their particular purpose and a thesaurus for the terms within the ontology....

  12. Integrating systems biology models and biomedical ontologies.

    Science.gov (United States)

    Hoehndorf, Robert; Dumontier, Michel; Gennari, John H; Wimalaratne, Sarala; de Bono, Bernard; Cook, Daniel L; Gkoutos, Georgios V

    2011-08-11

    Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology. We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models. We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms.

  13. Validating EHR clinical models using ontology patterns.

    Science.gov (United States)

    Martínez-Costa, Catalina; Schulz, Stefan

    2017-12-01

    Clinical models are artefacts that specify how information is structured in electronic health records (EHRs). However, the makeup of clinical models is not guided by any formal constraint beyond a semantically vague information model. We address this gap by advocating ontology design patterns as a mechanism that makes the semantics of clinical models explicit. This paper demonstrates how ontology design patterns can validate existing clinical models using SHACL. Based on the Clinical Information Modelling Initiative (CIMI), we show how ontology patterns detect both modeling and terminology binding errors in CIMI models. SHACL, a W3C constraint language for the validation of RDF graphs, builds on the concept of "Shape", a description of data in terms of expected cardinalities, datatypes and other restrictions. SHACL, as opposed to OWL, subscribes to the Closed World Assumption (CWA) and is therefore more suitable for the validation of clinical models. We have demonstrated the feasibility of the approach by manually describing the correspondences between six CIMI clinical models represented in RDF and two SHACL ontology design patterns. Using a Java-based SHACL implementation, we found at least eleven modeling and binding errors within these CIMI models. This demonstrates the usefulness of ontology design patterns not only as a modeling tool but also as a tool for validation. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Multiple Syntrophic Interactions in a Terephthalate-Degrading Methanogenic Consortium

    Energy Technology Data Exchange (ETDEWEB)

    Lykidis, Athanasios; Chen, Chia-Lung; Tringe, Susannah G.; McHardy, Alice C.; Copeland, Alex 5; Kyrpides, Nikos C.; Hugenholtz, Philip; Liu, Wen-Tso

    2010-08-05

    Terephthalate (TA) is one of the top 50 chemicals produced worldwide. Its production results in a TA-containing wastewater that is treated by anaerobic processes through a poorly understood methanogenic syntrophy. Using metagenomics, we characterized the methanogenic consortium tinside a hyper-mesophilic (i.e., between mesophilic and thermophilic), TA-degrading bioreactor. We identified genes belonging to dominant Pelotomaculum species presumably involved in TA degradation through decarboxylation, dearomatization, and modified ?-oxidation to H{sub 2}/CO{sub 2} and acetate. These intermediates are converted to CH{sub 4}/CO{sub 2} by three novel hyper-mesophilic methanogens. Additional secondary syntrophic interactions were predicted in Thermotogae, Syntrophus and candidate phyla OP5 and WWE1 populations. The OP5 encodes genes capable of anaerobic autotrophic butyrate production and Thermotogae, Syntrophus and WWE1 have the genetic potential to oxidize butyrate to COsub 2}/H{sub 2} and acetate. These observations suggest that the TA-degrading consortium consists of additional syntrophic interactions beyond the standard H{sub 2}-producing syntroph ? methanogen partnership that may serve to improve community stability.

  15. Fiscal 2000 regional consortium research and development project - regional new technology creation research and development. Development of micro-array for next generation gene analysis (1st fiscal year); 2000 nendo chiiki consortium kenkyu kaihatsu jigyo - chiiki shingijutsu soshutsu kenkyu kaihatsu seika hokokusho. Jisedai idenshi kaiseki micro array no kaihatsu (daiichi nendo)

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-03-01

    Efforts are under way to construct a novel DNA (deoxyribonucleic acid) micro-array for gene diagnosis on the basis of technologies of laser scan type manipulation, nanometric position detection, and micro-machining. Using these technologies, structural changes to accompany reactions induced in the probe DNA deposited on an array are detected for the identification of the DNA. Activities are conducted in the four fields of (1) the study of probe DNA fixation technology, (2) development of an optical detection system, (3) detailed check of DNA micro-array performance evaluation technologies, and (4) a comprehensive survey. In field (1), gold colloid modified DNA molecules are designed and evaluated, and the fixation of DNA to substrates and technologies for integration are studied. In field (2), the gold colloid modified DNA is fixed on a thin gold film, and then a surface plasmon resonance (SPR) is observed in the wake of hybridization. Furthermore, a Brownian motion is observed of the metal particles fixed on a glass substrate via DNA. (NEDO)

  16. Toward a formal ontology for narrative

    Directory of Open Access Journals (Sweden)

    Ciotti, Fabio

    2016-03-01

    Full Text Available In this paper the rationale and the first draft of a formal ontology for modeling narrative texts are presented. Building on the semiotic and structuralist narratology, and on the work carried out in the late 1980s by Giuseppe Gigliozzi in Italy, the focus of my research are the concepts of character and of narrative world/space. This formal model is expressed in the OWL 2 ontology language. The main reason to adopt a formal modeling approach is that I consider the purely probabilistic-quantitative methods (now widespread in digital literary studies inadequate. An ontology, on one hand provides a tool for the analysis of strictly literary texts. On the other hand (though beyond the scope of the present work, its formalization can also represent a significant contribution towards grounding the application of storytelling methods outside of scholarly contexts.

