<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kadam, Shantanu</style></author><author><style face="normal" font="default" size="100%">Vanka, Kumar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">New approximate method for the stochastic simulation of chemical systems: the representative reaction approach</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Computational Chemistry</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">approximate algorithm</style></keyword><keyword><style  face="normal" font="default" size="100%">Stochastic simulations</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JAN</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">3</style></number><publisher><style face="normal" font="default" size="100%">WILEY-BLACKWELL</style></publisher><pub-location><style face="normal" font="default" size="100%">COMMERCE PLACE, 350 MAIN ST, MALDEN 02148, MA USA</style></pub-location><volume><style face="normal" font="default" size="100%">33</style></volume><pages><style face="normal" font="default" size="100%">276-285</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We have developed two new approximate methods for stochastically simulating chemical systems. The methods are based on the idea of representing all the reactions in the chemical system by a single reaction, i.e., by the representative reaction approach (RRA). Discussed in the article are the concepts underlying the new methods along with flowchart with all the steps required for their implementation. It is shown that the two RRA methods {with the reaction \$ 2A \textbackslashrightarrow B \$ as the representative reaction (RR)} perform creditably with regard to accuracy and computational efficiency, in comparison to the exact stochastic simulation algorithm (SSA) developed by Gillespie and are able to successfully reproduce at least the first two moments of the probability distribution of each species in the systems studied. As such, the RRA methods represent a promising new approach for stochastically simulating chemical systems. (C) 2011 Wiley Periodicals, Inc. J Comput Chem, 2012&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">3.835
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kuriakose, Nishamol</style></author><author><style face="normal" font="default" size="100%">Kadam, Shantanu</style></author><author><style face="normal" font="default" size="100%">Vanka, Kumar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Theoretical study of metal-metal cooperativity in the homogeneous water gas shift reaction</style></title><secondary-title><style face="normal" font="default" size="100%">Inorganic Chemistry</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JAN</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">1</style></number><publisher><style face="normal" font="default" size="100%">AMER CHEMICAL SOC</style></publisher><pub-location><style face="normal" font="default" size="100%">1155 16TH ST, NW, WASHINGTON, DC 20036 USA</style></pub-location><volume><style face="normal" font="default" size="100%">51</style></volume><pages><style face="normal" font="default" size="100%">377-385</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The possibility of metal-metal cooperativity in improving the yield of the homogeneous water gas shift reaction (WGSR) has been investigated through full quantum mechanical density functional theory calculations. The calculations indicate that bimetallic catalysts would be likely to be more highly active than mononuclear metal-based catalysts for the WGSR. The results have implications for the design of improved WGSR catalysts in the future.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">4.593
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kadam, Shantanu</style></author><author><style face="normal" font="default" size="100%">Vanka, Kumar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Solving the problem of negative populations in approximate accelerated stochastic simulations using the representative reaction approach</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Computational Chemistry</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">approximate methods</style></keyword><keyword><style  face="normal" font="default" size="100%">binomial distributions</style></keyword><keyword><style  face="normal" font="default" size="100%">Gillespie algorithm</style></keyword><keyword><style  face="normal" font="default" size="100%">Kinetic Monte Carlo</style></keyword><keyword><style  face="normal" font="default" size="100%">Poisson distributions</style></keyword><keyword><style  face="normal" font="default" size="100%">representative reaction approach</style></keyword><keyword><style  face="normal" font="default" size="100%">Stochastic simulations</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">FEB</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">5</style></number><publisher><style face="normal" font="default" size="100%">WILEY-BLACKWELL</style></publisher><pub-location><style face="normal" font="default" size="100%">111 RIVER ST, HOBOKEN 07030-5774, NJ USA</style></pub-location><volume><style face="normal" font="default" size="100%">34</style></volume><pages><style face="normal" font="default" size="100%">394-404</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Methods based on the stochastic formulation of chemical kinetics have the potential to accurately reproduce the dynamical behavior of various biochemical systems of interest. However, the computational expense makes them impractical for the study of real systems. Attempts to render these methods practical have led to the development of accelerated methods, where the reaction numbers are modeled by Poisson random numbers. However, for certain systems, such methods give rise to physically unrealistic negative numbers for species populations. The methods which make use of binomial variables, in place of Poisson random numbers, have since become popular, and have been partially successful in addressing this problem. In this manuscript, the development of two new computational methods, based on the representative reaction approach (RRA), has been discussed. The new methods endeavor to solve the problem of negative numbers, by making use of tools like the stochastic simulation algorithm and the binomial method, in conjunction with the RRA. It is found that these newly developed methods perform better than other binomial methods used for stochastic simulations, in resolving the problem of negative populations. (C) 2012 Wiley Periodicals, Inc.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">3.601
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kadam, Shantanu</style></author><author><style face="normal" font="default" size="100%">Vanka, Kumar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Accounting of noise to solve the problem of negative populations in approximate accelerated stochastic simulations</style></title><secondary-title><style face="normal" font="default" size="100%">RSC Advances</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">OCT</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">102</style></number><publisher><style face="normal" font="default" size="100%">ROYAL SOC CHEMISTRY</style></publisher><pub-location><style face="normal" font="default" size="100%">THOMAS GRAHAM HOUSE, SCIENCE PARK, MILTON RD, CAMBRIDGE CB4 0WF, CAMBS, ENGLAND</style></pub-location><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">58127-58136</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The advent of different approximate accelerated stochastic simulation methods has helped considerably in reducing the computational load of the exact simulation algorithms. However, along with the reduction in the computational load comes the risk of driving the molecular numbers to the regime of negative numbers during the simulations. Over the years, various methods have been developed in order to solve the problem by using different strategies. Some methods have employed binomial numbers to model the reactions, while others have tried the partitioning of the reaction network. In this manuscript, we have proposed a new approach where the noise inherent in the choice of the number of firings of a given reaction during a time step is taken into account. This idea of noise accounting is used in conjunction with the accelerated stochastic method: the Representative Reaction Approach (RRA). It is found that the new method is successful at solving the problem of negative numbers, and compares very favorably with other state-of-the-art stochastic simulation methods.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">102</style></issue><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">3.98</style></custom4></record></records></xml>