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Cited by in F6Publishing
For: Xu Q, Georgiou G, Frölich S, van der Sande M, Veenstra GJC, Zhou H, van Heeringen SJ. ANANSE: An enhancer network-based computational approach for predicting key transcription factors in cell fate determination.. [DOI: 10.1101/2020.06.05.135798] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
Number Citing Articles
1 van der Sande M, Frölich S, van Heeringen SJ. Computational approaches to understand transcription regulation in development. Biochem Soc Trans 2023:BST20210145. [PMID: 36695505 DOI: 10.1042/BST20210145] [Reference Citation Analysis]
2 Kamal A, Arnold C, Claringbould A, Moussa R, Servaas NH, Kholmatov M, Daga N, Nogina D, Mueller-dott S, Reyes-palomares A, Palla G, Sigalova O, Bunina D, Pabst C, Zaugg JB. GRaNIE and GRaNPA: Inference and evaluation of enhancer-mediated gene regulatory networks applied to study macrophages.. [DOI: 10.1101/2021.12.18.473290] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
3 Tran A, Yang P, Yang JY, Ormerod JT. scREMOTE: Using multimodal single cell data to predict regulatory gene relationships and to build a computational cell reprogramming model.. [DOI: 10.1101/2021.10.11.463798] [Reference Citation Analysis]
4 Weinberger M, Simões FC, Sauka-spengler T, Riley PR. Distinct epicardial gene regulatory programmes drive development and regeneration of the zebrafish heart.. [DOI: 10.1101/2021.06.29.450229] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
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