Hence incorporating PPI network and pathway interaction information in cancer studies is critical in discovering interactions among genes and deciphering the molecular pathway of cancer.
Those interactions would be impossible to discover in an observational study where genetics might have influenced who got treatment and/or where the genetic variation in the population may be poorly aligned for discovering interactions.
Although its significance in the context of NRTI drugs remains unclear, this in silico discovered interaction deserves further attention.
These results are consistent with the recently discovered interaction between FLCN and AMPK and support a model in which FLCN is a regulator of mitochondrial function.
Both BPA and PCB 126 have been shown in controlled experiments to be associated with liver toxicity in rats [ 43, 44] so the discovered interaction seems plausible.
Libraries containing very large numbers of such short peptide sequences can be generated easily and used to discover interaction preferences of proteins.
Utilizing this newly discovered interaction, miR-181a-5p may serve as a prognostic biomarker, or could possibly be mimicked by anti-metastatic therapeutics.
The newly discovered interaction between His1 and Socs36E is consistent with the role that JAK/STAT pathway plays in the deposition of H1 protein into larval chromatin and in heterochromatic silencing (Xu et al. 2014).
Factorial design strategies are the only way to discover interactions between factors.
Ideally, one would like to perform ANCEA on a homogeneous population so that discovered interactions would pertain to only one state and could be input into a "view from the cell" in the network model.