  17. A Formal Theory for Modular ERDF Ontologies

    Science.gov (United States)

    Analyti, Anastasia; Antoniou, Grigoris; Damásio, Carlos Viegas

    The success of the Semantic Web is impossible without any form of modularity, encapsulation, and access control. In an earlier paper, we extended RDF graphs with weak and strong negation, as well as derivation rules. The ERDF #n-stable model semantics of the extended RDF framework (ERDF) is defined, extending RDF(S) semantics. In this paper, we propose a framework for modular ERDF ontologies, called modular ERDF framework, which enables collaborative reasoning over a set of ERDF ontologies, while support for hidden knowledge is also provided. In particular, the modular ERDF stable model semantics of modular ERDF ontologies is defined, extending the ERDF #n-stable model semantics. Our proposed framework supports local semantics and different points of view, local closed-world and open-world assumptions, and scoped negation-as-failure. Several complexity results are provided.

  18. The Russian Quest for Ontological Security

    DEFF Research Database (Denmark)

    Pedersen, Jonas Gejl

    This paper argues that Russia’s decision to militarily intervene in the Kosovo crisis (1999) arose out of ontological, alongside material, insecurity. Whereas states’ material security essentially deals with national survival, ontological security concerns safety of the ‘national Self......’. By supplementing the existing theories of geopolitics and regime security with the conceptual lens of ontological security, my interpretivist case study demonstrates why Russia, despite great risk and material costs, decided to militarily intervene and traces how Russian senses of ‘national Self’ were...... fundamentally reconstructed during intervention. I find that the anxiety arising from a future scenario of an already weak post-Soviet ‘Russian Self’ gradually being engulfed by a confident ‘Western Self’ played a significant role in Russia’s decision to occupy Slatina airbase. My analysis paradoxically shows...

  19. Løgstrup’s Ontological Ethics

    DEFF Research Database (Denmark)

    Rabjerg, Bjørn

    2017-01-01

    aim is to provide a coherent exposition of Løgstrup’s ethics. However, the result is not a normative ethics upon which we may act, but rather a descriptive diagnosis of interdependence as the basic ontological condition of human social life, where the sovereign expressions of life may enable us to act.......The article explores K. E. Løgstrup’s ontological ethics, understood as an ethics rooted in interdependence. Interdependence, the fact that human beings always hold power over each other, has two very different aspects, which I will call negative and positive, each of them in turn leading...... to different aspects of ontological ethics. By negative and positive I mean the two opposing possibilities of all human interaction that we can either destroy the other person’s life (to a greater or smaller degree) or cause the other person’s life to flourish. We can either be a blessing in the other person’s...

  20. Designing Network-based Business Model Ontology

    DEFF Research Database (Denmark)

    Hashemi Nekoo, Ali Reza; Ashourizadeh, Shayegheh; Zarei, Behrouz

    2015-01-01

    Survival on dynamic environment is not achieved without a map. Scanning and monitoring of the market show business models as a fruitful tool. But scholars believe that old-fashioned business models are dead; as they are not included the effect of internet and network in themselves. This paper...... is going to propose e-business model ontology from the network point of view and its application in real world. The suggested ontology for network-based businesses is composed of individuals` characteristics and what kind of resources they own. also, their connections and pre-conceptions of connections...... such as shared-mental model and trust. However, it mostly covers previous business model elements. To confirm the applicability of this ontology, it has been implemented in business angel network and showed how it works....

  1. Player-Specific Conflict Handling Ontology

    Directory of Open Access Journals (Sweden)

    Charline Hondrou

    2014-09-01

    Full Text Available This paper presents an ontology that leads the player of a serious game - regarding conflict handling - to the educative experience from which they will benefit the most. It provides a clearly defined tree of axioms that maps the player’s visually manifested affective cues and emotional stimuli from the serious game to conflict handling styles and proposes interventions. The importance of this ontology lies in the fact that it promotes natural interaction (non-invasive methods and at the same time makes the game as player-specific as it can be for its educational goal. It is an ontology that can be adapted to different educational theories and serve various educational purposes.

