OntoCAT -- simple ontology search and integration in Java, R and REST/JavaScript

Adamusiak, Tomasz; Burdett, Tony; Kurbatova, Natalja; Velde, K. Joeri van der; Abeygunawardena, Niran; Antonakaki, Despoina; Kapushesky, Misha; Parkinson, Helen; Swertz, Morris A.

doi:10.1186/1471-2105-12-218

Cited by 30 publications

(23 citation statements)

References 25 publications

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“…As can be observed in Figure 2B, AAA–AAG is the two-codon combination represented most (15) in YEF3 . In addition, based on frequency difference values for all codon doublets, AAG–AAG is the most over-represented in this sequence.…”

Section: Resultsmentioning

confidence: 56%

The gene-specific codon counting database: a genome-based catalog of one-, two-, three-, four- and five-codon combinations present in Saccharomyces cerevisiae genes

et al. 2012

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A codon consists of three nucleotides and functions during translation to dictate the insertion of a specific amino acid in a growing peptide or, in the case of stop codons, to specify the completion of protein synthesis. There are 64 possible single codons and there are 4096 double, 262 144 triple, 16 777 216 quadruple and 1 073 741 824 quintuple codon combinations available for use by specific genes and genomes. In order to evaluate the use of specific single, double, triple, quadruple and quintuple codon combinations in genes and gene networks, we have developed a codon counting tool and employed it to analyze 5780 Saccharomyces cerevisiae genes. We have also developed visualization approaches, including codon painting, combination and bar graphs, and have used them to identify distinct codon usage patterns in specific genes and groups of genes. Using our developed Gene-Specific Codon Counting Database, we have identified extreme codon runs in specific genes. We have also demonstrated that specific codon combinations or usage patterns are over-represented in genes whose corresponding proteins belong to ribosome or translation-associated biological processes. Our resulting database provides a mineable list of multi-codon data and can be used to identify unique sequence runs and codon usage patterns in individual and functionally linked groups of genes.Database URL: http://www.cs.albany.edu/~tumu/GSCC.html

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Section: Resultsmentioning

confidence: 56%

The gene-specific codon counting database: a genome-based catalog of one-, two-, three-, four- and five-codon combinations present in Saccharomyces cerevisiae genes

et al. 2012

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“…Richer programming interfaces for interacting with ontology resources are also available, e.g., OntoCAT [7], an application suite enabling the querying of several resources simultaneously, looking for synonyms and definitions (which is not supported directly by OWL API). Nevertheless, due to the complex structure and variety of relationships used in KiSAO, none of these interfaces provide an easy way to retrieve all the information from KiSAO.…”

Section: Resultsmentioning

confidence: 99%

LibKiSAO: a Java library for Querying KiSAO

et al. 2012

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BackgroundThe Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of Systems Biology models, their characteristics, parameters and inter-relationships. KiSAO enables the unambiguous identification of algorithms from simulation descriptions. Information about analogous methods having similar characteristics and about algorithm parameters incorporated into KiSAO is desirable for simulation tools. To retrieve this information programmatically an application programming interface (API) for KiSAO is needed.FindingsWe developed libKiSAO, a Java library to enable querying of the KiSA Ontology. It implements methods to retrieve information about simulation algorithms stored in KiSAO, their characteristics and parameters, and methods to query the algorithm hierarchy and search for similar algorithms providing comparable results for the same simulation set-up. Using libKiSAO, simulation tools can make logical inferences based on this knowledge and choose the most appropriate algorithm to perform a simulation. LibKiSAO also enables simulation tools to handle a wider range of simulation descriptions by determining which of the available methods are similar and can be used instead of the one indicated in the simulation description if that one is not implemented.ConclusionsLibKiSAO enables Java applications to easily access information about simulation algorithms, their characteristics and parameters stored in the OWL-encoded Kinetic Simulation Algorithm Ontology. LibKiSAO can be used by simulation description editors and simulation tools to improve reproducibility of computational simulation tasks and facilitate model re-use.

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“…Manual approaches [15] use search engines, such as the BioPortal web portal [14], to enable an expert to perform the mapping. Automated approaches, in particular MetaMap [16] and cTakes [17], provide a way to map various texts, sentences, etc.…”

Section: A Related Workmentioning

confidence: 99%

Integrating existing large scale medical laboratory data into the semantic web framework

Haider

Abidi

Woensel

2014

2014 IEEE International Conference on Big Data (Big Data)

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Semantic Web technologies have shown to have great potential in many different domains, to facilitate knowledge representation, exchange and reasoning, in a formal and yet both human and machine understandable way. In particular, within the health domain, they enable knowledge integration and understanding by explicitly defining and linking concepts and relationships using ontologies to information within clinical knowledge bases. This additional metadata also allows for automated decision support and semantic based analytics to be implemented, that facilitate improved healthcare at a lower cost. Unfortunately many existing datasets in healthcare environments are still stored in relational databases, as opposed to using semantic technologies. Due to this, the link with explicit metadata is often lacking or non-existent. Furthermore, both the databases and the clinical terminologies can be considerably large, making the mapping and subsequent uses of the information a difficult process. In a full fledged decision support system the level and accuracy of the mapping can greatly influence the effectiveness of any subsequent analysis and decision support tasks. This is especially true in clinical scenarios, where very large and complex sets of terms need to be mapped to relational databases. In this paper we aim to provide a general approach for interlinking relational data with clinical ontology based metadata that allows for a fine grade evaluation, with respect to the mapping's impact on analytics. We evaluate our approach by mapping information from clinical terminologies, such as SNOMED CT, to a large laboratory dataset contained in a relational database, with the goal of creating a full fledged, semantically enabled, analytics and decision support system.

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OntoCAT -- simple ontology search and integration in Java, R and REST/JavaScript

Cited by 30 publications

References 25 publications

The gene-specific codon counting database: a genome-based catalog of one-, two-, three-, four- and five-codon combinations present in Saccharomyces cerevisiae genes

The gene-specific codon counting database: a genome-based catalog of one-, two-, three-, four- and five-codon combinations present in Saccharomyces cerevisiae genes

LibKiSAO: a Java library for Querying KiSAO

Integrating existing large scale medical laboratory data into the semantic web framework

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