Random forest based similarity learning for single cell RNA sequencing data-Reference-Cited by-同舟云学术

Random forest based similarity learning for single cell RNA sequencing data

Published:2018-06-27 Issue:13 Volume:34 Page:i79-i88
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Pouyan Maziyar Baran¹,Kostka Dennis¹²

Affiliation:

1. Department of Developmental Biology, University of Pittsburgh, Pittsburgh, PA, USA

2. Department for Computational and Systems Biology, Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA

Funder

National Institutes of Health

University of Pittsburgh School of Medicine

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

http://academic.oup.com/bioinformatics/article-pdf/34/13/i79/25098553/bty260.pdf

Reference50 articles.

1. Psychrophilic proteases dramatically reduce single cell RNA-seq artifacts: a molecular atlas of kidney development;Adam;Development,2017

2. Random forests;Breiman;Mach. Learn,2001

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