  2. Using ontology network structure in text mining.

    Science.gov (United States)

    Berndt, Donald J; McCart, James A; Luther, Stephen L

    2010-11-13

    Statistical text mining treats documents as bags of words, with a focus on term frequencies within documents and across document collections. Unlike natural language processing (NLP) techniques that rely on an engineered vocabulary or a full-featured ontology, statistical approaches do not make use of domain-specific knowledge. The freedom from biases can be an advantage, but at the cost of ignoring potentially valuable knowledge. The approach proposed here investigates a hybrid strategy based on computing graph measures of term importance over an entire ontology and injecting the measures into the statistical text mining process. As a starting point, we adapt existing search engine algorithms such as PageRank and HITS to determine term importance within an ontology graph. The graph-theoretic approach is evaluated using a smoking data set from the i2b2 National Center for Biomedical Computing, cast as a simple binary classification task for categorizing smoking-related documents, demonstrating consistent improvements in accuracy.

  3. The Porifera Ontology (PORO): enhancing sponge systematics with an anatomy ontology.

    Science.gov (United States)

    Thacker, Robert W; Díaz, Maria Cristina; Kerner, Adeline; Vignes-Lebbe, Régine; Segerdell, Erik; Haendel, Melissa A; Mungall, Christopher J

    2014-01-01

    Porifera (sponges) are ancient basal metazoans that lack organs. They provide insight into key evolutionary transitions, such as the emergence of multicellularity and the nervous system. In addition, their ability to synthesize unusual compounds offers potential biotechnical applications. However, much of the knowledge of these organisms has not previously been codified in a machine-readable way using modern web standards. The Porifera Ontology is intended as a standardized coding system for sponge anatomical features currently used in systematics. The ontology is available from http://purl.obolibrary.org/obo/poro.owl, or from the project homepage http://porifera-ontology.googlecode.com/. The version referred to in this manuscript is permanently available from http://purl.obolibrary.org/obo/poro/releases/2014-03-06/. By standardizing character representations, we hope to facilitate more rapid description and identification of sponge taxa, to allow integration with other evolutionary database systems, and to perform character mapping across the major clades of sponges to better understand the evolution of morphological features. Future applications of the ontology will focus on creating (1) ontology-based species descriptions; (2) taxonomic keys that use the nested terms of the ontology to more quickly facilitate species identifications; and (3) methods to map anatomical characters onto molecular phylogenies of sponges. In addition to modern taxa, the ontology is being extended to include features of fossil taxa.

  4. Matching disease and phenotype ontologies in the ontology alignment evaluation initiative.

    Science.gov (United States)

    Harrow, Ian; Jiménez-Ruiz, Ernesto; Splendiani, Andrea; Romacker, Martin; Woollard, Peter; Markel, Scott; Alam-Faruque, Yasmin; Koch, Martin; Malone, James; Waaler, Arild

    2017-12-02

    The disease and phenotype track was designed to evaluate the relative performance of ontology matching systems that generate mappings between source ontologies. Disease and phenotype ontologies are important for applications such as data mining, data integration and knowledge management to support translational science in drug discovery and understanding the genetics of disease. Eleven systems (out of 21 OAEI participating systems) were able to cope with at least one of the tasks in the Disease and Phenotype track. AML, FCA-Map, LogMap(Bio) and PhenoMF systems produced the top results for ontology matching in comparison to consensus alignments. The results against manually curated mappings proved to be more difficult most likely because these mapping sets comprised mostly subsumption relationships rather than equivalence. Manual assessment of unique equivalence mappings showed that AML, LogMap(Bio) and PhenoMF systems have the highest precision results. Four systems gave the highest performance for matching disease and phenotype ontologies. These systems coped well with the detection of equivalence matches, but struggled to detect semantic similarity. This deserves more attention in the future development of ontology matching systems. The findings of this evaluation show that such systems could help to automate equivalence matching in the workflow of curators, who maintain ontology mapping services in numerous domains such as disease and phenotype.

  5. Validating genetic risk associations for ovarian cancer through the international Ovarian Cancer Association Consortium

    DEFF Research Database (Denmark)

    Pearce, C L; Near, A M; Van Den Berg, D J

    2009-01-01

    The search for genetic variants associated with ovarian cancer risk has focused on pathways including sex steroid hormones, DNA repair, and cell cycle control. The Ovarian Cancer Association Consortium (OCAC) identified 10 single-nucleotide polymorphisms (SNPs) in genes in these pathways, which had...... been genotyped by Consortium members and a pooled analysis of these data was conducted. Three of the 10 SNPs showed evidence of an association with ovarian cancer at P... and risk of ovarian cancer suggests that this pathway may be involved in ovarian carcinogenesis. Additional follow-up is warranted....

  6. MicrO: an ontology of phenotypic and metabolic characters, assays, and culture media found in prokaryotic taxonomic descriptions.

