Author

G. Popova

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioengineering· 1 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Organism:human· 2 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

A. Busia· 1 shared A. Carneiro· 1 shared A. Koc· 1 shared C. Fannjiang· 1 shared D. H. Brookes· 1 shared D. Shin· 1 shared D. V. Schaffer· 1 shared D. ZHU· 1 shared

Activity by Year

2021-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperBioengineering

A. Busia

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2 papers

Recent·Most cited

Cancer BiologybioRxivMar 10, 2023

Reconstructing the regulatory programs underlying the phenotypic plasticity of neural cancers

I. Larsson, F. Held, G. Popova…·S. Nelander

This study reconstructs regulatory programs in neural cancers using scRNA-seq data to identify therapeutic targets and transcription factors involved in tumor cell states.

DOI 10.1038/s41467-024-53954-3

humanscRNA-seq

BioengineeringbioRxivNov 2, 2021

Optimal trade-off control in machine learning-based library design, with application to adeno-associated virus (AAV) for gene therapy

D. ZHU, D. H. Brookes, A. Busia…·D. V. Schaffer

This paper develops a machine learning method to design more effective AAV libraries with better packaging capabilities and diversity, achieving higher success rates in gene therapy applications.

DOI 10.1126/sciadv.adj3786

humanmachine learning (classical)