1,721,152 research outputs found
Efficient finite-difference method for computing sensitivities of biochemical reactions
No full textSensitivity analysis of biochemical reactions aims at quantifying the dependence of the reaction dynamics on the reaction rates. The computation of the parameter sensitivities, however, poses many computational challenges when taking stochastic noise into account. This paper proposes a new finite-difference method for efficiently computing sensitivities of biochemical reactions. We employ propensity bounds of reactions to couple the simulation of the nominal and perturbed processes. The exactness of the simulation is preserved by applying the rejection-based mechanism. For each simulation step, the nominal and perturbed processes under our coupling strategy are synchronized and often jump together, increasing their positive correlation and hence reducing the variance of the estimator. The distinctive feature of our approach in comparison with existing coupling approaches is that it only needs to maintain a single data structure storing propensity bounds of reactions during the simulation of the nominal and perturbed processes. Our approach allows to compute sensitivities of many reaction rates simultaneously. Moreover, the data structure does not require to be updated frequently, hence improving the computational cost. This feature is especially useful when applied to large reaction networks. We benchmark our method on biological reaction models to prove its applicability and efficiency. © 2018 The Author(s) Published by the Royal Society. All rights reserved
Efficient stochastic simulation of biochemical reactions with noise and delays
No full textThe stochastic simulation algorithm has been used to generate exact trajectories of biochemical reaction networks. For each simulation step, the simulation selects a reaction and its firing time according to a probability that is proportional to the reaction propensity. We investigate in this paper new efficient formulations of the stochastic simulation algorithm to improve its computational efficiency. We examine the selection of the next reaction firing and reduce its computational cost by reusing the computation in the previous step. For biochemical reactions with delays, we present a new method for computing the firing time of the next reaction. The principle for computing the firing time of our approach is based on recycling of random numbers. Our new approach for generating the firing time of the next reaction is not only computationally efficient but also easy to implement. We further analyze and reduce the number of propensity updates when a delayed reaction occurred. We demonstrate the applicability of our improvements by experimenting with concrete biological models
Efficient rejection-based simulation of biochemical reactions with stochastic noise and delays
No full textWe propose a new exact stochastic rejection-based simulation algorithm for biochemical reactions and extend it to systems with delays. Our algorithm accelerates the simulation by pre-computing reaction propensity bounds to select the next reaction to perform. Exploiting such bounds, we are able to avoid recomputing propensities every time a (delayed) reaction is initiated or finished, as is typically necessary in standard approaches. Propensity updates in our approach are still performed, but only infrequently and limited for a small number of reactions, saving computation time and without sacrificing exactness. We evaluate the performance improvement of our algorithm by experimenting with concrete biological models
HRSSA - Efficient hybrid stochastic simulation for spatially homogeneous biochemical reaction networks
No full textThis paper introduces HRSSA (Hybrid Rejection-based Stochastic Simulation Algorithm), a new efficient hybrid stochastic simulation algorithm for spatially homogeneous biochemical reaction networks. HRSSA is built on top of RSSA, an exact stochastic simulation algorithm which relies on propensity bounds to select next reaction firings and to reduce the average number of reaction propensity updates needed during the simulation. HRSSA exploits the computational advantage of propensity bounds to manage time-varying transition propensities and to apply dynamic partitioning of reactions, which constitute the two most significant bottlenecks of hybrid simulation. A comprehensive set of simulation benchmarks is provided for evaluating performance and accuracy of HRSSA against other state of the art algorithms
Simulation algorithms for computational systems biology
No full textThe dynamics of molecular systems is an essential tool of systems biology. It helps figuring out what is the effect of the perturbation of a system, or what is the best dose for a drug or what could be an effective combined therapy. Simulation is the essence of what-if experiments that help making informed decision for the next lab experiments by saving time and resources.
We felt the lack of a comprehensive textbook collecting the most relevant and state of the art simulation algorithms that can be a reference for the students and the researchers entering the field. In particular, the book is intended for the practitioners of the systems biology field with mathematical/computing background, that want to understand simulation algorithms and algorithmic systems biology. The book can also be used in advanced undergraduate courses on modeling and simulation of biological systems. It contains many examples used as benchmarks as well that can help students gain a practical grasp on the main concepts throughout the book. Some knowledge of basic molecular biology and basic computer science can help, but the aim of the book is to be a self-contained approach to the field. All chapters propose further readings about the topics introduced, to drive the reader to deeper treatments of the topics in the book. All of these references are collected in the bibliography reported at the end of the book. The appendixes briefly recalls relevant knowledge needed to completely appreciate the book.
The book approaches three different classes of simulation algorithms: stochastic, deterministic and hybrid. As a final remark, we stress that we were forced to choose among many different algorithms and methods to constrain the book to a reasonable size. The choice was driven by our experience both as researchers and teachers working in the field. We are aware that there are many other excellent solutions to the problems addressed in the book that we were not able to include. The references are intended to manage this issue at least partially
Incorporating extrinsic noise into the stochastic simulation of biochemical reactions: A comparison of approaches
No full textThe stochastic simulation algorithm (SSA) has been widely used for simulating biochemical reaction networks. SSA is able to capture the inherently intrinsic noise of the biological system, which is due to the discreteness of species population and to the randomness of their reciprocal interactions. However, SSA does not consider other sources of heterogeneity in biochemical reaction systems, which are referred to as extrinsic noise. Here, we extend two simulation approaches, namely, the integration-based method and the rejection-based method, to take extrinsic noise into account by allowing the reaction propensities to vary in time and state dependent manner. For both methods, new efficient implementations are introduced and their efficiency and applicability to biological models are investigated. Our numerical results suggest that the rejection-based method performs better than the integration-based method when the extrinsic noise is considered
RSSALib: a library for stochastic simulation of complex biochemical reactions
No full textMOTIVATION: Stochastic chemical kinetics is an essential mathematical framework for investigating the dynamics of biological processes, especially when stochasticity plays a vital role in their development. Simulation is often the only option for the analysis of many practical models due to their analytical intractability. RESULTS: We present in this article, the simulation library RSSALib, implementing our recently developed rejection-based stochastic simulation algorithm (RSSA) and a wide range of its improvements, to accelerate the simulation and analysis of biochemical reactions. RSSALib supports reactions with complex kinetics and time delays, necessary to model complexities of reaction mechanisms. Our library provides both an application program interface and a graphic user interface to ease the set-up and visualization of the simulation results. AVAILABILITY AND IMPLEMENTATION: RSSALib is freely available at: https://github.com/vo-hong-thanh/rssalib. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.Peer reviewe
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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