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Gayoso, A.* ; Lopez, R.* ; Xing, G.* ; Boyeau, P.* ; Valiollah Pour Amiri, V.* ; Hong, J.* ; Wu, K.* ; Jayasuriya, M.* ; Mehlman, E.* ; Langevin, M.* ; Liu, Y.* ; Samaran, J.* ; Misrachi, G.* ; Nazaret, A.* ; Clivio, O.* ; Xu, C.* ; Ashuach, T.* ; Gabitto, M.* ; Lotfollahi, M. ; Svensson, V.* ; da Veiga Beltrame, E.* ; Kleshchevnikov, V.* ; Talavera-López, C.* ; Pachter, L.* ; Theis, F.J. ; Streets, A.* ; Jordan, M.I.* ; Regier, J.* ; Yosef, N.*

A Python library for probabilistic analysis of single-cell omics data.

Nat. Biotechnol. 40, 163-166 (2022)
DOI PMC
Open Access Green as soon as Postprint is submitted to ZB.
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Publication type Article: Journal article
Document type Scientific Article
ISSN (print) / ISBN 1087-0156
e-ISSN 1546-1696
Journal Nature Biotechnology
Quellenangaben Volume: 40, Issue: 2, Pages: 163-166 Article Number: , Supplement: ,
Publisher Nature Publishing Group
Publishing Place New York, NY
Reviewing status Peer reviewed
Institute(s) Institute of Computational Biology (ICB)
Grants NIH Training Grant
EPSRC Centre for Doctoral Training in Modern Statistics and Statistical Machine Learning
Chan-Zuckerberg Foundation Network
NIGMS of the National Institutes of Health