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S. Das

Researcher at Indian Institute of Technology Kanpur

Publications -  35
Citations -  1320

S. Das is an academic researcher from Indian Institute of Technology Kanpur. The author has contributed to research in topics: Curvature & Vesicle. The author has an hindex of 14, co-authored 35 publications receiving 1142 citations. Previous affiliations of S. Das include University of Leicester & Cornell University.

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Thermodynamics and Mechanics of Membrane Curvature Generation and Sensing by Proteins and Lipids

TL;DR: The present review first provides an overview of important classes of membrane proteins for which function is coupled to membrane curvature, and surveys several mechanisms that are assumed to underlie membranes curvature sensing and generation.
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Membrane Elasticity in Giant Vesicles with Fluid Phase Coexistence

TL;DR: The observations of experimental vesicle geometries being modulated by Gaussian curvature moduli differences confirm the prediction by the theory of Juelicher and Lipowsky that this geometry of giant unilamellar vesicles with coexisting liquid-disordered and liquid-ordered phases is dominated by the Gauss modulus.
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Multiple scales without center manifold reductions for delay differential equations near Hopf bifurcations

TL;DR: In this article, small perturbations of three linear Delay Differential Equations (DDEs) close to Hopf bifurcation points are studied, and it is shown that the method of multiple scales, on simply discarding the infinitely many exponentially decaying components of the complementary solutions obtained at each stage of the approximation, can bypass the explicit center manifold calculation.
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Nonlinear Sorting, Curvature Generation, and Crowding of Endophilin N-BAR on Tubular Membranes

TL;DR: The spontaneous curvature induced by endophilin is determined and a nonlinear curvature/composition coupling model is developed that predicts a curvature-induced phase transition among two states with varying protein density and membrane curvature.
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Adhesion of vesicles to curved substrates.

TL;DR: This work investigates the adhesion of vesicles, under the influence of a contact potential, to substrates with various geometry and constructs an approximate analytical solution that predicts the shape of the vesicle for large internal excess pressure and contact potential.