Výsledky vyhledávání - "Gene Expression Profiling - methods"

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    Zdroj: Nat Cardiovasc Res
    Nature cardiovascular research 3(10), 1217-1235 (2024). doi:10.1038/s44161-024-00544-7
    Nature cardiovascular research, 3(10):1217-1235
    Nature Cardiovascular Research

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    Zdroj: Genome Biol
    Genome Biology, Vol 26, Iss 1, Pp 1-21 (2025)
    Shi, M, Méar, L, Karlsson, M, Álvez, M B, Digre, A, Schutten, R, Katona, B, Vuu, J, Lindström, E, Hikmet, F, Jin, H, Yuan, M, Li, X, Yang, H, Song, X, Sjöstedt, E, Edfors, F, Oksvold, P, von Feilitzen, K, Zwahlen, M, Forsberg, M, Johansson, F, Mulder, J, Hökfelt, T, Luo, Y, Butler, L, Zhong, W, Mardinoglu, A, Sivertsson, Å, Ponten, F, Fagerberg, L, Lindskog, C, Uhlén, M & Zhang, C 2025, 'A resource for whole-body gene expression map of human tissues based on integration of single cell and bulk transcriptomics', Genome Biology, vol. 26, 152. https://doi.org/10.1186/s13059-025-03616-4
    Shi, M, Méar, L, Karlsson, M, Álvez, M B, Digre, A, Schutten, R, Katona, B, Vuu, J, Lindström, E, Hikmet, F, Jin, H, Yuan, M, Li, X, Yang, H, Song, X, Sjöstedt, E, Edfors, F, Oksvold, P, von Feilitzen, K, Zwahlen, M, Forsberg, M, Johansson, F, Mulder, J, Hökfelt, T, Luo, Y, Butler, L, Zhong, W, Mardinoglu, A, Sivertsson, Å, Ponten, F, Fagerberg, L, Lindskog, C, Uhlén, M & Zhang, C 2025, 'A resource for whole-body gene expression map of human tissues based on integration of single cell and bulk transcriptomics', Genome Biology, vol. 26, no. 1, 152, pp. 152. https://doi.org/10.1186/s13059-025-03616-4

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    Zdroj: Breast Cancer Res Treat

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    Zdroj: Acta Neuropathol Commun
    Acta Neuropathologica Communications, Vol 13, Iss 1, Pp 1-12 (2025)

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    Přispěvatelé: Wang, Xiaoxiao Venet, David Lifrange, Frédéric a další

    Zdroj: Nat Commun
    Nature Communications, Vol 15, Iss 1, Pp 1-22 (2024)

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    Zdroj: Liao , L , Madan , E , Palma , A M , Kim , H , Kumar , A , Bhoopathi , P , Winn , R , Trevino , J , Fisher , P , Brakebusch , C H , Kim , G , Kim , J , Gogna , R & Won , K J 2025 , ' SC2Spa : a deep learning based approach to map transcriptome to spatial origins at cellular resolution ' , BMC Bioinformatics , vol. 26 , no. 1 , 148 . https://doi.org/10.1186/s12859-025-06173-6

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    Autoři: Liu, Muyi Zheng, Suilan Li, Hongmin a další

    Zdroj: PLoS One

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    Relation: https://doi.org/10.1371/journal.pone.0318151; Liu, M., Zheng, S., Li, H., Budowle, B., Wang, L., Lou, Z., & Ge, J. (2025). High resolution tissue and cell type identification via single cell transcriptomic profiling. PloS one, 20(3), e0318151. https://doi.org/10.1371/journal.pone.0318151; https://hdl.handle.net/20.500.12503/33050; 20

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    Zdroj: Stokholm, M N, Rabaglino, M B & Kadarmideen, H N 2024, ' GEDI: An R Package for Integration of Transcriptomic Data from Multiple Platforms for Bioinformatics Applications ', Current Protocols, vol. 4, e70046 . https://doi.org/10.1002/cpz1.70046
    Stokholm, M N, Rabaglino, M B & Kadarmideen, H N 2024, 'GEDI: An R Package for Integration of Transcriptomic Data from Multiple Platforms for Bioinformatics Applications', Current protocols, vol. 4, no. 10, e70046. https://doi.org/10.1002/cpz1.70046

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