A Critical Survey of Deconvolution Methods for Separating Cell Types in Complex Tissues

Proceedings of the IEEE

Volumn 105, Issue 2, 2017, Pages 340-366

  Mohammadi, Shahin ^a   Zuckerman, Neta ^b,c   Goldsmith, Andrea ^b   Grama, Ananth ^a  

^a Purdue University   (United States)

^b Stanford University   (United States)

^c GENENTECH INC   (United States)

Author keywords

Deconvolution; feature selection; gene expression; linear regression; loss function; range filtering; regularization

Indexed keywords

AUDIO ACOUSTICS; CELL CULTURE; CELL PROLIFERATION; FEATURE EXTRACTION; FILTRATION; FUNCTION EVALUATION; GENE EXPRESSION; HISTOLOGY; HYPERSPECTRAL IMAGING; LINEAR REGRESSION; MIXING; MIXTURES; SPECTROSCOPY; SURVEYS; TISSUE;

DECONVOLUTION METHOD; DECONVOLUTION PROBLEM; DECONVOLUTION TECHNIQUES; DIVERSE APPLICATIONS; LOSS FUNCTIONS; OPTIMIZATION PROBLEMS; QUANTITATIVE CHARACTERIZATION; REGULARIZATION;

DECONVOLUTION;

EID: 85014894756     PISSN: 00189219     EISSN: 15582256     Source Type: Journal    
DOI: 10.1109/JPROC.2016.2607121     Document Type: Article

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