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This paper considers the behavior of discrete and continuous mathematical models for gene expression in the presence of transcriptional/translational bursting. We treat this problem in generality with respect to the distribution of the…

Probability · Mathematics 2015-10-15 M. C. Mackey , M. Tyran-Kamińska , R. Yvinec

We study a stochastic model proposed recently in the genetic literature to explain the heterogeneity of cell populations or of gene products. Cells are located in two colonies, whose sizes fluctuate as birth and migration processes in…

Populations and Evolution · Quantitative Biology 2007-05-23 Martin Gander , Christian Mazza , Hansklaus Rummler

In this paper, we consider a subclass of piecewise deterministic Markov processes with a Polish state space that involve a deterministic motion punctuated by random jumps, occurring in a Poisson-like fashion with some state-dependent rate,…

Probability · Mathematics 2024-05-28 Dawid Czapla

In biophysics, the search for analytical solutions of stochastic models of cellular processes is often a challenging task. In recent work on models of gene expression, it was shown that a mapping based on partitioning of Poisson arrivals…

Biological Physics · Physics 2018-05-09 Hugo Tschirhart , Thierry Platini

We introduce a novel training principle for probabilistic models that is an alternative to maximum likelihood. The proposed Generative Stochastic Networks (GSN) framework is based on learning the transition operator of a Markov chain whose…

Machine Learning · Computer Science 2014-05-27 Yoshua Bengio , Éric Thibodeau-Laufer , Guillaume Alain , Jason Yosinski

A multiplicative stochastic process with the lower bound lognormally distributed is investigated. For the process, the model is constructed, and its distribution function (involving four parameters) and the related statistical properties…

Data Analysis, Statistics and Probability · Physics 2024-01-19 Ken Yamamoto , Yoshihiro Yamazaki

Consider a system performing a continuous-time random walk on the integers, subject to catastrophes occurring at constant rate, and followed by exponentially-distributed repair times. After any repair the system starts anew from state zero.…

Understanding the differentiation, a biological process from a multipotent stem or progenitor state to a mature cell is critically important. We develop a theoretical framework to quantify the underlying potential landscape and biological…

Molecular Networks · Quantitative Biology 2012-02-29 Haidong Feng , Jin Wang

We examine immunostaining experimental data for the formation of the strip 2 of $even-skipped$ ($eve$) transcripts on $D.$ $melanogaster$ embryos. An estimate of the factor converting immunofluorescence intensity units into molecular…

Subcellular Processes · Quantitative Biology 2016-02-10 Guilherme N. Prata , José Eduardo M. Hornos , Alexandre F. Ramos

According to recent experimental evidence, the architecture of a promoter, defined as the number, strength and regulatory role of the operators that control the promoter, plays a major role in determining the level of cell-to-cell…

Molecular Networks · Quantitative Biology 2015-05-19 Alvaro Sanchez , Hernan Garcia , Daniel Jones , Rob Phillips , Jane' Kondev

Stochastic reaction network models are widely utilized in biology and chemistry to describe the probabilistic dynamics of biochemical systems in general, and gene interaction networks in particular. Most often, statistical analysis and…

Quantitative Methods · Quantitative Biology 2017-10-18 Eugenio Cinquemani

Gene expression is a stochastic process in which cells produce biomolecules essential to the function of life. Modern experimental methods allow for the measurement of biomolecules at single-cell and single-molecule resolution over time.…

Quantitative Methods · Quantitative Biology 2022-07-01 Zachary R Fox

We propose a stochastic model for evolution. Births and deaths of species occur with constant probabilities. Each new species is associated with a fitness sampled from the uniform distribution on [0,1]. Every time there is a death event…

Probability · Mathematics 2010-11-09 Herve Guiol , Fabio P. Machado , Rinaldo B. Schinazi

We study the local regularity and multifractal nature of the sample paths of jump diffusion processes, which are solutions to a class of stochastic differential equations with jumps. This article extends the recent work of Barral {\it et…

Probability · Mathematics 2017-09-06 Xiaochuan Yang

Phenotypic variation is a hallmark of cellular physiology. Metabolic heterogeneity, in particular, underpins single-cell phenomena such as microbial drug tolerance and growth variability. Much research has focussed on transcriptomic and…

Molecular Networks · Quantitative Biology 2019-01-31 Mona K. Tonn , Philipp Thomas , Mauricio Barahona , Diego A Oyarzún

Markov cohort state-transition models have been the standard approach for simulating the prognosis of patients or, more generally, the life trajectories of individuals over a time period. Current approaches for estimating the variance of a…

Applications · Statistics 2022-04-07 Rowan Iskandar , Cassandra Berns

In this paper we consider large state space continuous time Markov chains (MCs) arising in the field of systems biology. For density dependent families of MCs that represent the interaction of large groups of identical objects, Kurtz has…

Performance · Computer Science 2015-03-04 Alessio Angius , Gianfranco Balbo , Marco Beccuti , Enrico Bibbona , Andras Horvath , Roberta Sirovich

This paper consider a highly general dissemination model that keeps track of the stochastic evolution of the distribution of wealth over a set of agents. There are two types of events: (i) units of wealth externally arrive, and (ii) units…

Probability · Mathematics 2022-07-12 K. M. D. Chan , M. R. H. Mandjes

We propose a formalism to analyze discrete stochastic processes with finite-state-level N. By using an (N+1)-dimensional representation of su(2) Lie algebra, we re-express the master equation to a time-evolution equation for the state…

Statistical Mechanics · Physics 2015-10-27 Takashi Arai

The ordinary contact process is used to model the spread of a disease in a population. In this model, each infected individual waits an exponentially distributed time with parameter 1 before becoming healthy. In this paper, we introduce and…

Probability · Mathematics 2011-11-10 Erik I. Broman
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