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Use Case: Ontology with Rules for identifying brain anatomical structures

Christine Golbreich, Olivier Bierlaire, Olivier Dameron, Bernard Gibaud
2005 W3C Workshops  
The proposed use case focuses on interoperating between a rule base and a brain cortex anatomy ontology, in order to assist the labeling of the brain cortex structures -sulci and gyri -involved in MRI images. The use case documents the ontology and the rules so as to clarify the added value and needs of rules, and the language expressiveness required. The expected result is to get candidate languages extending OWL DL with rules that allow representing all the knowledge required (ontology and
more » ... es), joint with the properties of reasoning that are guaranteed.
dblp:conf/w3c/GolbreichBDG05 fatcat:mc4hmu6iord43gpr7twujj2oja

Reproducibility and reusability limitations in Regulatory Circuits: analysis and solutions [article]

Marine Louarn, Anne Siegel, Thierry Fest, Olivier Dameron, Fabrice Chatonnet
2021 bioRxiv   pre-print
The Regulatory Circuits project is among the most recent and the most complete attempts to identify cell-type specific regulatory networks in Human. It is one of the largest efforts of public genomics data integration, based on data from the major consortia FANTOM5, ENCODE and Roadmap Epigenomics. This project is a main provider of biological data, cited more than 224 times (Google Scholar) and its resulting networks were used in at least 42 other articles. For such a general resource,
more » ... bility of both the outputs (regulation networks) and methods (data integration pipeline) is a major issue, since biological data are updated regularly. In addition, users may want to introduce new data into the Regulatory Circuits framework to provide networks about previously uncharacterized cell types or to add information about specific regulators, which require to re-execute the whole pipeline on the new data. In this article, we analyze the various factors limiting reproducibility of the Regulatory Circuits data and methods. Starting from a factual description of our understanding of the methods used in Regulatory Circuits, our contribution is two-fold: we propose (1) a characterization of the different levels of reusability, reproducibility and conceptual issues in the original workflow and (2) a new implementation of the workflow ensuring its consistency with the published description and allowing for an easier reuse and reproduction of the published outputs. Both are applicable beyond the case of Regulatory Circuits.
doi:10.1101/2021.08.02.454723 fatcat:dhzk2qwsnvfwnibk7jywm4qx4a

Converting Alzheimer s disease map into a heavyweight ontology: a formal network to integrate data [article]

Vincent Henry, Ivan Moszer, Olivier Dameron, Marie-Claude Potier, Martin Hofmann-Apitius, Olivier Colliot
2018 arXiv   pre-print
Alzheimer s disease (AD) pathophysiology is still imperfectly understood and current paradigms have not led to curative outcome. Omics technologies offer great promises for improving our understanding and generating new hypotheses. However, integration and interpretation of such data pose major challenges, calling for adequate knowledge models. AlzPathway is a disease map that gives a detailed and broad account of AD pathophysiology. However, AlzPathway lacks formalism, which can lead to
more » ... ty and misinterpretation. Ontologies are an adequate framework to overcome this limitation, through their axiomatic definitions and logical reasoning properties. We introduce the AD Map Ontology (ADMO) an ontological upper model based on systems biology terms. We then propose to convert AlzPathway into an ontology and to integrate it into ADMO. We demonstrate that it allows one to deal with issues related to redundancy, naming, consistency, process classification and pathway relationships. Further, it opens opportunities to expand the model using elements from other resources, such as generic pathways from Reactome or clinical features contained in the ADO (AD Ontology). A version of the ontology will be made freely available to the community on Bioportal at the time of the confer-ence.
arXiv:1807.10509v1 fatcat:ow45axqhbbgyxb6utebzdo7pqm

