0000000000083708

AUTHOR

Konstantinos Sidiropoulos

0000-0003-1014-967x

showing 3 related works from this author

Reactome diagram viewer: data structures and strategies to boost performance

2017

Abstract Motivation Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. For web-based pathway visualization, Reactome uses a custom pathway diagram viewer that has been evolved over the past years. Here, we present comprehensive enhancements in usability and performance based on extensive usability testing sessions and technology developments, aiming to optimize the viewer towards the needs of the community. Results The pathway diagram viewer version 3 achieves consistently better performance, loading and rendering of 97% of the diagrams in Reactome in less than 1 s. Combining the multi-layer html5 canvas strategy with a space partit…

0301 basic medicineStatistics and ProbabilityDatabases FactualComputer scienceKnowledge BasesDatabases and OntologiesBiochemistryWorld Wide Web03 medical and health sciences0302 clinical medicineHumansMolecular BiologyInternetComputational BiologyData structureOriginal PapersComputer Science ApplicationsVisualizationComputational Mathematics030104 developmental biologyComputational Theory and Mathematics030220 oncology & carcinogenesisScalabilityAlgorithmsMetabolic Networks and PathwaysSoftwareBioinformatics
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Reactome graph database: Efficient access to complex pathway data

2018

Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data. At present, biological pathway databases typically store their contents in relational databases. This limits access efficiency because there are performance issues associated with queries traversing highly interconnected data. The same data in a graph database can be queried more efficiently. Here we present the rationale behind the adoption of a graph database (Neo4j) as well as the new ContentService (REST API) that provides access to these data. The Neo4j graph database and its qu…

0301 basic medicineDatabases FactualComputer scienceData managementKnowledge BasesSocial SciencesInformation Storage and RetrievalNoSQLcomputer.software_genreComputer ApplicationsDatabase and Informatics MethodsUser-Computer Interface0302 clinical medicineKnowledge extractionPsychologyDatabase Searchinglcsh:QH301-705.5Data ManagementLanguageBiological dataEcologySystems BiologyGenomicsGenomic DatabasesComputational Theory and MathematicsModeling and SimulationWeb-Based ApplicationsGraph (abstract data type)Information TechnologyResearch ArticleComputer and Information SciencesRelational databaseQuery languageResearch and Analysis MethodsEcosystems03 medical and health sciencesCellular and Molecular NeuroscienceDatabasesGeneticsComputer GraphicsHumansMolecular BiologyEcology Evolution Behavior and SystematicsInternetInformation retrievalGraph databasebusiness.industryEcology and Environmental SciencesCognitive PsychologyBiology and Life SciencesComputational BiologyGenome AnalysisRelational Databases030104 developmental biologyBiological Databaseslcsh:Biology (General)Cognitive Sciencebusinesscomputer030217 neurology & neurosurgerySoftwareNeurosciencePLoS Computational Biology
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Reactome pathway analysis: a high-performance in-memory approach

2016

Reactome aims to provide bioinformatics tools for visualisation, interpretation and analysis of pathway knowledge to support basic research, genome analysis, modelling, systems biology and education. Pathway analysis methods have a broad range of applications in physiological and biomedical research; one of the main problems, from the analysis methods performance point of view, is the constantly increasing size of the data samples. Here, we present a new high-performance in-memory implementation of the well-established over-representation analysis method. To achieve the target, the over-representation analysis method is divided in four different steps and, for each of them, specific data st…

0301 basic medicineData structuresDatabases FactualPathway analysisComputer scienceInterface (Java)Systems biologycomputer.software_genreGenomeBiochemistry03 medical and health sciences0302 clinical medicineStructural BiologyNucleic AcidsHumansMolecular BiologyApplied MathematicsComputational BiologyProteinsPathway analysisComputer Science ApplicationsTree (data structure)030104 developmental biology030220 oncology & carcinogenesisGraph (abstract data type)Data miningOver-representation analysiscomputerAlgorithmsSoftwareBMC Bioinformatics
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