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To celebrate Hans Frauenfelder's achievements, we examine energy(-like) "landscapes" for complex living systems. Energy landscapes summarize all possible dynamics of some physical systems. Energy(-like) landscapes can explain some…

Quantitative Methods · Quantitative Biology 2021-10-18 Lars Koopmans , Hyun Youk

The purpose of this research was to compare the robustness and performance of a local and global optimization algorithm when given the task of fitting the parameters of a common non-linear dose-response model utilized in the field of…

Neural and Evolutionary Computing · Computer Science 2020-12-18 Mark Connor , Michael O'Neill

An important task for many if not all the scientific domains is efficient knowledge integration, testing and codification. It is often solved with model construction in a controllable computational environment. In spite of that, the…

Molecular Networks · Quantitative Biology 2018-11-06 Emilia M. Wysocka , Valery Dzutsati , Tirthankar Bandyopadhyay , Laura Condon , Sahil Garg

High-throughput experimental techniques and bioinformatics tools make it possible to obtain reconstructions of the metabolism of microbial species. Combined with mathematical frameworks such as flux balance analysis, which assumes that…

We develop a path-based approach to continuous-time random walks on networks with arbitrarily weighted edges. We describe an efficient numerical algorithm for calculating statistical properties of the stochastic path ensemble. After…

Populations and Evolution · Quantitative Biology 2014-08-19 Michael Manhart , Alexandre V. Morozov

Learning governing equations from a family of data sets which share the same physical laws but differ in bifurcation parameters is challenging. This is due, in part, to the wide range of phenomena that could be represented in the data sets…

Numerical Analysis · Mathematics 2017-09-07 Hayden Schaeffer , Giang Tran , Rachel Ward

Population-based learning paradigms, including evolutionary strategies, Population-Based Training (PBT), and recent model-merging methods, combine fast within-model optimisation with slower population-level adaptation. Despite their…

Machine Learning · Computer Science 2026-03-26 Giacomo Borghi , Hyesung Im , Lorenzo Pareschi

This paper studies the parameter tuning problem of positive linear systems for optimizing their stability properties. We specifically show that, under certain regularity assumptions on the parametrization, the problem of finding the…

Optimization and Control · Mathematics 2019-11-26 Masaki Ogura , Masako Kishida , James Lam

This report proposes a novel framework for a rigorous robustness analysis of stochastic biochemical systems. The technique is based on probabilistic model checking. We adapt the general definition of robustness introduced by Kitano to the…

Numerical Analysis · Computer Science 2013-10-18 Lubos Brim , Milan Ceska , Sven Drazan , David Safranek

Modeling and parameter estimation for neuronal dynamics are often challenging because many parameters can range over orders of magnitude and are difficult to measure experimentally. Moreover, selecting a suitable model complexity requires a…

Dynamical Systems · Mathematics 2018-01-31 J. E. Rubin , B. Krauskopf , H. M. Osinga

Genetic fitness optimization using small populations or small population updates across generations generally suffers from randomly diverging evolutions. We propose a notion of highly probable fitness optimization through feasible…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Paul Vitanyi

Protein interaction networks aim to summarize the complex interplay of proteins in an organism. Early studies suggested that the position of a protein in the network determines its evolutionary rate but there has been considerable…

Molecular Networks · Quantitative Biology 2007-05-23 Ino Agrafioti , Jonathan Swire , James Abbott , Derek Huntley , Sarah Butcher , Michael P. H. Stumpf

Optimization techniques play a crucial role in estimating parameters and state information for nonlinear systems. However, some critical aspects of these problems have received little attention in previous research. In this paper, we…

Optimization and Control · Mathematics 2023-06-02 Kaushal Kumar

Stochastic modeling and simulation provide powerful predictive methods for the intrinsic understanding of fundamental mechanisms in complex biochemical networks. Typically, such mathematical models involve networks of coupled jump…

Information Theory · Computer Science 2013-08-02 Yannis Pantazis , Markos A. Katsoulakis , Dionisios G. Vlachos

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. Here we show that, according to its original…

Quantitative Methods · Quantitative Biology 2018-02-07 Alejandro F. Villaverde , Julio R. Banga

Fluorescent and luminescent gene reporters allow us to dynamically quantify changes in molecular species concentration over time on the single cell level. The mathematical modeling of their interaction through multivariate dynamical models…

Quantitative Methods · Quantitative Biology 2009-07-07 Michal Komorowski , Barbel Finkenstadt , Claire V. Harper , David A. Rand

Real-world optimisation problems are often dynamic. Previously good solutions must be updated or replaced due to changes in objectives and constraints. It is often claimed that evolutionary algorithms are particularly suitable for dynamic…

Neural and Evolutionary Computing · Computer Science 2016-07-13 Duc-Cuong Dang , Thomas Jansen , Per Kristian Lehre

Living systems continuously transform matter and energy through the chemical processes that constitute their metabolism. The overall metabolic rate of an organism correlates positively with its body mass, however both the exact scaling…

Soft Condensed Matter · Physics 2026-03-19 Efe Ilker , Michael Hinczewski , Xingbo Yang , Frank Jülicher

Given an unknown dynamic system such as a coupled harmonic oscillator with $n$ springs and point masses. We are often interested in gaining insights into its physical parameters, i.e. stiffnesses and masses, by observing trajectories of…

Machine Learning · Computer Science 2021-03-22 Gregory Barber , Mulugeta A. Haile , Tzikang Chen

One of the basic frameworks in science views behavioral products as a process within a dynamic system. The mechanism might be seen as a representation of many instances of centralized control in real time. Many real systems, however,…

Dynamical Systems · Mathematics 2019-08-19 Chulwook Park
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