Accessing and Manipulating Ontologies Using Web Services

Olivier Dameron, Natalya Fridman Noy, Holger Knublauch, Mark A. Musen
2004 International Semantic Web Conference  
Ontologies and Semantic Web Services are the two core technologies of the Semantic Web. The Semantic Web hinges on the ability of computer programs to perform some task involving the autonomous resolution of semantic issues. This ability requires providing standard access for software to ontologies. Moreover, for the Semantic Web to gain widespread acceptance, it needs to reach a critical mass of applications that can interact. This last point requires providing standard access to
more » ... s for manipulating ontologies. Therefore, it is relevant to bring ontologies and Web Services together by providing access to ontologies through Semantic Web Services. We analyse different kinds of ontology-manipulation functionalities that could be implemented as ontology Web Services (OWS). We then propose an architecture allowing programs to insert calls to ontology Web Services into the more general framework of Web Services. We show that this architecture is a necessary complement to OWL-S for Semantic Web applications to perform dynamic discovery and invocation of Web Services, thus addressing a key requirement of the Semantic Web. We then demonstrate the scalability of our architecture as it allows the composition of (ontology) Web Services for performing complex tasks.
dblp:conf/semweb/DameronNKM04 fatcat:3wpkxqt5gvdpvb57opko5vasim

Modeling cardiac rhythm and heart rate using BFO and DOLCE

Lynda Temal, Arnaud Rosier, Olivier Dameron, Anita Burgun
2009 Nature Precedings  
doi:10.1038/npre.2009.3558.1 fatcat:2fh273lvorevlay5desubgjcxu

Testing tactics to localize de-identification

Cyril Grouin, Arnaud Rosier, Olivier Dameron, Pierre Zweigenbaum
2009 Studies in Health Technology and Informatics  
Recent renewed interest in de-identification (also known as "anonymisation") has led to the development of a series of systems in the United States with very good performance on challenge test sets. De-identification needs however to be tuned to the local documents and their specificities. We address here two issues raised in this context. First, tuning is generally performed by language engineers who should not have to work on identified text. We therefore perform a first gross
more » ... n step in the hospital. Second, to set up a de-identification system for new documents in a language different from English, here French patient reports, we tested two methods: the first attempts to adapt an existing US de-identifier for English, the second re-develops a new system which applies the same methods. The first method involved localizing patterns designed for English, which proved cumbersome and did not quickly obtain good performance. With a similar effort, the latter method obtained much better results. Evaluated on a set of 23 randomly selected texts from a corpus of 21,749 clinical texts, it obtained 83% recall and 92% precision.
pmid:19745408 fatcat:n7mz53erenek7cdgtncv4g374e

Converting Alzheimer's Disease Map into a Heavyweight Ontology: A Formal Network to Integrate Data [chapter]

Vincent Henry, Ivan Moszer, Olivier Dameron, Marie-Claude Potier, Martin Hofmann-Apitius, Olivier Colliot
2018 Lecture Notes in Computer Science  
Alzheimer's disease (AD) pathophysiology is still imperfectly understood and current paradigms have not led to curative outcome. Omics technologies offer great promises for improving our understanding and generating new hypotheses. However, integration and interpretation of such data pose major challenges, calling for adequate knowledge models. AlzPathway is a disease map that gives a detailed and broad account of AD pathophysiology. However, AlzPathway lacks formalism, which can lead to
more » ... ty and misinterpretation. Ontologies are an adequate framework to overcome this limitation, through their axiomatic definitions and logical reasoning properties. We introduce the AD Map Ontology (ADMO), an ontological upper model based on systems biology terms. We then propose to convert AlzPathway into an ontology and to integrate it into ADMO. We demonstrate that it allows one to deal with issues related to redundancy, naming, consistency, process classification and pathway relationships. Further, it opens opportunities to expand the model using elements from other resources, such as generic pathways from Reactome or clinical features contained in the ADO (AD Ontology). A version of ADMO is freely available at http://bioportal.bioontology.org/ontologies/ADMO.
doi:10.1007/978-3-030-06016-9_20 fatcat:ayjfnrnkwvex5jz2pnhf5q7afm