    Science.gov (United States)

    Blank, Carrine E; Cui, Hong; Moore, Lisa R; Walls, Ramona L

    2016-01-01

    MicrO is an ontology of microbiological terms, including prokaryotic qualities and processes, material entities (such as cell components), chemical entities (such as microbiological culture media and medium ingredients), and assays. The ontology was built to support the ongoing development of a natural language processing algorithm, MicroPIE (or, Microbial Phenomics Information Extractor). During the MicroPIE design process, we realized there was a need for a prokaryotic ontology which would capture the evolutionary diversity of phenotypes and metabolic processes across the tree of life, capture the diversity of synonyms and information contained in the taxonomic literature, and relate microbiological entities and processes to terms in a large number of other ontologies, most particularly the Gene Ontology (GO), the Phenotypic Quality Ontology (PATO), and the Chemical Entities of Biological Interest (ChEBI). We thus constructed MicrO to be rich in logical axioms and synonyms gathered from the taxonomic literature. MicrO currently has ~14550 classes (~2550 of which are new, the remainder being microbiologically-relevant classes imported from other ontologies), connected by ~24,130 logical axioms (5,446 of which are new), and is available at (http://purl.obolibrary.org/obo/MicrO.owl) and on the project website at https://github.com/carrineblank/MicrO. MicrO has been integrated into the OBO Foundry Library (http://www.obofoundry.org/ontology/micro.html), so that other ontologies can borrow and re-use classes. Term requests and user feedback can be made using MicrO's Issue Tracker in GitHub. We designed MicrO such that it can support the ongoing and future development of algorithms that can leverage the controlled vocabulary and logical inference power provided by the ontology. By connecting microbial classes with large numbers of chemical entities, material entities, biological processes, molecular functions, and qualities using a dense array of logical axioms, we

  7. A meta-ontological framework for multi-agent systems design

    OpenAIRE

    Sokolova, Marina; Fernández Caballero, Antonio

    2007-01-01

    The paper introduces an approach to using a meta-ontology framework for complex multi-agent systems design, and illustrates it in an application related to ecological-medical issues. The described shared ontology is pooled from private sub-ontologies, which represent a problem area ontology, an agent ontology, a task ontology, an ontology of interactions, and the multi-agent system architecture ontology.

  8. OAE: The Ontology of Adverse Events.

    Science.gov (United States)

    He, Yongqun; Sarntivijai, Sirarat; Lin, Yu; Xiang, Zuoshuang; Guo, Abra; Zhang, Shelley; Jagannathan, Desikan; Toldo, Luca; Tao, Cui; Smith, Barry

    2014-01-01

    A medical intervention is a medical procedure or application intended to relieve or prevent illness or injury. Examples of medical interventions include vaccination and drug administration. After a medical intervention, adverse events (AEs) may occur which lie outside the intended consequences of the intervention. The representation and analysis of AEs are critical to the improvement of public health. The Ontology of Adverse Events (OAE), previously named Adverse Event Ontology (AEO), is a community-driven ontology developed to standardize and integrate data relating to AEs arising subsequent to medical interventions, as well as to support computer-assisted reasoning. OAE has over 3,000 terms with unique identifiers, including terms imported from existing ontologies and more than 1,800 OAE-specific terms. In OAE, the term 'adverse event' denotes a pathological bodily process in a patient that occurs after a medical intervention. Causal adverse events are defined by OAE as those events that are causal consequences of a medical intervention. OAE represents various adverse events based on patient anatomic regions and clinical outcomes, including symptoms, signs, and abnormal processes. OAE has been used in the analysis of several different sorts of vaccine and drug adverse event data. For example, using the data extracted from the Vaccine Adverse Event Reporting System (VAERS), OAE was used to analyse vaccine adverse events associated with the administrations of different types of influenza vaccines. OAE has also been used to represent and classify the vaccine adverse events cited in package inserts of FDA-licensed human vaccines in the USA. OAE is a biomedical ontology that logically defines and classifies various adverse events occurring after medical interventions. OAE has successfully been applied in several adverse event studies. The OAE ontological framework provides a platform for systematic representation and analysis of adverse events and of the factors (e

  9. Comprehensive Analysis of Hormone and Genetic Variation in 36 Genes Related to Steroid Hormone Metabolism in Pre- and Postmenopausal Women from the Breast and Prostate Cancer Cohort Consortium (BPC3)

    DEFF Research Database (Denmark)

    Beckmann, L.; Husing, A.; Setiawan, V. W.

    2011-01-01

    Context: Sex steroids play a central role in breast cancer development.Objective: This study aimed to relate polymorphic variants in 36 candidate genes in the sex steroid pathway to serum concentrations of sex steroid hormones and SHBG.Design: Data on 700 genetic polymorphisms were combined...

