Ontologies for use in Systems Biology: SBO, KiSAO and TEDDY

The use of computational modelling in the description and analysis of biological systems is at the heart of Systems Biology. Besides the information stored in a core model, there is increasingly a need to provide additional semantic information: to identify model components, to assist in biological interpretation of models, to define simulation conditions and to describe simulation results. This information deficit can be addressed through the use of ontologies. We describe here three ontologies created specifically to address the needs of the Systems Biology community in each sub-division, and illustrate their practical use with the 'Repressilator' model (Elowitz and Leibler, 2000)

Update: MIRIAM Registry and SBO

We describe the MIRIAM Registry, which forms a foundation layer database upon which persistent, unambiguous and perennial identifiers of data can be built. We also describe current status and planned improvements to this system, as well as providing an update on the Systems Biology ontology since the last COMBINE meeting in Edinburgh (2010). 
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Systems Biology Ontology: Update

The Systems Biology Ontology (SBO) is composed of hierarchically arranged sets of controlled vocabularies that are commonly used in mathematical modelling, providing an additional layer of semantic information. We present recent developments in SBO, including the ontology's OBO Foundry status, its relationship to SBGN, and detail some of the restructuring work that has been undertaken

Kinetic Simulation Algorithm Ontology

To enable the accurate and repeatable execution of a computational simulation task, it is important to identify both the algorithm used and the initial setup. These minimum information requirements are described by the MIASE guidelines. Since the details of some algorithms are not always publicly available, and many are implemented only in a limited number of simulation tools, it is crucial to identify alternative algorithms with similar characteristics that may be used to provide comparable results in an equivalent simulation experiment. The Kinetic Simulation Algorithm Ontology (KiSAO) was developed to address this issue by describing existing algorithms and their inter-relationships through their characteristics and parameters. The use of KiSAO in conjunction with simulation descriptions, such as SED-ML, will allow simulation software to automatically choose the best algorithm available to perform a simulation. The availability of algorithm parameters, together with their type may permit the automatic generation of user-interfaces to configure simulators. To enable making queries to KiSAO programmaticaly, from simulation experiment description editors and simulation tools, a java library libKiSAO was implemented

RO-Crates as a practical implementation of FAIR Digital Object to align biodiversity genomics work streams

We describe our pragmatic approach for aligning parallel scientific processes through the implementation of Fair Digital Objects (FDOs), as RO-Crates. Our work is grounded in the Biodiversity domains, but may be extrapolated to be useful more generally in other scientific domains

Unique, Persistent, Resolvable: Identifiers as the foundation of FAIR

The FAIR Principles describe characteristics intended to support access to and reuse of digital artifacts in the scientific research ecosystem. Persistent, globally unique identifiers, resolvable on the Web, and associated with a set of additional descriptive metadata, are foundational to FAIR data. Here we describe some basic principles and exemplars for their design, use and orchestration with other system elements to achieve FAIRness for digital research objects

SPARQL-enabled identifier conversion with Identifiers.org

Motivation: On the semantic web, in life sciences in particular, data is often distributed via multiple resources. Each of these sources is likely to use their own International Resource Identifier for conceptually the same resource or database record. The lack of correspondence between identifiers introduces a barrier when executing federated SPARQL queries across life science data. Results: We introduce a novel SPARQL-based service to enable on-the-fly integration of life science data. This service uses the identifier patterns defined in the Identifiers.org Registry to generate a plurality of identifier variants, which can then be used to match source identifiers with target identifiers. We demonstrate the utility of this identifier integration approach by answering queries across major producers of life science Linked Data. Availability and implementation: The SPARQL-based identifier conversion service is available without restriction at http://identifiers.org/services/sparql. Contact: [email protected]

BioModels: ten-year anniversary

BioModels (http://www.ebi.ac.uk/biomodels/) is a repository of mathematical models of biological processes. A large set of models is curated to verify both correspondence to the biological process that the model seeks to represent, and reproducibility of the simulation results as described in the corresponding peer-reviewed publication. Many models submitted to the database are annotated, cross-referencing its components to external resources such as database records, and terms from controlled vocabularies and ontologies. BioModels comprises two main branches: one is composed of models derived from literature, while the second is generated through automated processes. BioModels currently hosts over 1200 models derived directly from the literature, as well as in excess of 140 000 models automatically generated from pathway resources. This represents an approximate 60-fold growth for literature-based model numbers alone, since BioModels’ first release a decade ago. This article describes updates to the resource over this period, which include changes to the user interface, the annotation profiles of models in the curation pipeline, major infrastructure changes, ability to perform online simulations and the availability of model content in Linked Data form. We also outline planned improvements to cope with a diverse array of new challenges