scAEGAN: Unification of single-cell genomics data by adversarial learning of latent space correspondences.

Khan, Sumeer Ahmad; Lehmann, Robert; Martinez-de-Morentin, Xabier; Maillo, Alberto; Lagani, Vincenzo; Kiani, Narsis A; Gomez-Cabrero, David; Tegner, Jesper

Khan, Sumeer Ahmad; Lehmann, Robert; Martinez-de-Morentin, Xabier; Maillo, Alberto; Lagani, Vincenzo; Kiani, Narsis A; Gomez-Cabrero, David; Tegner, Jesper.

Affiliation

Khan SA; Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.
Lehmann R; Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.
Martinez-de-Morentin X; Translational Bioinformatics Unit, Navarrabiomed, Complejo Hospitalario de Navarra (CHN), Universidad Pública de Navarra (UPNA), IdiSNA, Pamplona, Spain.
Maillo A; Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.
Lagani V; Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.
Kiani NA; Department of Oncology and Pathology, Algorithmic Dynamic Lab, Karolinska Institute, Stockholm, Sweden.
Gomez-Cabrero D; Department of Medicine, Unit of Computational Medicine, Center for Molecular Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
Tegner J; Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.

PLoS One ; 18(2): e0281315, 2023.

Article de En | MEDLINE | ID: mdl-36735690

Sujet(s)

Texte intégral

Ajouter à My VHL

Imprimer

XML

PubMed Links

Recherche sur Google

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Analyse de profil d'expression de gènes / Analyse sur cellule unique Langue: En Journal: PLoS One Sujet du journal: CIENCIA / MEDICINA Année: 2023 Type de document: Article Pays d'affiliation: Arabie saoudite

Texte intégral

Ajouter à My VHL

Imprimer

XML

PubMed Links

Recherche sur Google