2023
The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks
Ben Guebila M, Wang T, Lopes-Ramos C, Fanfani V, Weighill D, Burkholz R, Schlauch D, Paulson J, Altenbuchinger M, Shutta K, Sonawane A, Lim J, Calderer G, van IJzendoorn D, Morgan D, Marin A, Chen C, Song Q, Saha E, DeMeo D, Padi M, Platig J, Kuijjer M, Glass K, Quackenbush J. The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks. Genome Biology 2023, 24: 45. PMID: 36894939, PMCID: PMC9999668, DOI: 10.1186/s13059-023-02877-1.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsComputational BiologyGene Regulatory NetworksHumansMultiomicsNeoplasmsSoftware
2020
Sex Differences in Gene Expression and Regulatory Networks across 29 Human Tissues
Lopes-Ramos C, Chen C, Kuijjer M, Paulson J, Sonawane A, Fagny M, Platig J, Glass K, Quackenbush J, DeMeo D. Sex Differences in Gene Expression and Regulatory Networks across 29 Human Tissues. Cell Reports 2020, 31: 107795. PMID: 32579922, PMCID: PMC7898458, DOI: 10.1016/j.celrep.2020.107795.Peer-Reviewed Original ResearchMeSH KeywordsChromosomes, Human, XDNA-Binding ProteinsFemaleGene Expression RegulationGene Regulatory NetworksHumansMaleOrgan SpecificitySex CharacteristicsTranscription FactorsConceptsGene regulatory networksTranscription factorsGenotype-Tissue ExpressionRegulatory networksArchitecture of gene regulatory networksRepertoire of transcription factorsSets of transcription factorsRegulatory network structureWhole-genome expression profilingTissue-related functionsGenes associated with Parkinson's diseaseHuman healthy tissuesGene regulationGene expressionMolecular basisSystems-based analysisExpression profilesGenesAlzheimer's diseaseRegulatory processesHuman tissuesExpressionTranscriptionTissueSex differences
2018
Cancer subtype identification using somatic mutation data
Kuijjer M, Paulson J, Salzman P, Ding W, Quackenbush J. Cancer subtype identification using somatic mutation data. British Journal Of Cancer 2018, 118: 1492-1501. PMID: 29765148, PMCID: PMC5988673, DOI: 10.1038/s41416-018-0109-7.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkers, TumorComputational BiologyData CurationDatabases, GeneticFemaleGene Regulatory NetworksHumansMutationNeoplasmsPrincipal Component AnalysisPrognosisConceptsSomatic mutation dataAssociated with mutationsNext-generation sequencing technologiesMutation dataBiological pathwaysSets of mutationsSignal transduction pathwaysCancer typesPan-cancer subtypesSequencing technologiesPhenotypic dataCancer Genome AtlasCancer subtype identificationTransduction pathwaysMutational driversSomatic mutationsSubgroup of patientsTargeted treatment optionsMutationsMutation patternsGenome AtlasClassification of patientsMutation profilesPrimary tumorPrognostic subtypes
2017
Understanding Tissue-Specific Gene Regulation
Sonawane A, Platig J, Fagny M, Chen C, Paulson J, Lopes-Ramos C, DeMeo D, Quackenbush J, Glass K, Kuijjer M. Understanding Tissue-Specific Gene Regulation. Cell Reports 2017, 21: 1077-1088. PMID: 29069589, PMCID: PMC5828531, DOI: 10.1016/j.celrep.2017.10.001.Peer-Reviewed Original ResearchMeSH KeywordsGene Regulatory NetworksGenome, HumanHumansOrgan SpecificityProtein Interaction MapsTranscription FactorsTranscriptional ActivationTranscriptomeConceptsTissue specificityTissue-specific gene regulationGenotype-Tissue Expression projectControl tissue specificityTissue-specific genesTranscription factor targetsTissue-specific functionsGene expression patternsGene set enrichment analysisTissue-specific mannerTissue-specific processesInvestigate gene expressionGene regulationRegulatory interactionsTranscriptional controlTranscription factor expressionTranscription factorsExpression projectEnrichment analysisGene expressionExpression patternsGenesRegulation nodeFactor targetsTranscriptionRegulatory network changes between cell lines and their tissues of origin
