Εμφάνιση απλής εγγραφής

dc.creatorTheodosiou T., Papanikolaou N., Savvaki M., Bonetto G., Maxouri S., Fakoureli E., Eliopoulos A.G., Tavernarakis N., Amoutzias G.D., Pavlopoulos G.A., Aivaliotis M., Nikoletopoulou V., Tzamarias D., Karagogeos D., Iliopoulos I.en
dc.date.accessioned2023-01-31T10:08:01Z
dc.date.available2023-01-31T10:08:01Z
dc.date.issued2020
dc.identifier10.1093/nargab/lqaa005
dc.identifier.issn26319268
dc.identifier.urihttp://hdl.handle.net/11615/79687
dc.description.abstractThe in-depth study of protein–protein interactions (PPIs) is of key importance for understanding how cells operate. Therefore, in the past few years, many experimental as well as computational approaches have been developed for the identification and discovery of such interactions. Here, we present UniReD, a user-friendly, computational prediction tool which analyses biomedical literature in order to extract known protein associations and suggest undocumented ones. As a proof of concept, we demonstrate its usefulness by experimentally validating six predicted interactions and by benchmarking it against public databases of experimentally validated PPIs succeeding a high coverage. We believe that UniReD can become an important and intuitive resource for experimental biologists in their quest for finding novel associations within a protein network and a useful tool to complement experimental approaches (e.g. mass spectrometry) by producing sorted lists of candidate proteins for further experimental validation. UniReD is available at http://bioinformatics.med.uoc.gr/unired/. © The Author(s) 2020. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.en
dc.language.isoenen
dc.sourceNAR Genomics and Bioinformaticsen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85090104575&doi=10.1093%2fnargab%2flqaa005&partnerID=40&md5=93c2bf728bd6c1cd6b5c63dcff63a8ad
dc.subjectarticleen
dc.subjectbenchmarkingen
dc.subjectbioinformaticsen
dc.subjectbiologisten
dc.subjecthumanen
dc.subjectmass spectrometryen
dc.subjectpredictionen
dc.subjectproof of concepten
dc.subjectprotein protein interactionen
dc.subjectOxford University Pressen
dc.titleUniProt-Related Documents (UniReD): assisting wet lab biologists in their quest on finding novel counterparts in a protein networken
dc.typejournalArticleen


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