Formalizing and Enriching Phenotype Signatures using Boolean Networks

Méline Wery, Olivier Dameron, Jacques Nicolas, lisabeth Remy, Anne Siegel
2019 Journal of Theoretical Biology  
In order to predict the behavior of a biological system, one common approach is to perform a simulation on a dynamic model. Boolean networks allow to analyze the qualitative aspects of the model by identifying its steady states and attractors. Each of them, when possible, is associated with a phenotype which conveys a biological interpretation. Phenotypes are characterized by their signatures, provided by domain experts. The number of steady states tends to increase with the network size and
more » ... number of simulation conditions, which makes the biological interpretation difficult. As a first step, we explore the use of Formal Concept Analysis as a symbolic bi-clustering technics to classify and sort the steady states of a Boolean network according to biological signatures based on the hierarchy of the roles the network components play in the phenotypes. FCA generates a lattice structure describing the dependencies between proteins in the signature and steady-states of the Boolean network. We use this lattice (i) to enrich the biological signatures according to the dependencies carried by the network dynamics, (ii) to identify variants to the phenotypes and (iii) to characterize hybrid phenotypes. We applied our approach on a T helper lymphocyte (Th) differentiation network with a set of signatures corresponding to the sub-types of Th. Our method generated the same classification as a manual analysis performed by experts in the field, and was also able to work under extended simulation conditions. This led to the identification and prediction of a new hybrid sub-type later confirmed by the literature.
doi:10.1016/j.jtbi.2019.01.015 pmid:30738049 fatcat:ffiybr3ijfhcfkgbceiwugwimy

Regulus, a transcriptional regulatory networks inference tool based on Semantic Web technologies [article]

Marine Louarn, Guillaume Collet, Eve Barre, Thierry Fest, Olivier Dameron, Anne Siegel, Fabrice Chatonnet
2021 bioRxiv   pre-print
Motivation: Transcriptional regulation -a major field of investigation in life science- is performed by binding of specialized proteins called transcription factors (TF) to DNA in specific, context-dependent regulatory regions, leading to either activation or inhibition of gene expression. Relations between TF, regions and genes can be described as regulatory networks, which are basically knowledge graphs containing the relationships between the different entities. Current methods of
more » ... onal regulatory networks inference rarely use information about TF binding or regulatory regions, often require a large number of samples and most of time do not indicate if the TF-gene relation is an activation or an inhibition. The resulting networks may then contain inconsistent relations and the methods are not applicable for common experimental or clinical settings, where the number of samples is limited. Therefore, based on our previous experience of formalizing the Regulatory Circuits data-sets with Semantic Web Technologies, we decided to create a new tool for transcriptional networks inference, that could solve these issues. Results: Our tool, Regulus, provides candidate signed TF-gene relations computed from gene expressions, regulatory region activities and TF binding sites data, together with the genomic location of all entities. After creating expressions and activities patterns, data are integrated into a RDF endpoint. A dedicated SPARQL query retrieves all potential TF-region relations for a given gene expression pattern. These ternary TF-region-gene pattern relations are then filtered and signed using a logical consistency check translated from biological knowledge. Regulus compares favorably to its closest network inference method, provides signs which are consistent with public databases and, when applied to real biological data, identifies both known and potential new regulators. We also provide several means to more stringently filter the output regulators. Altogether, we propose a new tool devoted to transcriptional network inference in settings where samples are scarce and cell populations may be closely related.
doi:10.1101/2021.08.02.454721 fatcat:uee4esor2bcgzo3ze7cpeejfie

A Similarity Measure Based on Care Trajectories as Sequences of Sets [chapter]

Yann Rivault, Nolwenn Le Meur, Olivier Dameron
2017 Lecture Notes in Computer Science  
Comparing care trajectories helps improve health services. Medicoadministrative databases are useful for automatically reconstructing the patients' history of care. Care trajectories can be compared by determining their overlapping parts. This comparison relies on both semantically-rich representation formalism for care trajectories and an adequate similarity measure. The longest common subsequence (LCS) approach could have been appropriate if representing complex care trajectories as simple
more » ... uences was expressive enough. Furthermore, by failing to take into account similarities between different but semantically close medical events, the LCS overestimates differences. We propose a generalization of the LCS to a more expressive representation of care trajectories as sequences of sets. A set represents a medical episode composed by one or several medical events, such as diagnosis, drug prescription or medical procedures. Moreover, we propose to take events' semantic similarity into account for comparing medical episodes. To assess our approach, we applied the method on a care trajectories' sample from patients who underwent a surgical act among three kinds of acts. The formalism reduced calculation time, and introducing semantic similarity made the three groups more homogeneous.
doi:10.1007/978-3-319-59758-4_32 fatcat:l3iisqifm5eu7j2zxgh46lgujq

