MOESM3 of Tumour heterogeneity revealed by unsupervised decomposition of dynamic contrast-enhanced magnetic resonance imaging is associated with underlying gene expression patterns and poor survival in breast cancer patients
Type
Data FileKAUST Department
Computational Bioscience Research Center (CBRC)Computer Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Structural and Functional Bioinformatics Group
Date
2019Permanent link to this record
http://hdl.handle.net/10754/664821
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Additional file 3: Figure S2. Image features from the slow-flow kinetics subregion correlated with gene modules.Citation
Fan, M., Pingping Xia, Liu, B., Zhang, L., Wang, Y., Gao, X., & Lihua Li. (2019). MOESM3 of Tumour heterogeneity revealed by unsupervised decomposition of dynamic contrast-enhanced magnetic resonance imaging is associated with underlying gene expression patterns and poor survival in breast cancer patients. Figshare. https://doi.org/10.6084/M9.FIGSHARE.10001720Publisher
figshareRelations
Is Supplement To:- [Article]
Fan, M., Xia, P., Liu, B., Zhang, L., Wang, Y., Gao, X., & Li, L. (2019). Tumour heterogeneity revealed by unsupervised decomposition of dynamic contrast-enhanced magnetic resonance imaging is associated with underlying gene expression patterns and poor survival in breast cancer patients. Breast Cancer Research, 21(1). doi:10.1186/s13058-019-1199-8. DOI: 10.1186/s13058-019-1199-8 HANDLE: 10754/659544
ae974a485f413a2113503eed53cd6c53
10.6084/m9.figshare.10001720