Lin, Eugene, Mukherjee, Sudipto, and Kannan, Sreeram. A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis. Retrieved from https://par.nsf.gov/biblio/10145951. BMC Bioinformatics 21.1 Web. doi:10.1186/s12859-020-3401-5.
Lin, Eugene, Mukherjee, Sudipto, & Kannan, Sreeram. A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis. BMC Bioinformatics, 21 (1). Retrieved from https://par.nsf.gov/biblio/10145951. https://doi.org/10.1186/s12859-020-3401-5
Lin, Eugene, Mukherjee, Sudipto, and Kannan, Sreeram.
"A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis". BMC Bioinformatics 21 (1). Country unknown/Code not available. https://doi.org/10.1186/s12859-020-3401-5.https://par.nsf.gov/biblio/10145951.
@article{osti_10145951,
place = {Country unknown/Code not available},
title = {A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis},
url = {https://par.nsf.gov/biblio/10145951},
DOI = {10.1186/s12859-020-3401-5},
abstractNote = {},
journal = {BMC Bioinformatics},
volume = {21},
number = {1},
author = {Lin, Eugene and Mukherjee, Sudipto and Kannan, Sreeram},
}
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