239 citations · 412 across the 24 of their papers we have counts for
30 papers
Analyzing Post-transcriptional Regulation in Stochastic Gene Expression Models Using Partitioned Poisson Arrivals
Kenny Wong, Argenis Arriojas, Sho Inaba +3
Gene expression is a stochastic process that allows for fluctuations in protein levels that can give rise to phenotypic heterogeneity within a population of genetically identical c…
Global redistribution and local migration in semi-discrete host-parasitoid population dynamic models
Brooks Emerick, Abhyudai Singh
Host-parasitoid population dynamics is often probed using a semi-discrete/hybrid modeling framework. Here, the update functions in the discrete-time model connecting year-to-year c…
Network Inference in Systems Biology: Recent Developments, Challenges, and Applications
Michael M. Saint-Antoine, Abhyudai Singh
One of the most interesting, difficult, and potentially useful topics in computational biology is the inference of gene regulatory networks (GRNs) from expression data. Although re…
Evaluating Pruning Methods in Gene Network Inference
Michael M. Saint-Antoine, Abhyudai Singh
One challenge in gene network inference is distinguishing between direct and indirect regulation. Some algorithms, including ARACNE and Phixer, approach this problem by using pruni…
Moment analysis of linear time-varying dynamical systems with renewal transitions
Mohammad Soltani, Abhyudai Singh
Stochastic dynamics of several systems can be modeled via piecewise deterministic time evolution of the state, interspersed by random discrete events. Within this general class of…
Moment Analysis of Stochastic Hybrid Systems Using Semidefinite Programming
Khem Raj Ghusinga, Andrew Lamperski, Abhyudai Singh
This paper proposes a semidefinite programming based method for estimating moments of a stochastic hybrid system (SHS). For polynomial SHSs -- which consist of polynomial continuou…
The Linear-Noise Approximation and moment-closure approximations for stochastic chemical kinetics
Abhyudai Singh, Ramon Grima
This is a short review of two common approximations in stochastic chemical and biochemical kinetics. It will appear as Chapter 6 in the book "Quantitative Biology: Theory, Computat…
Estimating stationary characteristic functions of stochastic systems via semidefinite programming
Khem Raj Ghusinga, Andrew Lamperski, Abhyudai Singh
This paper proposes a methodology to estimate characteristic functions of stochastic differential equations that are defined over polynomials and driven by Lévy noise. For such sys…
Linear piecewise-deterministic Markov processes with families of random discrete events
Mohammad Soltani, Abhyudai Singh
We consider a class of piecewise-deterministic Markov processes where the state evolves according to a linear dynamical system. This continuous time evolution is interspersed by di…
Prediction and Control of Projectile Impact Point using Approximate Statistical Moments
Cenk Demir, Abhyudai Singh
In this paper, trajectory prediction and control design for a desired hit point of a projectile is studied. Projectiles are subject to environment noise such as wind effect and mea…
Control design and analysis of a stochastic network control system
Mohammad Soltani, Abhyudai Singh
A Network Control System (NCS) consists of control components that interact with the plant over a shared network. The system dynamics of a NCS could be subject to noise arising fro…
Driving an Ornstein--Uhlenbeck Process to Desired First-Passage Time Statistics
Khem Raj Ghusinga, Vaibhav Srivastava, Abhyudai Singh
First-passage time (FPT) of an Ornstein-Uhlenbeck (OU) process is of immense interest in a variety of contexts. This paper considers an OU process with two boundaries, one of which…
Approximate moment dynamics for polynomial and trigonometric stochastic systems
Khem Raj Ghusinga, Mohammad Soltani, Andrew Lamperski +2
Stochastic dynamical systems often contain nonlinearities which make it hard to compute probability density functions or statistical moments of these systems. For the moment comput…
Analysis and Control of Stochastic Systems using Semidefinite Programming over Moments
Andrew Lamperski, Khem Raj Ghusinga, Abhyudai Singh
This paper develops a unified methodology for probabilistic analysis and optimal control design for jump diffusion processes defined by polynomials. For such systems, the evolution…
Bounds on stationary moments in stochastic chemical kinetics
Khem Raj Ghusinga, Cesar A. Vargas-Garcia, Andrew Lamperski +1
In the stochastic formulation of chemical kinetics, the stationary moments of the population count of species can be described via a set of linear equations. However, except for so…
Effect of gene-expression bursts on stochastic timing of cellular events
Khem Raj Ghusinga, Abhyudai Singh
Gene expression is inherently a noisy process which manifests as cell-to-cell variability in time evolution of proteins. Consequently, events that trigger at critical threshold lev…
Conditions for cell size homeostasis: A stochastic hybrid systems approach
César Augusto Vargas-García, Mohammad Soltani, Abhyudai Singh
A ubiquitous feature of living cells is their growth over time followed by division into daughter cells. How isogenic cell populations maintain size homeostasis, i.e., a narrow dis…
Cell-cycle coupled expression minimizes random fluctuations in gene product levels
Mohammad Soltani, Abhyudai Singh
Expression of many genes varies as a cell transitions through different cell-cycle stages. How coupling between stochastic expression and cell cycle impacts cell-to-cell variabilit…
Stochastic optimal control using semidefinite programming for moment dynamics
Andrew Lamperski, Khem Raj Ghusinga, Abhyudai Singh
This paper presents a method to approximately solve stochastic optimal control problems in which the cost function and the system dynamics are polynomial. For stochastic systems wi…
Moment dynamics for a class of time-triggered stochastic hybrid systems
Mohammad Soltani, Abhyudai Singh
Stochastic Hybrid Systems (SHS) constitute an important class of mathematical models that integrate discrete stochastic events with continuous dynamics. The time evolution of stati…
Gene expression noise is affected differentially by feedback in burst frequency and burst size
Pavol Bokes, Abhyudai Singh
Inside individual cells, expression of genes is stochastic across organisms ranging from bacterial to human cells. A ubiquitous feature of stochastic expression is burst-like synth…
A mechanistic first--passage time framework for bacterial cell-division timing
Khem Raj Ghusinga, Cesar A. Vargas-Garcia, Abhyudai Singh
How exponentially growing cells maintain size homeostasis is an important fundamental problem. Recent single-cell studies in prokaryotes have uncovered the adder principle, where c…
Optimal regulation of protein degradation to schedule cellular events with precision
Khem Raj Ghusinga, Abhyudai Singh
An important occurrence in many cellular contexts is the crossing of a prescribed threshold by a regulatory protein. The timing of such events is stochastic as a consequence of the…
Decomposing variability in protein levels from noisy expression, genome duplication and partitioning errors during cell-divisions
Mohammad Soltani, Cesar Augusto Vargas-Garcia, Duarte Antunes +1
Inside individual cells, expression of genes is inherently stochastic and manifests as cell-to-cell variability or noise in protein copy numbers. Since proteins half-lives can be c…