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dc.contributor.author Choi, Yoon Ha -
dc.contributor.author Kim, Jong Kyoung -
dc.date.accessioned 2019-03-29T02:34:54Z -
dc.date.available 2019-03-29T02:34:54Z -
dc.date.created 2019-03-29 -
dc.date.issued 2019-03 -
dc.identifier.issn 1016-8478 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/9682 -
dc.description.abstract Cell-to-cell variability in gene expression exists even in a homogeneous population of cells. Dissecting such cellular heterogeneity within a biological system is a prerequisite for understanding how a biological system is developed, homeo-statically regulated, and responds to external perturbations. Single-cell RNA sequencing (scRNA-seq) allows the quantitative and unbiased characterization of cellular heterogeneity by providing genome-wide molecular profiles from tens of thousands of individual cells. A major question in analyzing scRNA-seq data is how to account for the observed cell-to-cell variability. In this review, we provide an overview of scRNA-seq protocols, computational approaches for dissecting cellular heterogeneity, and future directions of single-cell transcriptomic analysis. -
dc.language English -
dc.publisher 한국분자세포생물학회 -
dc.title Dissecting Cellular Heterogeneity Using Single-Cell RNA Sequencing -
dc.type Article -
dc.identifier.doi 10.14348/molcells.2019.2446 -
dc.identifier.scopusid 2-s2.0-85064007878 -
dc.identifier.bibliographicCitation Molecules and Cells, v.42, no.3, pp.189 - 199 -
dc.identifier.kciid ART002447715 -
dc.description.isOpenAccess TRUE -
dc.subject.keywordAuthor cellular heterogeneity -
dc.subject.keywordAuthor RNA sequencing -
dc.subject.keywordAuthor singlecell -
dc.subject.keywordAuthor single-cell genomics -
dc.subject.keywordAuthor single-cell transcriptomics -
dc.subject.keywordPlus GENE-EXPRESSION -
dc.subject.keywordPlus TRANSCRIPTIONAL LANDSCAPE -
dc.subject.keywordPlus SEQ DATA -
dc.subject.keywordPlus GENOME -
dc.subject.keywordPlus QUANTIFICATION -
dc.subject.keywordPlus VISUALIZATION -
dc.subject.keywordPlus CHALLENGES -
dc.subject.keywordPlus CYTOMETRY -
dc.subject.keywordPlus INFERENCE -
dc.subject.keywordPlus IDENTITY -
dc.citation.endPage 199 -
dc.citation.number 3 -
dc.citation.startPage 189 -
dc.citation.title Molecules and Cells -
dc.citation.volume 42 -
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Department of New Biology Laboratory of Single-Cell Genomics 1. Journal Articles

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