Weaving the biomedical Semantic Web with the Prote'ge' OWL Plugin

Holger Knublauch, Olivier Dameron, Mark A. Musen
2004 Conference on Knowledge Representation in Medicine  
Olivier Dameron is funded by INRIA. Additional support for this work came from the UK Joint Information Services Committee under the CO-ODE grant.  ... 
dblp:conf/krmed/KnublauchDM04 fatcat:vfcjesfh4vellkcm4o5bpezmzu

Measuring the Evolution of Ontology Complexity: The Gene Ontology Case Study

Olivier Dameron, Charles Bettembourg, Nolwenn Le Meur, Marc Robinson-Rechavi
2013 PLoS ONE  
Ontologies support automatic sharing, combination and analysis of life sciences data. They undergo regular curation and enrichment. We studied the impact of an ontology evolution on its structural complexity. As a case study we used the sixty monthly releases between January 2008 and December 2012 of the Gene Ontology and its three independent branches, i.e. biological processes (BP), cellular components (CC) and molecular functions (MF). For each case, we measured complexity by computing
more » ... s related to the size, the nodes connectivity and the hierarchical structure. The number of classes and relations increased monotonously for each branch, with different growth rates. BP and CC had similar connectivity, superior to that of MF. Connectivity increased monotonously for BP, decreased for CC and remained stable for MF, with a marked increase for the three branches in November and December 2012. Hierarchy-related measures showed that CC and MF had similar proportions of leaves, average depths and average heights. BP had a lower proportion of leaves, and a higher average depth and average height. For BP and MF, the late 2012 increase of connectivity resulted in an increase of the average depth and average height and a decrease of the proportion of leaves, indicating that a major enrichment effort of the intermediate-level hierarchy occurred. The variation of the number of classes and relations in an ontology does not provide enough information about the evolution of its complexity. However, connectivity and hierarchy-related metrics revealed different patterns of values as well as of evolution for the three branches of the Gene Ontology. CC was similar to BP in terms of connectivity, and similar to MF in terms of hierarchy. Overall, BP complexity increased, CC was refined with the addition of leaves providing a finer level of annotations but decreasing slightly its complexity, and MF complexity remained stable.
doi:10.1371/journal.pone.0075993 pmid:24146805 pmcid:PMC3795689 fatcat:wubphyvfkfh5dndbccxo42xbxm

Grading glioma tumors using OWL-DL and NCI Thesaurus

Gwenaëlle Marquet, Olivier Dameron, Stephan Saikali, Jean Mosser, Anita Burgun
2007 AMIA Annual Symposium Proceedings  
Brain tumors' treatment and prognosis depend to a large extent on their grades. Grading tumors follows a set of rules that refers to domain knowledge. Developing an automatic grading system requires explicit and formal representation of the domain. The NCI Thesaurus is the major ontological resource in the cancer domain. However, the description of brain tumors and grades in the NCI Thesaurus does not enable automatic grading. We have developed an ontology based on the NCI Thesaurus for
more » ... c classification of glioma tumors based on a reference grading system. Two sets of tests have been done. The first one has been automatically generated and the second one consists of eleven pathology reports. The resulting ontology contains 243 classes, among which 234 correspond to NCI Thesaurus classes. Because all of the generated tests were correctly classified, we believe our system to be correct. Ten clinical reports are correctly graded and one is graded incompletely.
pmid:18693888 pmcid:PMC2655830 fatcat:dbwjcrkwgbarxny5wtizyvajpa

