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GillesPy2: A Biochemical Modeling Framework for Simulation Driven Biological Discovery. GillesPy2:模拟驱动生物发现的生化建模框架。
Q3 Mathematics Pub Date : 2023-01-10
Sean Matthew, Fin Carter, Joshua Cooper, Matthew Dippel, Ethan Green, Samuel Hodges, Mason Kidwell, Dalton Nickerson, Bryan Rumsey, Jesse Reeve, Linda R Petzold, Kevin R Sanft, Brian Drawert

Stochastic modeling has become an essential tool for studying biochemical reaction networks. There is a growing need for user-friendly and feature-complete software for model design and simulation. To address this need, we present GillesPy2, an open-source framework for building and simulating mathematical and biochemical models. GillesPy2, a major upgrade from the original GillesPy package, is now a stand-alone Python 3 package. GillesPy2 offers an intuitive interface for robust and reproducible model creation, facilitating rapid and iterative development. In addition to expediting the model creation process, GillesPy2 offers efficient algorithms to simulate stochastic, deterministic, and hybrid stochastic-deterministic models.

随机建模已成为研究生化反应网络的重要工具。对用户友好和功能完整的模型设计和仿真软件的需求日益增长。为了满足这一需求,我们提出了GillesPy2,一个用于构建和模拟数学和生化模型的开源框架。GillesPy2是原始GillesPy包的主要升级,现在是一个独立的Python 3包。GillesPy2提供了一个直观的界面,用于稳健和可重复的模型创建,促进快速迭代开发。除了加快模型创建过程外,GillesPy2还提供了高效的算法来模拟随机、确定性和混合随机-确定性模型。
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引用次数: 0
Welcome to Volume 10 欢迎来到第10卷
Q3 Mathematics Pub Date : 2023-01-01 DOI: 10.30707/lib10.1.1682014077.7837
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引用次数: 0
Mathematical Analysis and Parameter Estimation of a Two-Patch Zika Model 双补丁Zika模型的数学分析与参数估计
Q3 Mathematics Pub Date : 2023-01-01 DOI: 10.30707/lib10.1.1682014077.806265
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引用次数: 1
Modeling the Spread of Curly Top Disease in Tomatoes 番茄卷顶病的传播模型
Q3 Mathematics Pub Date : 2023-01-01 DOI: 10.30707/lib10.1.1682014077.8265
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引用次数: 0
Epidemiology, Game Theory, and Evolutionary Rescue: Understanding How Outbreaks Impact Population Viability 流行病学、博弈论和进化救援:了解疫情如何影响种群生存能力
Q3 Mathematics Pub Date : 2023-01-01 DOI: 10.30707/lib10.1.1684158870.855659
Brandon Grandison, Hannah Yin, Ana Kilgore, Matthew J. Young, Jing Jiao, Nina H. Feerman
Evolutionary game theory (EGT) analyzes the stability of competing strategies for withstanding selective pressures within a population over generations. Under rapid shifts in selective pressures (e
进化博弈论(EGT)分析了在一个世代的种群中,竞争策略在承受选择压力时的稳定性。在快速变化的选择压力下(如
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引用次数: 1
Comparative Transmission Dynamics and Optimal Controls for Chikungunya, Dengue and Zika Virus Infections 基孔肯雅、登革热和寨卡病毒感染的比较传播动力学和最优控制
Q3 Mathematics Pub Date : 2023-01-01 DOI: 10.30707/lib6.2.1681911844.007402
Narender Kumar, S. Parveen, Ravins Dohare
In this study, we used a simple epidemic model and 2015–16 outbreak data of Chikungunya, Dengue and Zika viruses, arthropod mediated infections that are transmitted by the common mosquito vector Aedes aegypti, from Mexico to quantify the transmission rates (humans-to-mosquitoes and mosquitoes-to-humans) of the three diseases. The transmission rates are estimated for the observed data and consequently the basic reproduction number (R0) is calculated 6.740, 2.904 and 12.6283 for Chikungunya, Dengue and Zika infection, respectively. Using the estimated parameters for the three diseases, we evaluated self-imposed controls measures by the population as a result of fear-driven behavior changes often seen during an outbreak. Furthermore, the sensitivity analysis reveals that the parameter 'mosquitoes death rate' is the most sensitive one for R0. Simulations of controlled basic reproduction number are also performed for all considered control measures. This study is likely to enrich the understanding about transmission of such viral infections and control strategies.
