Wei Peng

TL;DR: A predicting framework named by XGBFEMF for identifying essential proteins, which includes a SUB-EXPAND-SHRINK method for constructing the composite features with original features and obtaining the better subset of features for essential protein prediction, and also includes a model fusion method for getting a more effective prediction model.

TL;DR: The applications on DPINs will be discussed, including protein complexes/functional modules and network organization analysis, biomarkers detection in the progression or prognosis of the disease, and network medicine.

TL;DR: It is found that LINC00312 induced migration, invasion and VM of lung cancer cells by direct binding to the transcription factor Y-Box Binding Protein 1 (YBX1).

TL;DR: A new prediction method is proposed, named UDoNC, by combining the domain features of proteins with their topological properties in PPI network, which outperforms other existing methods in terms of area under the curve (AUC) and performs well in predicting essential proteins on data of E. coli.

TL;DR: This research will provide readers some guidance for choosing appropriate methods and features for obtaining reliable PPIs, and also enumerate several PPI network-based applications with taking a reliability assessment of the PPI data into consideration.