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 File
KAUST 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/10754/664821Metadata
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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
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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