RIP (regulatory interaction predictor) is a machine learning approach that inferred 73,923 RIs for 301 human TFs and 11,263 target genes with considerably good quality and 4,516 RIs with very high quality. The inference of RIs is independent of any specific condition.
RIP (Rotamerically Induced Perturbation) generates local perturbations of residues in a protein. In picoseconds of a molecular-dynamics (MD) simulation, RIP generates motions that reveal certain mechanical properties of a protein. 1) Flexibility Analysis: using larger perturbations, RIP can induce several ?ngstroms of conformational change in loops, identifying potential allosteric effectors. E.g. on the right is the RIP perturbation on TRP-83 in the Ligand-Binding Domain of the Estrogen Receptor, which produces a dramatic 10 ? motion of the ligand-binding Helix 12 in a 10 ps simulation. 2) Coupling Analysis: using small RIP perturbations, residues that interact strongly can be identified. Analysis of the patterns of strongly interacting residues allows an analysis of tertiary structure dynamics.