NSforest specifications


Unique identifier OMICS_27112
Name NSforest

Publication for NSforest

NSforest citation


Cell type discovery using single cell transcriptomics: implications for ontological representation

Hum Mol Genet
PMCID: 5946857
PMID: 29590361
DOI: 10.1093/hmg/ddy100

[…] ssin the CLA specimen source description(anatomic structure + species).In order to identify the set of necessary and sufficient marker genes from an sc/snRNAseq experiment, we have developed a method—NSforest—that utilizes a random forest of decision trees machine learning approach. The methodology described here is unique in that it determines the minimum number of differentiallyexpressed genes, […]

NSforest institution(s)
J. Craig Venter Institute, La Jolla, CA, USA; Allen Institute for Brain Science, Seattle, WA, USA; Department of Biomedical Informatics, University at Buffalo, Buffalo, NY, USA; European Molecular Biology Laboratory - European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, UK; Department of Pathology, University of California San Diego, La Jolla, CA, USA
NSforest funding source(s)
Supported by the Allen Institute for Brain Science, the JCVI Innovation Fund, the U.S. National Institutes of Health R21-AI122100 and U19-AI118626, and the California Institute for Regenerative Medicine GC1R-06673-B.

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