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dc.creatorTheodorakis E., Antonakis A.N., Baltsavia I., Pavlopoulos G.A., Samiotaki M., Amoutzias G.D., Theodosiou T., Acuto O., Efstathiou G., Iliopoulos I.en
dc.date.accessioned2023-01-31T10:07:41Z
dc.date.available2023-01-31T10:07:41Z
dc.date.issued2021
dc.identifier10.1093/nar/gkab329
dc.identifier.issn03051048
dc.identifier.urihttp://hdl.handle.net/11615/79672
dc.description.abstractBottom-up proteomics analyses have been proved over the last years to be a powerful tool in the characterization of the proteome and are crucial for understanding cellular and organism behaviour. Through differential proteomic analysis researchers can shed light on groups of proteins or individual proteins that play key roles in certain, normal or pathological conditions. However, several tools for the analysis of such complex datasets are powerful, but hard-to-use with steep learning curves. In addition, some other tools are easy to use, but are weak in terms of analytical power. Previously, we have introduced ProteoSign, a powerful, yet user-friendly open-source online platform for protein differential expression/abundance analysis designed with the end-proteomics user in mind. Part of Proteosign's power stems from the utilization of the well-established Linear Models For Microarray Data (LIMMA) methodology. Here, we present a substantial upgrade of this computational resource, called ProteoSign v2, where we introduce major improvements, also based on user feedback. The new version offers more plot options, supports additional experimental designs, analyzes updated input datasets and performs a gene enrichment analysis of the differentially expressed proteins. We also introduce the deployment of the Docker technology and significantly increase the speed of a full analysis. ProteoSign v2 is available at http://bioinformatics.med.uoc.gr/ProteoSign. © 2021 The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.en
dc.language.isoenen
dc.sourceNucleic Acids Researchen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85110317826&doi=10.1093%2fnar%2fgkab329&partnerID=40&md5=025b4c569f7211236faad516bf1178ce
dc.subjectarticleen
dc.subjectbioinformaticsen
dc.subjectDNA microarrayen
dc.subjectexperimental designen
dc.subjecthumanen
dc.subjectproteomicsen
dc.subjectshipyard workeren
dc.subjectvelocityen
dc.subjectgeneticsen
dc.subjectInterneten
dc.subjectmass spectrometryen
dc.subjectmetabolismen
dc.subjectproceduresen
dc.subjectproteomicsen
dc.subjectsoftwareen
dc.subjectstatistical analysisen
dc.subjectproteinen
dc.subjectData Interpretation, Statisticalen
dc.subjectInterneten
dc.subjectMass Spectrometryen
dc.subjectProteinsen
dc.subjectProteomicsen
dc.subjectSoftwareen
dc.subjectOxford University Pressen
dc.titleProteoSign v2: A faster and evolved user-friendly online tool for statistical analyses of differential proteomicsen
dc.typejournalArticleen


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