Theis FJ - Search Results

1

Predicting cellular responses to complex perturbations in high-throughput screens.

Lotfollahi M, Klimovskaia Susmelj A, De Donno C, Hetzel L, Ji Y, Ibarra IL, Srivatsan SR, Naghipourfar M, Daza RM, Martin B, Shendure J, McFaline-Figueroa JL, Boyeau P, Wolf FA, Yakubova N, Günnemann S, Trapnell C, Lopez-Paz D, Theis FJ. Lotfollahi M, et al. Among authors: theis fj. Mol Syst Biol. 2023 Jun 12;19(6):e11517. doi: 10.15252/msb.202211517. Epub 2023 May 8. Mol Syst Biol. 2023. PMID: 37154091 Free PMC article.

2

Diffusion pseudotime robustly reconstructs lineage branching.

Haghverdi L, Büttner M, Wolf FA, Buettner F, Theis FJ. Haghverdi L, et al. Among authors: theis fj. Nat Methods. 2016 Oct;13(10):845-8. doi: 10.1038/nmeth.3971. Epub 2016 Aug 29. Nat Methods. 2016. PMID: 27571553

3

Model-based branching point detection in single-cell data by K-branches clustering.

Chlis NK, Wolf FA, Theis FJ. Chlis NK, et al. Among authors: theis fj. Bioinformatics. 2017 Oct 15;33(20):3211-3219. doi: 10.1093/bioinformatics/btx325. Bioinformatics. 2017. PMID: 28582478 Free PMC article.

4

Reconstructing cell cycle and disease progression using deep learning.

Eulenberg P, Köhler N, Blasi T, Filby A, Carpenter AE, Rees P, Theis FJ, Wolf FA. Eulenberg P, et al. Among authors: theis fj. Nat Commun. 2017 Sep 6;8(1):463. doi: 10.1038/s41467-017-00623-3. Nat Commun. 2017. PMID: 28878212 Free PMC article.

5

SCANPY: large-scale single-cell gene expression data analysis.

Wolf FA, Angerer P, Theis FJ. Wolf FA, et al. Among authors: theis fj. Genome Biol. 2018 Feb 6;19(1):15. doi: 10.1186/s13059-017-1382-0. Genome Biol. 2018. PMID: 29409532 Free PMC article.

6

Cell type atlas and lineage tree of a whole complex animal by single-cell transcriptomics.

Plass M, Solana J, Wolf FA, Ayoub S, Misios A, Glažar P, Obermayer B, Theis FJ, Kocks C, Rajewsky N. Plass M, et al. Among authors: theis fj. Science. 2018 May 25;360(6391):eaaq1723. doi: 10.1126/science.aaq1723. Epub 2018 Apr 19. Science. 2018. PMID: 29674432

7

A test metric for assessing single-cell RNA-seq batch correction.

Büttner M, Miao Z, Wolf FA, Teichmann SA, Theis FJ. Büttner M, et al. Among authors: theis fj. Nat Methods. 2019 Jan;16(1):43-49. doi: 10.1038/s41592-018-0254-1. Epub 2018 Dec 20. Nat Methods. 2019. PMID: 30573817

8

PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells.

Wolf FA, Hamey FK, Plass M, Solana J, Dahlin JS, Göttgens B, Rajewsky N, Simon L, Theis FJ. Wolf FA, et al. Among authors: theis fj. Genome Biol. 2019 Mar 19;20(1):59. doi: 10.1186/s13059-019-1663-x. Genome Biol. 2019. PMID: 30890159 Free PMC article.

9

scGen predicts single-cell perturbation responses.

Lotfollahi M, Wolf FA, Theis FJ. Lotfollahi M, et al. Among authors: theis fj. Nat Methods. 2019 Aug;16(8):715-721. doi: 10.1038/s41592-019-0494-8. Epub 2019 Jul 29. Nat Methods. 2019. PMID: 31363220

10

Generalizing RNA velocity to transient cell states through dynamical modeling.

Bergen V, Lange M, Peidli S, Wolf FA, Theis FJ. Bergen V, et al. Among authors: theis fj. Nat Biotechnol. 2020 Dec;38(12):1408-1414. doi: 10.1038/s41587-020-0591-3. Epub 2020 Aug 3. Nat Biotechnol. 2020. PMID: 32747759

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