2024
Identifying topologically associating domains using differential kernels
Maisuradze L, King M, Surovtsev I, Mochrie S, Shattuck M, O’Hern C. Identifying topologically associating domains using differential kernels. PLOS Computational Biology 2024, 20: e1012221. PMID: 39008525, PMCID: PMC11249266, DOI: 10.1371/journal.pcbi.1012221.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsChromatinComputational BiologyHumansImage Processing, Computer-AssistedConceptsTopologically associating domainsHi-C mapsFalse discovery rateChromatin conformation capture techniquesEnhancer-promoter interactionsLow false discovery rateSelf-interacting regionsStructure of chromatinRegulate gene expressionAverage contact probabilitiesHi-CLocus IDNA transcriptionGene expressionChromatinDiscovery rateContact probabilityBiological phenomenaState-of-the-artKernel-based techniqueComputer visionReplicationCorrelated changesDisease statesCapture techniques
2015
Oufti: an integrated software package for high‐accuracy, high‐throughput quantitative microscopy analysis
Paintdakhi A, Parry B, Campos M, Irnov I, Elf J, Surovtsev I, Jacobs-Wagner C. Oufti: an integrated software package for high‐accuracy, high‐throughput quantitative microscopy analysis. Molecular Microbiology 2015, 99: 767-777. PMID: 26538279, PMCID: PMC4752901, DOI: 10.1111/mmi.13264.Peer-Reviewed Original ResearchConceptsSingle-cell studiesOpen-source software packageGraphical user interfaceComplex subcellular organizationSoftware packageImage analysisUser interfaceMassive datasetsCellular functionsSubcellular organizationBacterial researchHigh-throughput analysisTouching cellsMicrobial cellsSubpixel precisionInteractive modulesComputational skillsComputational solutionPost-processing analysisPhenotypic variabilityFluorescence signalQuantitative microscopy analysisCell morphologyAutomated MeasurementConfluent samples