TY  - JOUR
A1  - Maity, Alok Kumar
A1  - Bandyopadhyay, Arnab
A1  - Chattopadhyay, Sudip
A1  - Chaudhuri, Jyotipratim Ray
A1  - Metzler, Ralf
A1  - Chaudhury, Pinaki
A1  - Banik, Suman K.
T1  - Quantification of noise in bifunctionality-induced post-translational modification
JF  - Physical review : E, Statistical, nonlinear and soft matter physics
N2  - We present a generic analytical scheme for the quantification of fluctuations due to bifunctionality-induced signal transduction within the members of a bacterial two-component system. The proposed model takes into account post-translational modifications in terms of elementary phosphotransfer kinetics. Sources of fluctuations due to autophosphorylation, kinase, and phosphatase activity of the sensor kinase have been considered in the model via Langevin equations, which are then solved within the framework of linear noise approximation. The resultant analytical expression of phosphorylated response regulators are then used to quantify the noise profile of biologically motivated single and branched pathways. Enhancement and reduction of noise in terms of extra phosphate outflux and influx, respectively, have been analyzed for the branched system. Furthermore, the role of fluctuations of the network output in the regulation of a promoter with random activation-deactivation dynamics has been analyzed.
Y1  - 2013
U6  - https://doi.org/10.1103/PhysRevE.88.032716
SN  - 1539-3755
VL  - 88
IS  - 3
PB  - American Physical Society
CY  - College Park
ER  - 
TY  - JOUR
A1  - Talukder, Srijeeta
A1  - Sen, Shrabani
A1  - Metzler, Ralf
A1  - Banik, Suman K.
A1  - Chaudhury, Pinaki
T1  - Stochastic optimization-based study of dimerization kinetics
JF  - JOURNAL OF CHEMICAL SCIENCES
N2  - We investigate the potential of numerical algorithms to decipher the kinetic parameters involved in multi-step chemical reactions. To this end, we study dimerization kinetics of protein as a model system. We follow the dimerization kinetics using a stochastic simulation algorithm and combine it with three different optimization techniques (genetic algorithm, simulated annealing and parallel tempering) to obtain the rate constants involved in each reaction step. We find good convergence of the numerical scheme to the rate constants of the process. We also perform a sensitivity test on the reaction kinetic parameters to see the relative effects of the parameters for the associated profile of the monomer/dimer distribution.
KW  - Stochastic optimization
KW  - dimerization kinetics
KW  - sensitivity analysis
KW  - stochastic simulation algorithm
KW  - probability distribution function
Y1  - 2013
SN  - 0974-3626
SN  - 0973-7103
VL  - 125
IS  - 6
SP  - 1619
EP  - 1627
PB  - INDIAN ACAD SCIENCES
CY  - BANGALORE
ER  -