Lopes-Ramos C, Paulson J, Chen C, Kuijjer M, Fagny M, Platig J, Sonawane A, DeMeo D, Quackenbush J, Glass K. Regulatory network changes between cell lines and their tissues of origin. BMC Genomics 2017, 18: 723. PMID: 28899340, PMCID: PMC5596945, DOI: 10.1186/s12864-017-4111-x.Peer-Reviewed Original ResearchMeSH KeywordsCell CycleCell LineGene Expression ProfilingGene Regulatory NetworksHumansOrgan SpecificityConceptsLymphoblastoid cell linesCell linesTranscription factor (TFChIP-seq dataRegulatory network changesRNA-seq dataTissue of originRegulatory network analysisCell cycle genesPrimary tissuesGene expression analysisEpstein-Barr virus-transformed lymphoblastoid cell linesChIP-seqVirus-transformed lymphoblastoid cell linesTF-targetRNA-seqGTEx projectTF regulationCycle genesTranscriptomic differencesBackgroundCell linesTranscript levelsExpression analysisFibroblast cell lineNetwork analysisExploring regulation in tissues with eQTL networks
Fagny M, Paulson J, Kuijjer M, Sonawane A, Chen C, Lopes-Ramos C, Glass K, Quackenbush J, Platig J. Exploring regulation in tissues with eQTL networks. Proceedings Of The National Academy Of Sciences Of The United States Of America 2017, 114: e7841-e7850. PMID: 28851834, PMCID: PMC5604022, DOI: 10.1073/pnas.1707375114.Peer-Reviewed Original ResearchConceptsExpression quantitative trait lociEQTL networksGenetic variantsCoherent biological processesImpact of genetic variantsActive chromatin regionsQuantitative trait lociTissue-specific processesGene expression levelsChromatin regionsGroup genesTrait lociComplex phenotypesRegulatory potentialGenotype to phenotype mappingPhenotype mappingBiological processesRegulatory functionsExpression levelsGenesRegulatory impactVariantsLociBipartite networksPhenotypeEstimating gene regulatory networks with pandaR
Schlauch D, Paulson J, Young A, Glass K, Quackenbush J. Estimating gene regulatory networks with pandaR. Bioinformatics 2017, 33: 2232-2234. PMID: 28334344, PMCID: PMC5870629, DOI: 10.1093/bioinformatics/btx139.Peer-Reviewed Original Research
2015
Methylome Analysis in Chickens Immunized with Infectious Laryngotracheitis Vaccine
Carrillo J, He Y, Luo J, Menendez K, Tablante N, Zhao K, Paulson J, Li B, Song J. Methylome Analysis in Chickens Immunized with Infectious Laryngotracheitis Vaccine. PLOS ONE 2015, 10: e0100476. PMID: 26107953, PMCID: PMC4481310, DOI: 10.1371/journal.pone.0100476.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsChickensCpG IslandsDNA MethylationEukaryotic Initiation Factor-2Gene Regulatory NetworksGenomeHerpesvirus 1, GallidImmune System DiseasesInflammationRibosomal Protein S6 Kinases, 70-kDaRNA Processing, Post-TranscriptionalSignal TransductionTOR Serine-Threonine KinasesTranscription Initiation SiteVaccinesConceptsTranscription start siteMethyl-CpG binding domain protein-enriched genome sequencingDNA methylationProtein-enriched genome sequencingRNA post-transcriptional modificationsIdentified canonical pathwaysRegulation of eIF4Post-transcriptional modificationsDifferentially expressed genesAxonal guidance signalingGlobal DNA methylationHypermethylated DMRsP70S6K signalingGenome sequenceStart siteMethylome analysisCpG islandsGene networksMethyl-CpGEIF2 signalingCanonical pathwaysK signalingGenesMTOR signalingInfectious laryngotracheitis