2022
CINS: Cell Interaction Network inference from Single cell expression data
Yuan Y, Cosme C, Adams TS, Schupp J, Sakamoto K, Xylourgidis N, Ruffalo M, Li J, Kaminski N, Bar-Joseph Z. CINS: Cell Interaction Network inference from Single cell expression data. PLOS Computational Biology 2022, 18: e1010468. PMID: 36095011, PMCID: PMC9499239, DOI: 10.1371/journal.pcbi.1010468.Peer-Reviewed Original ResearchConceptsCell type interactionsSingle-cell expression dataSingle-cell RNA-seq dataRNA-seq dataScRNA-seq experimentsCell-cell interactionsExpression dataCell typesMouse datasetsNetwork inferenceCell interactionsInteraction predictionNetwork analysisInference pipelineGenesCINSProteinInteractionBayesian network analysisBronchial epithelium epithelial-mesenchymal plasticity forms aberrant basaloid-like cells in vitro
Uthaya Kumar DB, Motakis E, Yurieva M, Kohar V, Martinek J, Wu TC, Khoury J, Grassmann J, Lu M, Palucka K, Kaminski N, Koff JL, Williams A. Bronchial epithelium epithelial-mesenchymal plasticity forms aberrant basaloid-like cells in vitro. American Journal Of Physiology - Lung Cellular And Molecular Physiology 2022, 322: l822-l841. PMID: 35438006, PMCID: PMC9142163, DOI: 10.1152/ajplung.00254.2021.Peer-Reviewed Original ResearchConceptsProtein codingEpithelial-mesenchymal transitionLncRNA genesEMT inductionSingle-cell RNA sequencingSingle-cell RNA-seq dataEpithelial-mesenchymal plasticityRNA-seq dataMechanisms of EMTSingle-cell levelEpithelial cell typesRole of EMTTranscriptional reprogrammingHuman bronchial epithelial cellsRNA genesEMT gene signatureTranscriptional changesTranscriptional differencesRNA sequencingSpecific lncRNAsBronchial epithelial cellsDifferential expressionMyofibroblast conversionCell typesGenes
2021
A Markov random field model for network-based differential expression analysis of single-cell RNA-seq data
Li H, Zhu B, Xu Z, Adams T, Kaminski N, Zhao H. A Markov random field model for network-based differential expression analysis of single-cell RNA-seq data. BMC Bioinformatics 2021, 22: 524. PMID: 34702190, PMCID: PMC8549347, DOI: 10.1186/s12859-021-04412-0.Peer-Reviewed Original ResearchConceptsMarkov random field modelRandom field modelMean field-like approximationField modelSpecific DEGsExpectation maximizationSingle-cell sequencing technologiesProtein-coding genesRNA sequencing data setsSingle-cell RNA-seq dataCell-type levelCell typesGibbs samplerSingle-cell RNA sequencing data setsCell-cell networksDifferential expression analysisRNA-seq dataGene network informationStatistical powerType I error ratesDifferent expression levelsMRF modelI error rateModel parametersBiological networks
2019
Integrating multiomics longitudinal data to reconstruct networks underlying lung development
Ding J, Ahangari F, Espinoza CR, Chhabra D, Nicola T, Yan X, Lal CV, Hagood JS, Kaminski N, Bar-Joseph Z, Ambalavanan N. Integrating multiomics longitudinal data to reconstruct networks underlying lung development. American Journal Of Physiology - Lung Cellular And Molecular Physiology 2019, 317: l556-l568. PMID: 31432713, PMCID: PMC6879899, DOI: 10.1152/ajplung.00554.2018.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsAnimals, NewbornChildChild, PreschoolDNA MethylationEpigenesis, GeneticFemaleGene Expression ProfilingGene Expression Regulation, DevelopmentalGene Regulatory NetworksHigh-Throughput Nucleotide SequencingHumansImmunity, InnateInfantInfant, NewbornLungMaleMiceMice, Inbred C57BLMicroRNAsOrganogenesisProteomicsPulmonary AlveoliRNA, MessengerSingle-Cell AnalysisTranscriptomeConceptsSingle-cell RNA-seq dataLung developmentDynamic regulatory networksOmics data setsRNA-seq dataIndividual cell typesHuman lung developmentRegulatory networksDNA methylationLaser capture microdissectionEpigenetic changesExpression trajectoriesKey pathwaysCell typesActive pathwaysCapture microdissectionRegulatorKey eventsInnate immunityNew insightsSpecific key eventsPathwayComprehensive understandingProteomicsMethylation
2018
Reconstructing differentiation networks and their regulation from time series single-cell expression data
Ding J, Aronow BJ, Kaminski N, Kitzmiller J, Whitsett JA, Bar-Joseph Z. Reconstructing differentiation networks and their regulation from time series single-cell expression data. Genome Research 2018, 28: 383-395. PMID: 29317474, PMCID: PMC5848617, DOI: 10.1101/gr.225979.117.Peer-Reviewed Original ResearchTranscription factorsSingle-cell expression dataSingle-cell RNA-seq dataRNA-seq dataDiverse cell populationsGene expression levelsDifferent cell typesStages of organogenesisCell fateDescendant cellsDifferentiation networkExpression similarityKey regulatorRegulatory informationExpression dataCell typesProgenitor cellsCell trajectoriesExpression levelsCell populationsDevelopmental dataCellsLineagesOrganogenesisRegulator