2019
Gene set enrichment for reproducible science: comparison of CERNO and eight other algorithms
Zyla J, Marczyk M, Domaszewska T, Kaufmann SHE, Polanska J, Weiner J. Gene set enrichment for reproducible science: comparison of CERNO and eight other algorithms. Bioinformatics 2019, 35: 5146-5154. PMID: 31165139, PMCID: PMC6954644, DOI: 10.1093/bioinformatics/btz447.Peer-Reviewed Original ResearchConceptsReal-world datasetsEvaluation metricsCernoNovel algorithmReproducible scienceOnline implementationComputational timeFalse positive ratePractical reproducibilityFast algorithmSupplementary dataAlgorithmRelated dataNovel approachDatasetR packageEnrichment algorithmPositive rateMetricsImplementationEssential partGS sizeRepositoryPackage
2016
Improved Detection of 2D Gel Electrophoresis Spots by Using Gaussian Mixture Model
Marczyk M. Improved Detection of 2D Gel Electrophoresis Spots by Using Gaussian Mixture Model. Lecture Notes In Computer Science 2016, 9683: 284-294. DOI: 10.1007/978-3-319-38782-6_24.Peer-Reviewed Original ResearchParallel computing capabilitiesSpot detectionGaussian mixture modelGel imagesComputing capabilitiesAutomatic methodEfficient implementationComputational timeBest overall performanceMixture modelAbstract2D gel electrophoresisOverall performanceImagesTrue positionDetectionAlgorithmDatasetSoftwareImplementationCapabilityMethodThousandsAccurate estimates