GO2PUB: Querying PubMed with semantic expansion of gene ontology terms

Charles Bettembourg, Christian Diot, Anita Burgun, Olivier Dameron
2012 Journal of Biomedical Semantics  
With the development of high throughput methods of gene analyses, there is a growing need for mining tools to retrieve relevant articles in PubMed. As PubMed grows, literature searches become more complex and time-consuming. Automated search tools with good precision and recall are necessary. We developed GO2PUB to automatically enrich PubMed queries with gene names, symbols and synonyms annotated by a GO term of interest or one of its descendants. Results: GO2PUB enriches PubMed queries based
more » ... n selected GO terms and keywords. It processes the result and displays the PMID, title, authors, abstract and bibliographic references of the articles. Gene names, symbols and synonyms that have been generated as extra keywords from the GO terms are also highlighted. GO2PUB is based on a semantic expansion of PubMed queries using the semantic inheritance between terms through the GO graph. Two experts manually assessed the relevance of GO2PUB, GoPubMed and PubMed on three queries about lipid metabolism. Experts' agreement was high (kappa=0.88). GO2PUB returned 69% of the relevant articles, GoPubMed: 40% and PubMed: 29%. GO2PUB and GoPubMed have 17% of their results in common, corresponding to 24% of the total number of relevant results. 70% of the articles returned by more than one tool were relevant. 36% of the relevant articles were returned only by GO2PUB, 17% only by GoPubMed and 14% only by PubMed. For determining whether these results can be generalized, we generated twenty queries based on random GO terms with a granularity similar to those of the first three queries and compared the proportions of GO2PUB and GoPubMed results. These were respectively of 77% and 40% for the first queries, and of 70% and 38% for the random queries. The two experts also assessed the relevance of seven of the twenty queries (the three related to lipid metabolism and four related to other domains). Expert agreement was high (0.93 and 0.8). GO2PUB and GoPubMed performances were similar to those of the first queries. Conclusions: We demonstrated that the use of genes annotated by either GO terms of interest or a descendant of these GO terms yields some relevant articles ignored by other tools. The comparison of GO2PUB, based on semantic expansion, with GoPubMed, based on text mining techniques, showed that both tools are complementary. The analysis of the randomly-generated queries suggests that the results obtained about lipid metabolism can be generalized to other biological processes. GO2PUB is available at http://go2pub.genouest.org.
doi:10.1186/2041-1480-3-7 pmid:22958570 pmcid:PMC3599846 fatcat:ifmrmcuxmfgihcajry64sm65ra

Semantic Particularity Measure for Functional Characterization of Gene Sets Using Gene Ontology

Charles Bettembourg, Christian Diot, Olivier Dameron, Christos A. Ouzounis
2014 PLoS ONE  
Genetic and genomic data analyses are outputting large sets of genes. Functional comparison of these gene sets is a key part of the analysis, as it identifies their shared functions, and the functions that distinguish each set. The Gene Ontology (GO) initiative provides a unified reference for analyzing the genes molecular functions, biological processes and cellular components. Numerous semantic similarity measures have been developed to systematically quantify the weight of the GO terms
more » ... by two genes. We studied how gene set comparisons can be improved by considering gene set particularity in addition to gene set similarity. Results: We propose a new approach to compute gene set particularities based on the information conveyed by GO terms. A GO term informativeness can be computed using either its information content based on the term frequency in a corpus, or a function of the term's distance to the root. We defined the semantic particularity of a set of GO terms Sg1 compared to another set of GO terms Sg2. We combined our particularity measure with a similarity measure to compare gene sets. We demonstrated that the combination of semantic similarity and semantic particularity measures was able to identify genes with particular functions from among similar genes. This differentiation was not recognized using only a semantic similarity measure. Conclusion: Semantic particularity should be used in conjunction with semantic similarity to perform functional analysis of GO-annotated gene sets. The principle is generalizable to other ontologies.
doi:10.1371/journal.pone.0086525 pmid:24489737 pmcid:PMC3904913 fatcat:kogusrsk3ja3lgflxxs2tu5c6m
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