Skip to main content
construction release_alert
The Scholars Team is working with OIT to resolve some issues with the Scholars search index
cancel
bioRxiv

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

Publication ,  Preprint
Pratapa, A; Jalihal, A; Law, J; Bharadwaj, A; Murali, TM
2019

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

DOI

Publication Date

2019
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Pratapa, A., Jalihal, A., Law, J., Bharadwaj, A., & Murali, T. M. (2019). Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data. bioRxiv. https://doi.org/10.1101/642926
Pratapa, Aditya, Amogh Jalihal, Jeffrey Law, Aditya Bharadwaj, and T. M. Murali. “Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data.” BioRxiv, 2019. https://doi.org/10.1101/642926.
Pratapa A, Jalihal A, Law J, Bharadwaj A, Murali TM. Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data. bioRxiv. 2019.
Pratapa, Aditya, et al. “Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data.” BioRxiv, 2019. Epmc, doi:10.1101/642926.
Pratapa A, Jalihal A, Law J, Bharadwaj A, Murali TM. Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data. bioRxiv. 2019.

DOI

Publication Date

2019