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Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data

This repository contains input files from the synthetic, curated, and processed experimental single-cell gene expression datasets used in BEELINE. New in version 4:1) We are updating the configuration files and directory structure for the BEELINE v1.1 release. <

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CreatorAditya Pratapa
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Published2020-03-27
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DOI10.5281/zenodo.19009603
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Downloads6,849
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Licensecc-by-nc-4.0
File Size266.2 MB
Data TypeDataset
Published2020
Licensecc-by-nc-4.0
Total Views11,326
Total Downloads6,849

This repository contains input files from the synthetic, curated, and processed experimental single-cell gene expression datasets used in BEELINE.

New in version 4:
1) We are updating the configuration files and directory structure for the BEELINE v1.1 release.

2) PlotSyntheticNetworks.yaml and PlotCuratedNetworks.yaml can be used to recreate Figures 2 and 4, respectively, from the original paper.

3) This version will not work with versions of BEELINE before BEELINE v1.1. Use version 3 of this dataset if you are using code from before 2026/03/13.

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Benchmarking algorithms for gene regulatory network inference from… (Full Dataset)266.2 MB
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Files are hosted on the source repository. Click download to access the full dataset.

Aditya Pratapa (2020). Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data. https://doi.org/10.5281/zenodo.19009603