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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. Nucleic Acids Res 2021:gkab598. [PMID: 34244796 DOI: 10.1093/nar/gkab598] [Cited by in Crossref: 10] [Cited by in F6Publishing: 11] [Article Influence: 5.0] [Reference Citation Analysis]
Number Citing Articles
1 Hong D, Lin H, Liu L, Shu M, Dai J, Lu F, Tong M, Huang J. Complexity of enhancer networks predicts cell identity and disease genes revealed by single-cell multi-omics analysis. Brief Bioinform 2023;24:bbac508. [PMID: 36464486 DOI: 10.1093/bib/bbac508] [Reference Citation Analysis]
2 Luna Velez MV, Neikes HK, Snabel RR, Quint Y, Qian C, Martens A, Veenstra GJC, Freeman MR, van Heeringen SJ, Vermeulen M. ONECUT2 regulates RANKL-dependent enterocyte and microfold cell differentiation in the small intestine; a multi-omics study. Nucleic Acids Res 2023:gkac1236. [PMID: 36625255 DOI: 10.1093/nar/gkac1236] [Reference Citation Analysis]
3 Heuts BMH, Arza-Apalategi S, Frölich S, Bergevoet SM, van den Oever SN, van Heeringen SJ, van der Reijden BA, Martens JHA. Identification of transcription factors dictating blood cell development using a bidirectional transcription network-based computational framework. Sci Rep 2022;12:18656. [PMID: 36333382 DOI: 10.1038/s41598-022-21148-w] [Reference Citation Analysis]
4 Luna Velez MV, Neikes HK, Snabel RR, Quint Y, Qian C, Martens A, Veenstra GJC, Freeman MR, van Heeringen SJ, Vermeulen M. ONECUT2 restricts Microfold cell numbers in the small intestine; a multi-omics study.. [DOI: 10.1101/2022.09.01.506202] [Reference Citation Analysis]
5 Smits JG, Cunha DL, Qu J, Owen N, Latta L, Szentmary N, Seitz B, Roux LN, Moosajee M, Aberdam D, van Heeringen SJ, Zhou H. Multi-omics analyses identify transcription factor interplay in corneal epithelial fate determination and disease.. [DOI: 10.1101/2022.07.13.499857] [Reference Citation Analysis]
6 Marazzi L, Shah M, Balakrishnan S, Patil A, Vera-Licona P. NETISCE: a network-based tool for cell fate reprogramming. NPJ Syst Biol Appl 2022;8:21. [PMID: 35725577 DOI: 10.1038/s41540-022-00231-y] [Reference Citation Analysis]
7 Perez-posada A, Lin C, Lin C, Chen Y, Gómez Skarmeta JL, Yu J, Su Y, Tena JJ. Insights into deuterostome evolution from the biphasic transcriptional programmes of hemichordates.. [DOI: 10.1101/2022.06.10.495707] [Reference Citation Analysis]
8 Guebila MB, Wang T, Lopes-ramos CM, Fanfani V, Weighill D, Burkholz R, Schlauch D, Paulson JN, Altenbuchinger M, Sonanwane A, Lim J, Calderer G, van Ijzendoorn D, Morgan D, Marin A, Chen C, Song A, Shutta K, Demeo D, Padi M, Platig J, Kuijjer ML, Glass K, Quackenbush J. The Network Zoo: a multilingual package for the inference and analysis of biological networks.. [DOI: 10.1101/2022.05.30.494077] [Reference Citation Analysis]
9 Tran A, Yang P, Yang JYH, Ormerod JT. scREMOTE: Using multimodal single cell data to predict regulatory gene relationships and to build a computational cell reprogramming model. NAR Genomics and Bioinformatics 2022;4:lqac023. [DOI: 10.1093/nargab/lqac023] [Reference Citation Analysis]
10 Marazzi L, Shah M, Balakrishnan S, Patil A, Vera-licona P. NETISCE: A Network-Based Tool for Cell Fate Reprogramming.. [DOI: 10.1101/2021.12.30.474582] [Reference Citation Analysis]