Manikandan Narayanan

TL;DR: The causal network structure is a useful predictor of response to gene perturbations and presents a framework to test models of disease mechanisms underlying LOAD.

TL;DR: Independent of age and pre-existing antibody titers, accurate models could be constructed using pre-perturbation cell populations alone, which were validated using independent baseline time points.

TL;DR: Using expression profiles from postmortem prefrontal cortex samples of 624 dementia patients and non‐demented controls, this work identified a 242‐gene subnetwork enriched for independent AD/HD signatures, which revealed a surprising dichotomy of gained/lost correlations among two inter‐connected processes, chromatin organization and neural differentiation.

TL;DR: The results suggest that CD8+ lymphocytes undergo chromatin remodeling in a progressive fashion, and have major implications for the understanding of peripheral T-cell ontogeny and the formation of immunological memory.

TL;DR: A method that compares the protein interaction networks of two species to detect functionally similar (conserved) protein modules between them, based on an algorithm developed to identify matching subgraphs between two graphs that performs competitively with and sometimes better than two previous network comparison methods.