TGF-β induced epithelial-mesenchymal transition modeling

International Conference on Bio-Medical Instrumentation and related Engineering and Physical Sciences

物理学;医药卫生

Xenitidis, P.^1 ; Seimenis, I.^1 ; Kakolyris, S.^2 ; Adamopoulos, A.^1

Medical Physics Lab, School of Medicine, Democritus University of Thrace, Alexandroupolis, Greece^1

Department of Medical Oncology, School of Medicine, Democritus University of Thrace, Alexandroupolis, Greece^2

关键词: Algorithm performance;    Epithelial to Mesenchymal transitions;    Epithelial-mesenchymal transition;    Gene expression microarray;    Gene regulatory networks;    Network inference;    Receiver operating characteristics;    Transforming growth factor beta;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/637/1/012035/pdf
DOI  :  10.1088/1742-6596/637/1/012035

学科分类：卫生学

来源: IOP

【 摘 要 】

Epithelial cells may undergo a process called epithelial to mesenchymal transition (EMT). During EMT, cells lose their epithelial characteristics and acquire a migratory ability. Transforming growth factor-beta (TGF-β) signaling is considered to play an important role in EMT by regulating a set of genes through a gene regulatory network (GRN). This work aims at TGF-β induced EMT GRN modeling using publicly available experimental data (gene expression microarray data). The time-series network identification (TSNI) algorithm was used for inferring the EMT GRN. Receiver operating characteristic (ROC) and precision-recall (P-R) curves were constructed and the areas under them were used for evaluating the algorithm performance regarding network inference.