Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data
Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data
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Publisher
New York: Nature Publishing Group US
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Language
English
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New York: Nature Publishing Group US
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Scope and Contents
Contents
We present a systematic evaluation of state-of-the-art algorithms for inferring gene regulatory networks from single-cell transcriptional data. As the ground truth for assessing accuracy, we use synthetic networks with predictable trajectories, literature-curated Boolean models and diverse transcriptional regulatory networks. We develop a strategy...
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Full title
Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data
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TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7098173
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7098173
Other Identifiers
ISSN
1548-7091
E-ISSN
1548-7105
DOI
10.1038/s41592-019-0690-6