  10. HPV status, cancer stem cell marker expression, hypoxia gene signatures and tumour volume identify good prognosis subgroups in patients with HNSCC after primary radiochemotherapy: A multicentre retrospective study of the German Cancer Consortium Radiation Oncology Group (DKTK-ROG)

    DEFF Research Database (Denmark)

    Linge, Annett; Lohaus, Fabian; Löck, Steffen

    2016-01-01

    OBJECTIVE: To investigate the impact of the tumour volume, HPV status, cancer stem cell (CSC) marker expression and hypoxia gene signatures, as potential markers of radiobiological mechanisms of radioresistance, in a contemporary cohort of patients with locally advanced head and neck squamous cell...

  11. Ontology-based Metadata Portal for Unified Semantics

    Data.gov (United States)

    National Aeronautics and Space Administration — The Ontology-based Metadata Portal for Unified Semantics (OlyMPUS) will extend the prototype Ontology-Driven Interactive Search Environment for Earth Sciences...

  12. One Song, Many Works: A Pluralist Ontology of Rock

    Directory of Open Access Journals (Sweden)

    Dan Burkett

    2016-01-01

    Full Text Available A number of attempts have been made to construct a plausible ontology of rock music. Each of these ontologies identifies a single type of ontological entity as the “work” in rock music. Yet, all the suggestions advanced to date fail to capture some important considerations about how we engage with music of this tradition. This prompted Lee Brown to advocate a healthy skepticism of higher-order musical ontologies. I argue here that we should instead embrace a pluralist ontology of rock, an ontology that recognizes more than one kind of entity as “the work” in rock music. I contend that this approach has a number of advantages over other ontologies of rock, including that of allowing us to make some comparisons across ontological kinds.

  13. Prospects and Possibilities for Ontology Evaluation: The View from NCOR

    National Research Council Canada - National Science Library

    Obrst, Leo; Hughes, Todd; Ray, Steve

    2006-01-01

    ...) on ontology evaluation. NCOR's inauguration was recently held (October 2005), and at that time goals were identified and committees formed to pursue those goals, including the Ontology Evaluation Committee...

  14. Annotating Evidence Based Clinical Guidelines : A Lightweight Ontology

    NARCIS (Netherlands)

    Hoekstra, R.; de Waard, A.; Vdovjak, R.; Paschke, A.; Burger, A.; Romano, P.; Marshall, M.S.; Splendiani, A.

    2012-01-01

    This paper describes a lightweight ontology for representing annotations of declarative evidence based clinical guidelines. We present the motivation and requirements for this representation, based on an analysis of several guidelines. The ontology provides the means to connect clinical questions

  15. Semi-automated ontology generation and evolution

    Science.gov (United States)

    Stirtzinger, Anthony P.; Anken, Craig S.

    2009-05-01

    Extending the notion of data models or object models, ontology can provide rich semantic definition not only to the meta-data but also to the instance data of domain knowledge, making these semantic definitions available in machine readable form. However, the generation of an effective ontology is a difficult task involving considerable labor and skill. This paper discusses an Ontology Generation and Evolution Processor (OGEP) aimed at automating this process, only requesting user input when un-resolvable ambiguous situations occur. OGEP directly attacks the main barrier which prevents automated (or self learning) ontology generation: the ability to understand the meaning of artifacts and the relationships the artifacts have to the domain space. OGEP leverages existing lexical to ontological mappings in the form of WordNet, and Suggested Upper Merged Ontology (SUMO) integrated with a semantic pattern-based structure referred to as the Semantic Grounding Mechanism (SGM) and implemented as a Corpus Reasoner. The OGEP processing is initiated by a Corpus Parser performing a lexical analysis of the corpus, reading in a document (or corpus) and preparing it for processing by annotating words and phrases. After the Corpus Parser is done, the Corpus Reasoner uses the parts of speech output to determine the semantic meaning of a word or phrase. The Corpus Reasoner is the crux of the OGEP system, analyzing, extrapolating, and evolving data from free text into cohesive semantic relationships. The Semantic Grounding Mechanism provides a basis for identifying and mapping semantic relationships. By blending together the WordNet lexicon and SUMO ontological layout, the SGM is given breadth and depth in its ability to extrapolate semantic relationships between domain entities. The combination of all these components results in an innovative approach to user assisted semantic-based ontology generation. This paper will describe the OGEP technology in the context of the architectural

  16. Ontological Model of Business Process Management Systems

    Science.gov (United States)

    Manoilov, G.; Deliiska, B.

    2008-10-01

    The activities which constitute business process management (BPM) can be grouped into five categories: design, modeling, execution, monitoring and optimization. Dedicated software packets for business process management system (BPMS) are available on the market. But the efficiency of its exploitation depends on used ontological model in the development time and run time of the system. In the article an ontological model of BPMS in area of software industry is investigated. The model building is preceded by conceptualization of the domain and taxonomy of BPMS development. On the base of the taxonomy an simple online thesaurus is created.

