scENCORE: leveraging single-cell epigenetic data to predict chromatin conformation using graph embedding
Duan Z, Xu S, Srinivasan S, Hwang A, Lee C, Yue F, Gerstein M, Luan Y, Girgenti M, Zhang J. scENCORE: leveraging single-cell epigenetic data to predict chromatin conformation using graph embedding. Briefings In Bioinformatics 2024, 25: bbae096. PMID: 38493342, PMCID: PMC10944576, DOI: 10.1093/bib/bbae096.Peer-Reviewed Original ResearchConceptsA/B compartmentsEpigenetic dataChromatin interaction frequenciesCell type-specific mannerChromatin conformational changesGenome binsGenomic regionsChromatin conformationEukaryotic DNAChromatin compartmentsDynamic compartmentalizationRepressed stateGenetic blueprintTranscriptional programsTranscriptional changesChromatinConformational changesComplex tissuesInteraction frequencyCompartmentGenomeChromosomeStructural heterogeneityDNAA/BLess-is-more: selecting transcription factor binding regions informative for motif inference
Xu J, Gao J, Ni P, Gerstein M. Less-is-more: selecting transcription factor binding regions informative for motif inference. Nucleic Acids Research 2024, 52: e20-e20. PMID: 38214231, PMCID: PMC10899791, DOI: 10.1093/nar/gkad1240.Peer-Reviewed Original ResearchConceptsChIP-seq signalsChIP-seqGenomic regionsMotif inferenceTranscription factorsTargeting motifTranscription factor binding regionsChIP-seq datasetsNon-specific interactionsC-scoreDNA motifsBinding regionMotifTranscriptionTF signalingAccurate inferenceStronger signalSignalDNARegionTargetInteraction