Madhusudan Natarajan

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Cellular information processing requires the coordinated activity of a large network of intracellular signalling pathways. Cross-talk between pathways provides for complex non-linear responses to combinations of stimuli, but little is known about the density of these interactions in any specific cell. Here, we have analysed a large-scale survey of pathway(More)
Statistical analyses of protein families reveal networks of coevolving amino acids that functionally link distantly positioned functional surfaces. Such linkages suggest a concept for engineering allosteric control into proteins: The intramolecular networks of two proteins could be joined across their surface sites such that the activity of one protein(More)
The Alliance for Cellular Signaling is a large-scale collaboration designed to answer global questions about signalling networks. Pathways will be studied intensively in two cells--B lymphocytes (the cells of the immune system) and cardiac myocytes--to facilitate quantitative modelling. One goal is to catalyse complementary research in individual(More)
Cellular signal transduction machinery integrates information from multiple inputs to actuate discrete cellular behaviors. Interaction complexity exists when an input modulates the output behavior that results from other inputs. To address whether this machinery is iteratively complex--that is, whether increasing numbers of inputs produce exponential(More)
Wireless sensor network (WSN) consists of spatially distributed autonomous sensors to monitor physical and environmental conditions. Grouping sensor nodes into the cluster can reduce the size of the routing table of the each individual node and conserve communication bandwidth. Sensors in such environments are energy constrained and their batteries cannot(More)
The inference of cellular architectures from detailed time-series measurements of intracellular variables is an active area of research. High throughput measurements of responses to cellular perturbations are usually analyzed using a variety of machine learning methods that typically only work within one type of measurement. Here, summaries of some recent(More)
Deciding how and where to control a fluid system often relies heavily on intuition, experience, and what actuators are readily available. While useful for flows for which experience exists, adopting such an approach for the control of novel, complex fluid systems may lead to suboptimal or ineffective control strategies. In this report we develop a procedure(More)
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