本研究采用简单的流行模型和2015-16年墨西哥基孔肯雅热、登革热和寨卡病毒(由常见蚊媒埃及伊蚊传播的节肢动物媒介感染)的暴发数据,量化了这三种疾病的传播率(人-蚊和蚊-人)。根据观测数据估计传播率,计算基孔肯雅热、登革热和寨卡病毒的基本繁殖数R0分别为6.740、2.904和12.6283。利用这三种疾病的估计参数,我们评估了由于在疫情期间经常看到的恐惧驱动的行为改变而导致的人群自我强加的控制措施。灵敏度分析表明,“蚊子死亡率”参数对R0最敏感。对所有考虑的控制措施也进行了控制基本繁殖数的模拟。这项研究可能会丰富人们对这类病毒感染的传播和控制策略的认识。
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引用次数: 1
Effect of SOF/VEL Antiviral Therapy for HCV Treatment SOF/VEL抗病毒治疗丙型肝炎的疗效
Q3 Mathematics Pub Date : 2023-01-01 DOI: 10.30707/lib8.1.1682013528.144161
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引用次数: 4
Modeling Assumptions, Mathematical Analysis and Mitigation Through Intervention 建模假设、数学分析和干预缓解
Q3 Mathematics Pub Date : 2023-01-01 DOI: 10.30707/lib6.2.1681911844.017516
Ram Singh, Naveen Sharma, Aditi Ghosh
Ebola virus is a life-threatening virus and has two major characteristics; one potential to have high mortality rate and the other infection transmission through newly infected dead bodies. There are some relevant features of Ebola that were observed during its recent outbreak: including varying rate of access to isolation facilities by patients and transmission of infection via improper handling of the dead bodies of infected diseased. Quick and safe burial may play an important role in the control and prevention of this virus. In this study, we consider mathematical modeling framework with four different cases for dynamics of Ebola virus with safe and unsafe burial practices, vaccination and treatment interventions with varying efficiency. The goal of this study is to show how timely treatment to Ebola leads to an effective control of the virus and, most importantly, how safe burial of dead bodies helps control the spread. ARTICLE HISTORY Received November 27, 2018 Accepted December 18, 2019
埃博拉病毒是一种危及生命的病毒,它有两个主要特征;一种可能具有高死亡率,另一种可能通过新感染的尸体传播。在最近爆发期间观察到埃博拉的一些相关特征:包括患者进入隔离设施的比率不同,以及通过不当处理受感染患者的尸体传播感染。快速和安全埋葬可能在控制和预防该病毒方面发挥重要作用。在本研究中,我们考虑了四种不同情况下埃博拉病毒动力学的数学建模框架,包括安全和不安全的埋葬做法、疫苗接种和不同效率的治疗干预措施。这项研究的目的是表明及时治疗埃博拉病毒如何导致病毒得到有效控制,最重要的是,尸体的安全埋葬如何有助于控制传播。收稿日期2018年11月27日收稿日期2019年12月18日
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引用次数: 5
Substrate Transport in Cylindrical Multi-Capillary Beds with Axial Diffusion 轴向扩散圆柱形多毛细管床中的底物输运
Q3 Mathematics Pub Date : 2023-01-01 DOI: 10.30707/lib10.1.1682535100.316029
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引用次数: 0
A Hybrid Differential Equations Model for the Dynamics of Single and Double Strand Breaks of Cancer Cells Treated by Radiotherapy 放疗后癌细胞单链和双链断裂动力学的混合微分方程模型
Q3 Mathematics Pub Date : 2023-01-01 DOI: 10.30707/lib9.1.1681913305.295521
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引用次数: 1
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