We report a novel computational algorithm "BP-STOCH" to be used for studying single-type ligand binding with biopolymers of finite lengths, such as DNA oligonucleotides or oligopeptides. It is based on an id...
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We report a novel computational algorithm "BP-STOCH" to be used for studying single-type ligand binding with biopolymers of finite lengths, such as DNA oligonucleotides or oligopeptides. It is based on an idea to represent any type of ligand biopolymer complex in a form of binary number, where "0" and "1" bits stand for vacant and engaged monomers of the biopolymer, respectively. Cycling over all binary numbers from the lowest 0 up to the highest 2(N) - 1 means a sequential generating of all possible configurations of vacant/ engaged monomers, which, after proper filtering, results in a full set of possible types of complexes in solution between the ligand and the N-site lattice. The principal advantage of BP-STOCH algorithm is the possibility to incorporate into this cycle any conditions on computation of the concentrations and observed experimental parameters of the complexes in solution, and programmatic access to each monomer of the biopolymer within each binding site of every binding configuration. The latter is equivalent to unlimited extension of the basic reaction scheme and allows to use BP-STOCH algorithm as an alternative to conventional computational approaches. (C) 2010 Wiley Periodicals, Inc. Biopolymers 95: 208-216, 2011.
In this paper, we investigate uniform convergence of the improper Hubbell radiation rectangular source (HRS) integral H(a,b). We prove that HRS integral H(a,b) is uniform convergent in the domain D = {(a,b) is an elem...
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In this paper, we investigate uniform convergence of the improper Hubbell radiation rectangular source (HRS) integral H(a,b). We prove that HRS integral H(a,b) is uniform convergent in the domain D = {(a,b) is an element of [0,A] x [0,infinity)} for any positive finite number A. Then we give an accurate and efficient computation algorithm for the HRS integral. (C) 2011 Elsevier Ltd. All rights reserved.
The paper presents a method to find the solution of the constant coefficient matrix differential Riccati differential in terms of solutions of algebraic Riccati and Lyapunov equations, and the state transition matrix ...
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The paper presents a method to find the solution of the constant coefficient matrix differential Riccati differential in terms of solutions of algebraic Riccati and Lyapunov equations, and the state transition matrix (matrix exponential) of the corresponding linear dynamic system. The method presented represents an improved method of Potter-Anderson-Moore since the solution is obtained under milder assumptions than the original algorithm of Potter-Anderson-Moore. An aircraft and satellite examples done in the paper demonstrate the advantages of the improved algorithm. (C) 2011 Elsevier Inc. All rights reserved.
In this paper, we establish an algorithm for the computation of the mean residual life of a (n - k + 1)-out-of-n system in the case of independent but not necessarily identically distributed lifetimes of the component...
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In this paper, we establish an algorithm for the computation of the mean residual life of a (n - k + 1)-out-of-n system in the case of independent but not necessarily identically distributed lifetimes of the components. An application for the exponentiated Weibull distribution is given to study the effect of various parameters on the mean residual life of the system. Also the relationship between the mean residual life for the system and that of its components is investigated. (C) 2011 Elsevier Inc. All rights reserved.
Up to now, several computational methods have been proposed for crystal plasticity models. The main objective of these computational methods has been to overcome the problem with the non-uniqueness of active slip syst...
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Up to now, several computational methods have been proposed for crystal plasticity models. The main objective of these computational methods has been to overcome the problem with the non-uniqueness of active slip systems during the plastic deformation of a single crystal. Crystal plasticity models based on a single crystal yield function have been proposed as alternative algorithms to overcome this problem. But the problem with these models is that they use a highly non-linear yield function for the crystal, which makes them computationally expensive. In this paper, a computational method is proposed that would modify a single crystal yield function in order to make it computationally efficient. Also to better capture experimental data, a new parameter is introduced into the single crystal yield function to make it more flexible. For verification, this crystal plasticity model was directly applied for the simulation of hydroforming of an extruded aluminum tube under complex strain paths. It was found that the current model is considerably faster than the previous crystal plasticity model based on a power-law type single crystal yield surface. Due to its computational efficiency, the current crystal plasticity model can also be used to calculate the anisotropy coefficients of phenomenological yield functions. (c) 2006 Elsevier Ltd. All rights reserved.
The optimization of a transient process in a linear singularly perturbed system is considered. The goal is to find a (multidimensional) control of minimal intensity. An algorithm for constructing asymptotic approximat...
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The optimization of a transient process in a linear singularly perturbed system is considered. The goal is to find a (multidimensional) control of minimal intensity. An algorithm for constructing asymptotic approximations to the solution of the problem is proposed. The main advantage of the algorithm is that the original problem decomposes into optimal control problems of lower dimension.
The DNA sequencing technology developed by Frederick Sanger in the 1970s established genomics as the basis of comparative genetics. The recent invention of next-generation sequencing (NGS) platform has added a new dim...
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The DNA sequencing technology developed by Frederick Sanger in the 1970s established genomics as the basis of comparative genetics. The recent invention of next-generation sequencing (NGS) platform has added a new dimension to genome research by generating ultra-fast and high-throughput sequencing data in an unprecedented manner. The advent of NGS technology also provides the opportunity to study genetic diseases where sequence variants or mutations are sought to establish a causal relationship with disease phenotypes. However, it is not a trivial task to seek genetic variants responsible for genetic diseases and even harder for complex diseases such as diabetes and cancers. In such polygenic diseases, multiple genes and alleles, which can exist in healthy individuals, come together to contribute to common disease phenotypes in a complex manner. Hence, it is desirable to have an approach that integrates omics data with both knowledge of protein structure and function and an understanding of networks/pathways, i.e. functional genomics and systems biology;in this way, genotype-phenotype relationships can be better understood. In this review, we bring this 'bottom-up' approach alongside the current NGS-driven genetic study of genetic variations and disease aetiology. We describe experimental and computational techniques for assessing genetic variants and their deleterious effects on protein structure and function.
In this paper, we consider a class of optimal control problem involving an impulsive systems in which some of its coefficients are subject to variation. We formulate this optimal control problem as a two-stage optimal...
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In this paper, we consider a class of optimal control problem involving an impulsive systems in which some of its coefficients are subject to variation. We formulate this optimal control problem as a two-stage optimal control problem. We first formulate the optimal impulsive control problem with all its coefficients assigned to their nominal values. This becomes a standard optimal impulsive control problem and it can be solved by many existing optimal control computational techniques, such as the control parameterizations technique used in conjunction with the time scaling transform. The optimal control software package, MISER 3.3, is applicable. Then, we formulate the second optimal impulsive control problem, where the sensitivity of the variation of coefficients is minimized subject to an additional constraint indicating the allowable reduction in the optimal cost. The gradient formulae of the cost functional for the second optimal control problem are obtained. On this basis, a gradient-based computational method is established, and the optimal control software, MISER 3.3, can be applied. For illustration, two numerical examples are solved by using the proposed method. (C) 2011 Elsevier Inc. All rights reserved.
In this paper, uniform convergence of the generalized exponential (GE) integrals is investigated. We also study the continuity, differentiability, summability and asymptotic behaviour of GE integrals. Then we give an ...
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In this paper, uniform convergence of the generalized exponential (GE) integrals is investigated. We also study the continuity, differentiability, summability and asymptotic behaviour of GE integrals. Then we give an accurate and efficient computation algorithm for these integrals.
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