Manifold learning-based methods for analyzing single-cell RNA-sequencing data

Current Opinion in Systems Biology

Volumn 7, Issue , 2018, Pages 36-46

  Moon, Kevin R ^a,b   Stanley, Jay S ^a,b   Burkhardt, Daniel ^a   van Dijk, David ^a,c   Wolf, Guy ^b   Krishnaswamy, Smita ^a,b,c  

^a YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b YALE UNIVERSITY   (United States)

^c Yale University   (United States)

Author keywords

Data mining; Gene regulatory networks; Imputation; Manifold learning; Pseudotime trends; Single cell RNA sequencing

Indexed keywords

ARTICLE; DATA ANALYSIS; DATA EXTRACTION; GENE EXPRESSION; GENE INTERACTION; GENE REGULATORY NETWORK; LEARNING ALGORITHM; MANIFOLD LEARNING; NOISE REDUCTION; RNA SEQUENCE; SINGLE CELL RNA SEQUENCING;

EID: 85045320368     PISSN: None     EISSN: 24523100     Source Type: Journal    
DOI: 10.1016/j.coisb.2017.12.008     Document Type: Review

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