  17. Methodology of decreasing software complexity using ontology

    Science.gov (United States)

    DÄ browska-Kubik, Katarzyna

    2015-09-01

    In this paper a model of web application`s source code, based on the OSD ontology (Ontology for Software Development), is proposed. This model is applied to implementation and maintenance phase of software development process through the DevOntoCreator tool [5]. The aim of this solution is decreasing software complexity of that source code, using many different maintenance techniques, like creation of documentation, elimination dead code, cloned code or bugs, which were known before [1][2]. Due to this approach saving on software maintenance costs of web applications will be possible.

  18. Ontology-Based Model Of Firm Competitiveness

    Science.gov (United States)

    Deliyska, Boryana; Stoenchev, Nikolay

    2010-10-01

    Competitiveness is important characteristics of each business organization (firm, company, corporation etc). It is of great significance for the organization existence and defines evaluation criteria of business success at microeconomical level. Each criterium comprises set of indicators with specific weight coefficients. In the work an ontology-based model of firm competitiveness is presented as a set of several mutually connected ontologies. It would be useful for knowledge structuring, standardization and sharing among experts and software engineers who develop application in the domain. Then the assessment of the competitiveness of various business organizations could be generated more effectively.

  19. Biodegradation of phenanthrene in bioaugmented microcosm by consortium ASP developed from coastal sediment of Alang-Sosiya ship breaking yard.

    Science.gov (United States)

    Patel, Vilas; Patel, Janki; Madamwar, Datta

    2013-09-15

    A phenanthrene-degrading bacterial consortium (ASP) was developed using sediment from the Alang-Sosiya shipbreaking yard at Gujarat, India. 16S rRNA gene-based molecular analyses revealed that the bacterial consortium consisted of six bacterial strains: Bacillus sp. ASP1, Pseudomonas sp. ASP2, Stenotrophomonas maltophilia strain ASP3, Staphylococcus sp. ASP4, Geobacillus sp. ASP5 and Alcaligenes sp. ASP6. The consortium was able to degrade 300 ppm of phenanthrene and 1000 ppm of naphthalene within 120 h and 48 h, respectively. Tween 80 showed a positive effect on phenanthrene degradation. The consortium was able to consume maximum phenanthrene at the rate of 46 mg/h/l and degrade phenanthrene in the presence of other petroleum hydrocarbons. A microcosm study was conducted to test the consortium's bioremediation potential. Phenanthrene degradation increased from 61% to 94% in sediment bioaugmented with the consortium. Simultaneously, bacterial counts and dehydrogenase activities also increased in the bioaugmented sediment. These results suggest that microbial consortium bioaugmentation may be a promising technology for bioremediation. Copyright © 2013 Elsevier Ltd. All rights reserved.

  20. Applications of the ACGT Master Ontology on Cancer

    OpenAIRE

    Brochhausen, Mathias; Weiler, Gabriele; Martín Martín, Luis; Cocos, Cristian; Stenzhorn, Holger; Graf, Norbert; Dörr, Martin; Tsiknakis, Manolis; Smith, Barry

    2008-01-01

    In this paper we present applications of the ACGT Master Ontology (MO) which is a new terminology resource for a transnational network providing data exchange in oncology, emphasizing the integration of both clinical and molecular data. The development of a new ontology was necessary due to problems with existing biomedical ontologies in oncology. The ACGT MO is a test case for the application of best practices in ontology development. This paper provides an overview of the application of the...

  1. Self-adaptation of Ontologies to Folksonomies in Semantic Web

    OpenAIRE

    Francisco Echarte; José Javier Astrain; Alberto Córdoba; Jesús Villadangos

    2008-01-01

    Ontologies and tagging systems are two different ways to organize the knowledge present in the current Web. In this paper we propose a simple method to model folksonomies, as tagging systems, with ontologies. We show the scalability of the method using real data sets. The modeling method is composed of a generic ontology that represents any folksonomy and an algorithm to transform the information contained in folksonomies to the generic ontology. The method allows representing folksonomies at...

  2. A collaborative recommendation framework for ontology evaluation and reuse

    OpenAIRE

    Cantador, Iván; Fernández Sánchez, Miriam; Castells, Pablo

    2006-01-01

    This is an electronic version of the paper presented at the International Workshop on Recommender Systems, held in Riva del Garda on 2006 Ontology evaluation can be defined as assessing the quality and the adequacy of an ontology for being used in a spe-cific context, for a specific goal. Although ontology reuse is being extensively addressed by the Semantic Web community, the lack of appropriate support tools and automatic techniques for the evaluation of certain ontology features are oft...

