The Orthology Ontology: development and applications

Fernández-Breis, Jesualdo Tomás; Chiba, Hirokazu; Legaz-García, María del Carmen; Uchiyama, Ikuo

doi:10.1186/s13326-016-0077-x

Cited by 21 publications

(11 citation statements)

References 25 publications

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“…Ontologies provide a way to describe and organize concepts used in biological databases, and thereby facilitate data interoperability across multiple resources. An Orthology Ontology (ORTH) was recently introduced ( 36 ), and we adapted and extended the ORTH ontology to fully support OMA. To enhance interoperability among resources, this updated ontology uses whenever possible terms compatible with other resources, such as the Microbial Genome Database (MBGD) ( 12 ) and Universal Protein Resource (UniProt) ( 37 ) ontologies.…”

Section: Modern Programmatic Access: Rest and Sparqlmentioning

confidence: 99%

The OMA orthology database in 2018: retrieving evolutionary relationships among all domains of life through richer web and programmatic interfaces

Altenhoff

Glover

Train

et al. 2017

Nucleic Acids Research

222

227

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The Orthologous Matrix (OMA) is a leading resource to relate genes across many species from all of life. In this update paper, we review the recent algorithmic improvements in the OMA pipeline, describe increases in species coverage (particularly in plants and early-branching eukaryotes) and introduce several new features in the OMA web browser. Notable improvements include: (i) a scalable, interactive viewer for hierarchical orthologous groups; (ii) protein domain annotations and domain-based links between orthologous groups; (iii) functionality to retrieve phylogenetic marker genes for a subset of species of interest; (iv) a new synteny dot plot viewer; and (v) an overhaul of the programmatic access (REST API and semantic web), which will facilitate incorporation of OMA analyses in computational pipelines and integration with other bioinformatic resources. OMA can be freely accessed at https://omabrowser.org.

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Section: Modern Programmatic Access: Rest and Sparqlmentioning

confidence: 99%

The OMA orthology database in 2018: retrieving evolutionary relationships among all domains of life through richer web and programmatic interfaces

Altenhoff

Glover

Train

et al. 2017

Nucleic Acids Research

222

227

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“…Discussion during the meeting also highlighted the potential of applying semantic web principles and concepts to produce RDF implementations of orthology resources. Progress on the development of the Orthology Ontology ( Fernández-Breis et al , 2016 ) and its application to generate RDF versions of OrthoXML resources were presented. While more work remains to be done before such a system is fully adapted and in broad use among orthology call providers, the operations of a working group for development of orthology utilities has led to steady progress addressing specific technical issues and research questions.…”

Section: Meeting Highlightsmentioning

confidence: 99%

Gearing up to handle the mosaic nature of life in the quest for orthologs

et al. 2017

Self Cite

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Summary: The Quest for Orthologs (QfO) is an open collaboration framework for experts in comparative phylogenomics and related research areas who have an interest in highly accurate orthology predictions and their applications. We here report highlights and discussion points from the QfO meeting 2015 held in Barcelona. Achievements in recent years have established a basis to support developments for improved orthology prediction and to explore new approaches. Central to the QfO effort is proper benchmarking of methods and services, as well as design of standardized datasets and standardized formats to allow sharing and comparison of results. Simultaneously, analysis pipelines have been improved, evaluated and adapted to handle large datasets. All this would not have occurred without the long-term collaboration of Consortium members. Meeting regularly to review and coordinate complementary activities from a broad spectrum of innovative researchers clearly benefits the community. Highlights of the meeting include addressing sources of and legitimacy of disagreements between orthology calls, the context dependency of orthology definitions, special challenges encountered when analyzing very anciently rooted orthologies, orthology in the light of whole-genome duplications, and the concept of orthologous versus paralogous relationships at different levels, including domain-level orthology. Furthermore, particular needs for different applications (e.g. plant genomics, ancient gene families and others) and the infrastructure for making orthology inferences available (e.g. interfaces with model organism databases) were discussed, with several ongoing efforts that are expected to be reported on during the upcoming 2017 QfO meeting.

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“…The current UniProt RDF release comprises over 44 billion triples, and is based on the OWL 2 Full UniProt core ontology described in Redaschi et al (45). For the orthology data in OMA, we adopted the Orthology (ORTH) ontology (46), which was recently devised by the Quest for Orthologs Consortium (47) as a common data schema for integrating Orthology databases, such as OMA.…”

Section: Semantic Modelsmentioning

confidence: 99%

Enabling Semantic Queries Across Federated Bioinformatics Databases

Sima

Farias

Zbinden

et al. 2019

Preprint

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Motivation: Data integration promises to be one of the main catalysts in enabling new insights to be drawn from the wealth of biological data available publicly. However, the heterogeneity of the different data sources, both at the syntactic and the semantic level, still poses significant challenges for achieving interoperability among biological databases. Results: We introduce an ontology-based federated approach for data integration. We applied this approach to three heterogeneous data stores that span different areas of biological knowledge: 1) Bgee, a gene expression relational database; 2) OMA, a Hierarchical Data Format 5 (HDF5) orthology data store, and 3) UniProtKB, a Resource Description Framework (RDF) store containing protein sequence and functional information. To enable federated queries across these sources, we first defined a new semantic model for gene expression called GenEx. We then show how the relational data in Bgee can be expressed as a virtual RDF graph, instantiating GenEx, through dedicated relational-to-RDF mappings. By applying these mappings, Bgee data are now accessible through a public SPARQL endpoint. Similarly, the materialised RDF data of OMA, expressed in terms of the Orthology ontology, is made available in a public SPARQL endpoint. We identified and formally described intersection points (i.e. virtual links) among the three data sources. These allow performing joint queries across the data stores. Finally, we lay the groundwork to enable nontechnical users to benefit from the integrated data, by providing a natural language template-based search interface. Project URL: http://biosoda.expasy.org, https:// github.com/biosoda/bioquery data interoperability | ontology | SPARQL Correspondence: {Marc.Robinson-Rechavi, Christophe.Dessimoz}@unil.ch

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The Orthology Ontology: development and applications

Cited by 21 publications

References 25 publications

The OMA orthology database in 2018: retrieving evolutionary relationships among all domains of life through richer web and programmatic interfaces

The OMA orthology database in 2018: retrieving evolutionary relationships among all domains of life through richer web and programmatic interfaces

Gearing up to handle the mosaic nature of life in the quest for orthologs

Enabling Semantic Queries Across Federated Bioinformatics Databases

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