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Page 1
An integrated cell atlas of the lung in health and disease.
Sikkema L, Ramírez-Suástegui C, Strobl DC, Gillett TE, Zappia L, Madissoon E, Markov NS, Zaragosi LE, Ji Y, Ansari M, Arguel MJ, Apperloo L, Banchero M, Bécavin C, Berg M, Chichelnitskiy E, Chung MI, Collin A, Gay ACA, Gote-Schniering J, Hooshiar Kashani B, Inecik K, Jain M, Kapellos TS, Kole TM, Leroy S, Mayr CH, Oliver AJ, von Papen M, Peter L, Taylor CJ, Walzthoeni T, Xu C, Bui LT, De Donno C, Dony L, Faiz A, Guo M, Gutierrez AJ, Heumos L, Huang N, Ibarra IL, Jackson ND, Kadur Lakshminarasimha Murthy P, Lotfollahi M, Tabib T, Talavera-López C, Travaglini KJ, Wilbrey-Clark A, Worlock KB, Yoshida M; Lung Biological Network Consortium; van den Berge M, Bossé Y, Desai TJ, Eickelberg O, Kaminski N, Krasnow MA, Lafyatis R, Nikolic MZ, Powell JE, Rajagopal J, Rojas M, Rozenblatt-Rosen O, Seibold MA, Sheppard D, Shepherd DP, Sin DD, Timens W, Tsankov AM, Whitsett J, Xu Y, Banovich NE, Barbry P, Duong TE, Falk CS, Meyer KB, Kropski JA, Pe'er D, Schiller HB, Tata PR, Schultze JL, Teichmann SA, Misharin AV, Nawijn MC, Luecken MD, Theis FJ. Sikkema L, et al. Among authors: lotfollahi m. Nat Med. 2023 Jun;29(6):1563-1577. doi: 10.1038/s41591-023-02327-2. Epub 2023 Jun 8. Nat Med. 2023. PMID: 37291214 Free PMC article.
scGen predicts single-cell perturbation responses.
Lotfollahi M, Wolf FA, Theis FJ. Lotfollahi M, et al. Nat Methods. 2019 Aug;16(8):715-721. doi: 10.1038/s41592-019-0494-8. Epub 2019 Jul 29. Nat Methods. 2019. PMID: 31363220
Machine learning for perturbational single-cell omics.
Ji Y, Lotfollahi M, Wolf FA, Theis FJ. Ji Y, et al. Among authors: lotfollahi m. Cell Syst. 2021 Jun 16;12(6):522-537. doi: 10.1016/j.cels.2021.05.016. Cell Syst. 2021. PMID: 34139164 Free article. Review.
Mapping single-cell data to reference atlases by transfer learning.
Lotfollahi M, Naghipourfar M, Luecken MD, Khajavi M, Büttner M, Wagenstetter M, Avsec Ž, Gayoso A, Yosef N, Interlandi M, Rybakov S, Misharin AV, Theis FJ. Lotfollahi M, et al. Nat Biotechnol. 2022 Jan;40(1):121-130. doi: 10.1038/s41587-021-01001-7. Epub 2021 Aug 30. Nat Biotechnol. 2022. PMID: 34462589 Free PMC article.
Squidpy: a scalable framework for spatial omics analysis.
Palla G, Spitzer H, Klein M, Fischer D, Schaar AC, Kuemmerle LB, Rybakov S, Ibarra IL, Holmberg O, Virshup I, Lotfollahi M, Richter S, Theis FJ. Palla G, et al. Among authors: lotfollahi m. Nat Methods. 2022 Feb;19(2):171-178. doi: 10.1038/s41592-021-01358-2. Epub 2022 Jan 31. Nat Methods. 2022. PMID: 35102346 Free PMC article.
A Python library for probabilistic analysis of single-cell omics data.
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 FJ, Streets A, Jordan MI, Regier J, Yosef N. Gayoso A, et al. Among authors: lotfollahi m. Nat Biotechnol. 2022 Feb;40(2):163-166. doi: 10.1038/s41587-021-01206-w. Nat Biotechnol. 2022. PMID: 35132262 No abstract available.
Best practices for single-cell analysis across modalities.
Heumos L, Schaar AC, Lance C, Litinetskaya A, Drost F, Zappia L, Lücken MD, Strobl DC, Henao J, Curion F; Single-cell Best Practices Consortium; Schiller HB, Theis FJ. Heumos L, et al. Nat Rev Genet. 2023 Aug;24(8):550-572. doi: 10.1038/s41576-023-00586-w. Epub 2023 Mar 31. Nat Rev Genet. 2023. PMID: 37002403 Free PMC article. Review.
The scverse project provides a computational ecosystem for single-cell omics data analysis.
Virshup I, Bredikhin D, Heumos L, Palla G, Sturm G, Gayoso A, Kats I, Koutrouli M; Scverse Community; Berger B, Pe'er D, Regev A, Teichmann SA, Finotello F, Wolf FA, Yosef N, Stegle O, Theis FJ. Virshup I, et al. Nat Biotechnol. 2023 May;41(5):604-606. doi: 10.1038/s41587-023-01733-8. Nat Biotechnol. 2023. PMID: 37037904 No abstract available.
22 results