  3. Conflict Resolution in Partially Ordered OWL DL Ontologies

    NARCIS (Netherlands)

    Ji, Q.; Gao, Z.; Huang, Z.

    2014-01-01

    Inconsistency handling in OWL DL ontologies is an important problem because an ontology can easily be inconsistent when it is generated or modified. Current approaches to dealing with inconsistent ontologies often assume that there exists a total order over axioms and use such an order to select

  4. Methodology for Automatic Ontology Generation Using Database Schema Information

    Directory of Open Access Journals (Sweden)

    JungHyen An

    2018-01-01

    Full Text Available An ontology is a model language that supports the functions to integrate conceptually distributed domain knowledge and infer relationships among the concepts. Ontologies are developed based on the target domain knowledge. As a result, methodologies to automatically generate an ontology from metadata that characterize the domain knowledge are becoming important. However, existing methodologies to automatically generate an ontology using metadata are required to generate the domain metadata in a predetermined template, and it is difficult to manage data that are increased on the ontology itself when the domain OWL (Ontology Web Language individuals are continuously increased. The database schema has a feature of domain knowledge and provides structural functions to efficiently process the knowledge-based data. In this paper, we propose a methodology to automatically generate ontologies and manage the OWL individual through an interaction of the database and the ontology. We describe the automatic ontology generation process with example schema and demonstrate the effectiveness of the automatically generated ontology by comparing it with existing ontologies using the ontology quality score.

  5. Construction of Engineering Ontologies for Knowledge Sharing and Reuse

    NARCIS (Netherlands)

    Borst, Willem Nico; Borst, W.N.

    1997-01-01

    This thesis describes an investigation into the practical use of ontologies for the development of information systems. Ontologies are formal descriptions of shared knowledge in a domain. An ontology can be used as a specification of an information system because it specifies the knowledge that is

  6. Six scenarios of exploiting an ontology based, mobilized learning environment

    NARCIS (Netherlands)

    Kismihók, G.; Szabó, I.; Vas, R.

    2012-01-01

    In this article, six different exploitation possibilities of an educational ontology based, mobilized learning management system are presented. The focal point of this system is the educational ontology model. The first version of this educational ontology model serves as a foundation for curriculum

  7. On Automatic Modeling and Use of Domain-specific Ontologies

    DEFF Research Database (Denmark)

    Andreasen, Troels; Knappe, Rasmus; Bulskov, Henrik

    2005-01-01

    In this paper, we firstly introduce an approach to the modeling of a domain-specific ontology for use in connection with a given document collection. Secondly, we present a methodology for deriving conceptual similarity from the domain-specific ontology. Adopted for ontology representation is a s...

  8. ContoExam: an ontology on context-aware examinations

    NARCIS (Netherlands)

    Brandt, P.; Basten, A.A.; Stuijk, S.

    2014-01-01

    Patient observations in health care, subjective surveys in social research or dyke sensor data in water management are all examples of measurements. Several ontologies already exist to express measurements, W3C's SSN ontology being a prominent example. However, these ontologies address quantities

  9. Towards Ontological Foundations for Agent Modeling Concepts using UFO

    NARCIS (Netherlands)

    Guizzardi, G.; Wagner, Gerd

    Foundational ontologies provide the basic concepts upon which any domain-specific ontology is built. This paper presents a new foundational ontology, UFO, and shows how it can be used as a foundation of agent concepts and for evaluating agent-oriented modeling methods. UFO is derived from a

  10. Menthor Editor: An Ontology-Driven Conceptual Modeling Platform

    NARCIS (Netherlands)

    Moreira, João Luiz; Sales, Tiago Prince; Guerson, John; Braga, Bernardo F.B; Brasileiro, Freddy; Sobral, Vinicius

    2016-01-01

    The lack of well-founded constructs in ontology tools can lead to the construction of non-intended models. In this demonstration we present the Menthor Editor, an ontology-driven conceptual modelling platform which incorporates the theories of the Unified Foundational Ontology (UFO). We illustrate

  11. The Relationship between User Expertise and Structural Ontology Characteristics

    Science.gov (United States)

    Waldstein, Ilya Michael

    2014-01-01

    Ontologies are commonly used to support application tasks such as natural language processing, knowledge management, learning, browsing, and search. Literature recommends considering specific context during ontology design, and highlights that a different context is responsible for problems in ontology reuse. However, there is still no clear…

  12. Developing Learning Materials Using an Ontology of Mathematical Logic

    Science.gov (United States)

    Boyatt, Russell; Joy, Mike

    2012-01-01

    Ontologies describe a body of knowledge and give formal structure to a domain by describing concepts and their relationships. The construction of an ontology provides an opportunity to develop a shared understanding and a consistent vocabulary to be used for a given activity. This paper describes the construction of an ontology for an area of…

  13. Unsupervised Ontology Generation from Unstructured Text. CRESST Report 827

    Science.gov (United States)

    Mousavi, Hamid; Kerr, Deirdre; Iseli, Markus R.

