Biophysical modeling with variational autoencoders for bimodal, single-cell RNA sequencing data.

Journal

bioRxiv : the preprint server for biology
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187

Informations de publication

Date de publication:
02 May 2023
Historique:
pubmed: 31 1 2023
medline: 31 1 2023
entrez: 30 1 2023
Statut: epublish

Résumé

We motivate and present

Identifiants

DOI: 10.1101/2023.01.13.523995 PMID: 36712140 PMC: PMC9882246
pubmed: 36712140
doi: 10.1101/2023.01.13.523995
pmc: PMC9882246
pii:
doi:

Types de publication

Preprint

Langues

eng

Subventions

Organisme : NIGMS NIH HHS
ID : T32 GM007377
Pays : United States
Organisme : NIMH NIH HHS
ID : U19 MH114830
Pays : United States
Organisme : NHGRI NIH HHS
ID : UM1 HG012077
Pays : United States

Auteurs

Maria Carilli (M)

Division of Biology and Biological Engineering, California Institute of Technology.

Gennady Gorin (G)

Division of Chemistry and Chemical Engineering, California Institute of Technology.

Yongin Choi (Y)

Biomedical Engineering Graduate Group, University of California, Davis.
Genome Center, University of California, Davis.

Tara Chari (T)

Division of Biology and Biological Engineering, California Institute of Technology.

Lior Pachter (L)

Division of Biology and Biological Engineering, California Institute of Technology.
Department of Computing and Mathematical Sciences, California Institute of Technology.

Classifications MeSH