Rodyti trumpą aprašą

dc.contributor.authorSerackis, Artūras
dc.contributor.authorMatuzevičius, Dalius
dc.contributor.authorNavakauskas, Dalius
dc.contributor.authorŠabanovič, Eldar
dc.contributor.authorKatkevičius, Andrius
dc.contributor.authorPlonis, Darius
dc.date.accessioned2023-09-18T16:54:00Z
dc.date.available2023-09-18T16:54:00Z
dc.date.issued2017
dc.identifier.issn2255-9140
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/117928
dc.description.abstractThe aim of the investigation presented in this paper was to develop a software-based assistant for the protein analysis workflow. The prior characterization of the unknown protein in two-dimensional electrophoresis gel images is performed according to the molecular weight and isoelectric point of each protein spot estimated from the gel image before further sequence analysis by mass spectrometry. The paper presents a method for automatic and robust identification of the protein standard band in a two-dimensional gel image. In addition, the method introduces the identification of the positions of the markers, prepared by using pre-selected proteins with known molecular mass. The robustness of the method was achieved by using special validation rules in the proposed original algorithms. In addition, a self-organizing map-based decision support algorithm is proposed, which takes Gabor coefficients as image features and searches for the differences in preselected vertical image bars. The experimental investigation proved the good performance of the new algorithms included into the proposed method. The detection of the protein standard markers works without modification of algorithm parameters on two-dimensional gel images obtained by using different staining and destaining procedures, which results in different average levels of intensity in the images.eng
dc.formatPDF
dc.format.extentp. 63-68
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyGenamics Journal Seek
dc.relation.isreferencedbyDOAJ
dc.relation.isreferencedbyJ-Gate
dc.relation.isreferencedbyEmerging Sources Citation Index (Web of Science)
dc.rightsLaisvai prieinamas internete
dc.source.urihttps://doi.org/10.1515/ecce-2017-0009
dc.source.urihttps://talpykla.elaba.lt/elaba-fedora/objects/elaba:25363633/datastreams/MAIN/content
dc.subjectIK04 - Skaitmeninės signalų apdorojimo technologijos / Digital signal processing technologies
dc.titleA robust identification of the protein standard bands in two-dimensional electrophoresis gel images
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.accessRightsThis is an open access article licensed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), in the manner agreed with De Gruyter Open.
dcterms.references16
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyElektronikos fakultetas / Faculty of Electronics
dc.subject.researchfieldT 001 - Elektros ir elektronikos inžinerija / Electrical and electronic engineering
dc.subject.ltspecializationsL106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies
dc.subject.enBiomedical imaging
dc.subject.enImage analysis
dc.subject.enMolecular biomarkers
dc.subject.enProteins
dc.subject.enQuantization
dcterms.sourcetitleElectrical, control and communication engineering
dc.description.issueiss. 1
dc.description.volumeVol. 13
dc.publisher.nameDe Gruyter
dc.publisher.cityWarsaw
dc.identifier.doi000419688200003
dc.identifier.doi10.1515/ecce-2017-0009
dc.identifier.elaba25363633


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