    2013-01-01

    Ontologies are a vital component of most knowledge acquisition systems, and recently there has been a huge demand for generating ontologies automatically since manual or supervised techniques are not scalable. In this paper, we introduce "OntoMiner", a rule-based, iterative method to extract and populate ontologies from unstructured or…

  14. Ontology-based intelligent fuzzy agent for diabetes application

    NARCIS (Netherlands)

    Acampora, G.; Lee, C.-S.; Wang, M.-H.; Hsu, C.-Y.; Loia, V.

    2009-01-01

    It is widely pointed out that classical ontologies are not sufficient to deal with imprecise and vague knowledge for some real world applications, but the fuzzy ontology can effectively solve data and knowledge with uncertainty. In this paper, an ontology-based intelligent fuzzy agent (OIFA),

  15. MultiFarm: A Benchmark for Multilingual Ontology Matching

    NARCIS (Netherlands)

    Meilicke, C.; García-Castro, R.; Freitas, F.; van Hage, W.R.; Montiel-Ponsoda, E.; Ribeiro de Azevedo, R.; Stuckenschmidt, H.; Svab-Zamazal, O.; Svatek, V.; Tamalin, A.; Wang, S.

    2012-01-01

    In this paper we present the MultiFarm dataset, which has been designed as a benchmark for multilingual ontology matching. The MultiFarm dataset is composed of a set of ontologies translated in different languages and the corresponding alignments between these ontologies. It is based on the OntoFarm

  16. Utilizing a structural meta-ontology for family-based quality assurance of the BioPortal ontologies.

    Science.gov (United States)

    Ochs, Christopher; He, Zhe; Zheng, Ling; Geller, James; Perl, Yehoshua; Hripcsak, George; Musen, Mark A

    2016-06-01

    An Abstraction Network is a compact summary of an ontology's structure and content. In previous research, we showed that Abstraction Networks support quality assurance (QA) of biomedical ontologies. The development of an Abstraction Network and its associated QA methodologies, however, is a labor-intensive process that previously was applicable only to one ontology at a time. To improve the efficiency of the Abstraction-Network-based QA methodology, we introduced a QA framework that uses uniform Abstraction Network derivation techniques and QA methodologies that are applicable to whole families of structurally similar ontologies. For the family-based framework to be successful, it is necessary to develop a method for classifying ontologies into structurally similar families. We now describe a structural meta-ontology that classifies ontologies according to certain structural features that are commonly used in the modeling of ontologies (e.g., object properties) and that are important for Abstraction Network derivation. Each class of the structural meta-ontology represents a family of ontologies with identical structural features, indicating which types of Abstraction Networks and QA methodologies are potentially applicable to all of the ontologies in the family. We derive a collection of 81 families, corresponding to classes of the structural meta-ontology, that enable a flexible, streamlined family-based QA methodology, offering multiple choices for classifying an ontology. The structure of 373 ontologies from the NCBO BioPortal is analyzed and each ontology is classified into multiple families modeled by the structural meta-ontology. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. Contributions to a Conceptual Ontology for Wittgenstein

    DEFF Research Database (Denmark)

    Addis, Mark; Brock, Steen; Pichler, Alois

    2015-01-01

    A conceptual ontology was used to semantically enrich the Wittgenstein Archives at the University of Bergen’s taxonomy for Wittgenstein Source to facilitate improved searching in the areas of the philosophies of mathematics and psychology. The classes and sub-classes of the multilingual taxonomy...

  18. Social Groups, Explanation and Ontological Holism | Sheehy ...

    African Journals Online (AJOL)

    The paper begins from the claim that ontological holism is given prima facie plausibility by the apparently ineliminable role of groups in some descriptions and explanations of the social domain. If the individualist accepts the link between indispensabilty and realism, then individualism must show that groups cannot play the ...

  19. Africanity: A Combative Ontology | Mafeje | CODESRIA Bulletin

    African Journals Online (AJOL)

    Africanity: A Combative Ontology. Archie Mafeje. AJOL African Journals Online. HOW TO USE AJOL... for Researchers · for Librarians · for Authors · FAQ's · More about AJOL · AJOL's Partners · Terms and Conditions of Use · Contact AJOL · News. OTHER RESOURCES... for Researchers · for Journals · for Authors · for Policy ...

  20. Ontological Order in Scientific Explanation | Park | Philosophical ...

    African Journals Online (AJOL)

    A conceptually sound explanation, I claim, respects the ontological order between properties. A dependent property is to be explained in terms of its underlying property, not the other way around. The applicability of this point goes well beyond the realm of the debate between scientific realists and antirealists.