2023
POLCOVID: a multicenter multiclass chest X-ray database (Poland, 2020–2021)
Suwalska A, Tobiasz J, Prazuch W, Socha M, Foszner P, Piotrowski D, Gruszczynska K, Sliwinska M, Walecki J, Popiela T, Przybylski G, Nowak M, Fiedor P, Pawlowska M, Flisiak R, Simon K, Zapolska G, Gizycka B, Szurowska E, Marczyk M, Cieszanowski A, Polanska J. POLCOVID: a multicenter multiclass chest X-ray database (Poland, 2020–2021). Scientific Data 2023, 10: 348. PMID: 37268643, PMCID: PMC10236395, DOI: 10.1038/s41597-023-02229-5.Peer-Reviewed Original ResearchConceptsLung maskChest X-ray databaseChest X-ray imagesArtificial intelligence toolsCOVID-19 detectionX-ray databaseImage collectionImage databaseX-ray imagesIntelligence toolsSegmentation solutionSegmentation modelDiagnosis methodOriginal radiographsDatasetImagesCOVID-19 diagnosisDatabaseHealthcare systemMaskMedical assistanceSmall numberLung areaSetTool
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
2018
BatchI: Batch effect Identification in high-throughput screening data using a dynamic programming algorithm
Papiez A, Marczyk M, Polanska J, Polanski A. BatchI: Batch effect Identification in high-throughput screening data using a dynamic programming algorithm. Bioinformatics 2018, 35: 1885-1892. PMID: 30357412, PMCID: PMC6546123, DOI: 10.1093/bioinformatics/bty900.Peer-Reviewed Original ResearchAlgorithmsResearch DesignGaMRed—Adaptive Filtering of High-Throughput Biological Data
Marczyk M, Jaksik R, Polanski A, Polanska J. GaMRed—Adaptive Filtering of High-Throughput Biological Data. IEEE/ACM Transactions On Computational Biology And Bioinformatics 2018, 17: 149-157. PMID: 30040660, DOI: 10.1109/tcbb.2018.2858825.Peer-Reviewed Original Research
2017
Ranking metrics in gene set enrichment analysis: do they matter?
Zyla J, Marczyk M, Weiner J, Polanska J. Ranking metrics in gene set enrichment analysis: do they matter? BMC Bioinformatics 2017, 18: 256. PMID: 28499413, PMCID: PMC5427619, DOI: 10.1186/s12859-017-1674-0.Peer-Reviewed Original ResearchMixture Modeling of 2-D Gel Electrophoresis Spots Enhances the Performance of Spot Detection
Marczyk M. Mixture Modeling of 2-D Gel Electrophoresis Spots Enhances the Performance of Spot Detection. IEEE Transactions On NanoBioscience 2017, 16: 91-99. PMID: 28278480, DOI: 10.1109/tnb.2017.2676725.Peer-Reviewed Original Research
2015
Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry
Polanski A, Marczyk M, Pietrowska M, Widlak P, Polanska J. Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry. PLOS ONE 2015, 10: e0134256. PMID: 26230717, PMCID: PMC4521892, DOI: 10.1371/journal.pone.0134256.Peer-Reviewed Original ResearchConceptsGaussian mixture modelingMixture modelGaussian mixture modelPeak detectionProteomic mass spectraFeature extractionPartitioning algorithmEfficient algorithmSignal compressionSoftware packageAlgorithmMain ideaMixture modelingModeling approachModelingDatasetApplicationsDetectionPreliminary resultsDetection efficiencyProteomic datasetsMixture modeling approachModelDifferent typesHigh resolution
2013
Adaptive filtering of microarray gene expression data based on Gaussian mixture decomposition
Marczyk M, Jaksik R, Polanski A, Polanska J. Adaptive filtering of microarray gene expression data based on Gaussian mixture decomposition. BMC Bioinformatics 2013, 14: 101. PMID: 23510016, PMCID: PMC3637832, DOI: 10.1186/1471-2105-14-101.Peer-Reviewed Original ResearchConceptsGaussian mixture decompositionFalse discoveriesMicroarray gene expression dataNon-informative genesAdaptive filteringSample meanAdaptive methodSample varianceGaussian componentsMixture decompositionGene filteringEarlier paperGene expression dataFilteringOptimal threshold valuePrevious methodsMicroarray experimentsNew methodTwo-step procedureThreshold valueCorrection methodPower of detectionImportant parametersSecond stepMicroarray data