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Peeken, J.C.* ; Bernhofer, M.* ; Wiestler, B.* ; Goldberg, T.* ; Cremers, D.* ; Rost, B.* ; Wilkens, J.J.* ; Combs, S.E. ; Nüsslin, F.*

Radiomics in radiooncology - Challenging the medical physicist.

Phys. Med. 48, 27-36 (2018)
DOI Verlagsversion bestellen
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Flatworms of the species Schmidtea mediterranea are immortal-adult animals contain a large pool of pluripotent stem cells that continuously differentiate into all adult cell types. Therefore, single-cell transcriptome profiling of adult animals should reveal mature and progenitor cells. By combining perturbation experiments, gene expression analysis, a computational method that predicts future cell states from transcriptional changes, and a lineage reconstruction method, we placed all major cell types onto a single lineage tree that connects all cells to a single stem cell compartment. We characterized gene expression changes during differentiation and discovered cell types important for regeneration. Our results demonstrate the importance of single-cell transcriptome analysis for mapping and reconstructing fundamental processes of developmental and regenerative biology at high resolution.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Review
Schlagwörter Radiomics ; Radiogenomics ; Machine Learning ; Neural Networks ; Convolutional Neural Network; Planarian Schmidtea-mediterranea; Stem-cells; Rna-seq; Gene-expression; Regeneration; Pluripotency; Trajectories; Organism; Tissues; System
ISSN (print) / ISBN 1120-1797
e-ISSN 1724-191X
Quellenangaben Band: 48, Heft: , Seiten: 27-36 Artikelnummer: , Supplement: ,
Verlag Elsevier
Verlagsort 1200 New York Ave, Nw, Washington, Dc 20005 Usa
Begutachtungsstatus Peer reviewed