14 papers · ranked by Valyu relevance
Kyu Hyong Park, Réka Albert
Comprehensive analysis of the dynamics of Boolean models of biological systems is hampered by the exponentially large state space. Here we introduce the succession-diagram-based Markov chain (SD Markov chain), a coarse-grained representation that uses trap spaces (unescapable state subspaces) of the Boolean model as…
Alan Kleinman
A correct understanding of the DNA evolution of drug resistance is critical in developing strategies for suppressing and preventing this process. The Kishony Mega-Plate Experiment demonstrates this important phenomenon that occurs in the practice of medicine, that of the evolution of drug-resistance. The evolutionary…
Jordan M Culp, Donovan M Ashby, Antis G George, G. Campbell Teskey + 2 more
Mesoscale cortical dynamics consist of stereotyped patterns of recurring activity motifs, however the constraints and rules governing how these motifs assemble over time is not known. Here we propose a Continuous Time Markov Chain model that probabilistically describes the temporal sequence of activity motifs using…
Frederic von Wegner, Gesine Hermann, Inken Tödt, Inga Karin Todtenhaupt + 1 more
Higher-order syntax properties of EEG microstate sequences offer insight into the transition dynamics of functional brain networks. We here define higher-order syntax as microstate sequence properties that are not explained by the first-order transition matrix, and we postulate three requirements that surrogate data…
John J. Vastola, Tejas Ramdas, Samuel J. Gershman
Cells store information in part by attaching molecular marks to proteins and DNA. But because marks can be randomly removed (e.g., due to ambient phosphatase activity) and added (e.g., due to ambient kinase activity), information encoding may be poor, and in the worst case marks may only store information on the time…
Kevin Song, Dmitrii E. Makarov, Etienne Vouga
A key theoretical challenge posed by single-molecule studies is the inverse problem of deducing the underlying molecular dynamics from the time evolution of low-dimensional experimental observables. Toward this goal, a variety of low-dimensional models have been proposed as descriptions of single-molecule signals…
David H. Margarit, Marcela V. Reale, Ariel F. Scagliotti, Lilia M. Romanelli
Absorbing Markov Chains are an important mathematical tool used for different applications in science. On the other hand, cancer and its metastases in children have a significant impact on health due to their degree of lethality. Therefore, the aim of this work is to model the metastatic pathways of the main childhood…
Alon Korngreen
Markov models are widely used to describe the gating kinetics of voltage-gated ion channels, but increasing model complexity can introduce parameters that are difficult to constrain from macroscopic measurements. In this study, I used global variance-based Sobol sensitivity analysis to examine how model topology…
Sebastian J. Schreiber
A population exhibits an Allee effect when there is a critical density below which it goes extinct and above which it persists. Classical models with environmental stochasticity predict inevitable extinction, stemming from the assumption that environmental variation is normally distributed with rare but arbitrary large…
Ankit Gupta, Mustafa Khammash
Dynamic analysis and control of living cells relies on mathematical representations of cellular processes that are themselves modelled as biomolecular reaction networks. Stochastic models for biomolecular reaction networks are commonly employed for analysing intracellular networks having constituent species with…
Anthony J. Dominic, Thomas Sayer, Siqin Cao, Thomas E. Markland + 2 more
The ability to predict and understand the complex molecular motions occurring over diverse timescales ranging from picoseconds to seconds and even hours occurring in biological systems remains one of the largest challenges to chemical theory. Markov State Models (MSMs), which provide a memoryless description of the…
Luigi Catacuzzeno, Maria Vittoria Leonardi, Fabio Franciolini, Carmen Domene + 2 more
Molecular dynamics (MD) simulation of biological processes has always been a very challenging task due to the long timescales of the processes involved and the challenges associated with handling the large amount of output data. Markov State Models (MSMs) have been recently introduced as a powerful tool in this area of…
Hyukpyo Hong, Mark Jayson Cortez, Yu-Yu Cheng, Hang Joon Kim + 3 more
Cell function is regulated by gene regulatory networks (GRNs) defined by protein-mediated interaction between constituent genes. Despite advances in experimental techniques, we can still measure only a fraction of the processes that govern GRN dynamics. To infer the properties of GRNs using partial observation…
Shangbin Ma, Youming Li
The global potential of a chemical reaction network has many applications and is closely related to the stochastic detailed balance. However, many fundamental questions concerning stochastic detailed balance remain unresolved, such as whether it depends on the system volume and how to construct new systems that satisfy…