Welcome
Hi. I am a grad student in physics at Matscience, Chennai, India. My primary research interest is the effects of noise in biology, with particular focus on constructive effects of stochastic fluctuations in various biological and biochemical contexts. I employ both analytical and numerical techniques to study these stochastic processes, most of which are in the birth-death format. I also focus on the study of active matter, especially the dynamics of active filaments. In addition to these primary fields of study, I am also interested in the design and analysis of quantum mechanical systems inspired from biology. My advisor is Dr Ronojoy Adhikari.Publications and Preprints
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Abhrajit Laskar, Rajeev Singh, Somdeb Ghose, Gayathri Jayaraman, P. B. Sunil Kumar, R. Adhikari, "Hydrodynamic Instabilities Provide A Generic Route To Spontaneous Biomimetic Oscillations In Chemomechanically Active Filaments", arXiv:1211.5368 (2012). To appear in Nature Scientific Reports. [Abstract] [pdf]
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Gayathri Jayaraman, Sanoop Ramachandran, Somdeb Ghose, Abhrajit Laskar, M. Saad Bhamla, P. B. Sunil Kumar, R. Adhikari, "Autonomous Motility of Active Filaments due to Spontaneous Flow-Symmetry Breaking", Physical Review Letters, 109, 158302 (2012). [Abstract] [pdf] [Movies] [bibteX]
@article{ jayaraman2012, title={Autonomous Motility of Active Filaments due to Spontaneous Flow-Symmetry Breaking},
author={Jayaraman, Gayathri and Ramachandran, Sanoop and Ghose, Somdeb and Laskar, Abhrajit and Saad Bhamla, M. and Sunil Kumar, P. B. and Adhikari, R. },
journal={Phys. Rev. Lett.},
volume = {109}, year = {2012}, pages = {158302}, url = {http://prl.aps.org/abstract/PRL/v109/i15/e158302},
abstract = {We simulate the nonlocal Stokesian hydrodynamics of an elastic filament which is active due a permanent distribution of stresslets along its contour. A bending instability of an initially straight filament spontaneously breaks flow symmetry and leads to autonomous filament motion which, depending on conformational symmetry, can be translational or rotational. At high ratios of activity to elasticity, the linear instability develops into nonlinear fluctuating states with large amplitude deformations. The dynamics of these states can be qualitatively understood as a superposition of translational and rotational motion associated with filament conformational modes of opposite symmetry. Our results can be tested in molecular-motor filament mixtures, synthetic chains of autocatalytic particles, or other linearly connected systems where chemical energy is converted to mechanical energy in a fluid environment.} -
Soma Saha, Somdeb Ghose, R. Adhikari and Arti Dua, "Nonrenewal Statistics in the Catalytic Activity of Enzyme Molecules at Mesoscopic Concentrations", Physical Review Letters, 107, 218301 (2011). [Abstract] [pdf] [bibteX]
@article{ saha2011, title = {Nonrenewal Statistics in the Catalytic Activity of Enzyme Molecules at Mesoscopic Concentrations}, author = {Saha, Soma and Ghose, Somdeb and Adhikari, R. and Dua, Arti}, journal = {Phys. Rev. Lett.}, volume = {107}, year = {2011}, pages = {218301}, url = {http://link.aps.org/doi/10.1103/PhysRevLett.107.218301}, abstract={Recent fluorescence spectroscopy measurements of single-enzyme kinetics have shown that enzymatic turnovers form a renewal stochastic process in which the inverse of the mean waiting time between turnovers follows the Michaelis-Menten equation. We study enzyme kinetics at physiologically relevant mesoscopic concentrations using a master equation. From the exact solution of the master equation we find that the waiting times are neither independent nor identically distributed, implying that enzymatic turnovers form a nonrenewal stochastic process. The inverse of the mean waiting time shows strong departure from the Michaelis-Menten equation. The waiting times between consecutive turnovers are anticorrelated, where short intervals are more likely to be followed by long intervals and vice versa. Correlations persist beyond consecutive turnovers indicating that multiscale fluctuations govern enzyme kinetics.} -
Somdeb Ghose and R. Adhikari, "Endogenous Quasicycles and Stochastic Coherence in a Closed Endemic Model", Physical Review E, 82, 021913 (2010). [Abstract] [pdf] [bibteX]
@article{ ghose2010, title = {Endogenous quasicycles and stochastic coherence in a closed endemic model}, author = {Ghose, Somdeb and Adhikari, R.}, journal = {Phys. Rev. E}, volume = {82}, year = {2010}, pages = {021913}, url = {http://link.aps.org/doi/10.1103/PhysRevE.82.021913}, abstract = {We study the role of demographic fluctuations in typical endemics as exemplified by the stochastic SIRS model. The birth-death master equation of the model is simulated using exact numerics and analyzed within the linear noise approximation. The endemic fixed point is unstable to internal demographic noise, and leads to sustained oscillations. This is ensured when the eigenvalues (λ) of the linearized drift matrix are complex, which in turn, is possible only if detailed balance is violated. In the oscillatory state, the phases decorrelate asymptotically, distinguishing such oscillations from those produced by external periodic forcing. These so-called quasicycles are of sufficient strength to be detected reliably only when the ratio |Im(λ)/Re(λ)| is of order unity. The coherence or regularity of these oscillations show a maximum as a function of population size, an effect known variously as stochastic coherence or coherence resonance. We find that stochastic coherence can be simply understood as resulting from a nonmonotonic variation of |Im(λ)/Re(λ)| with population size. Thus, within the linear noise approximation, stochastic coherence can be predicted from a purely deterministic analysis. The non-normality of the linearized drift matrix, associated with the violation of detailed balance, leads to enhanced fluctuations in the population amplitudes.}
© 2012 Somdeb Ghose
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