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In principle, the generalized master equation can be used to efficiently compute the macroscopic first passage time (FPT) distribution of a complex stochastic system from short-term microscopic simulation data. However, computing its…

Computational Physics · Physics 2007-05-23 David Shalloway

Biological structure and function depend on complex regulatory interactions between many genes. A wealth of gene expression data is available from high-throughput genome-wide measurement technologies, but effective gene regulatory network…

Molecular Networks · Quantitative Biology 2016-03-28 Arwen Vanice Bradley , Ye Henry Li , Bokyung Choi , Wing Hung Wong

Software Testing is a process to identify the quality and reliability of software, which can be achieved through the help of proper test data. However, doing this manually is a difficult task due to the presence of number of predicate nodes…

Software Engineering · Computer Science 2014-01-22 Yeresime Suresh , Santanu Ku. Rath

Multi-goal path finding (MGPF) aims to find a closed and collision-free path to visit a sequence of goals orderly. As a physical travelling salesman problem, an undirected complete graph with accurate weights is crucial for determining the…

Robotics · Computer Science 2023-12-25 Yuan Huang

We consider a model of mRNA production governed by the dynamics of a gene that exists in three possible states -- inactive, poised and active. The transitions between the adjacent states are controlled by stochastic processes characterized…

Dynamical Systems · Mathematics 2022-05-20 Boris Rubinstein , Jay Unruh , Julia Zeitlinger

We consider the problem of approximating the moment generating function (MGF) of a truncated random variable in terms of the MGF of the underlying (i.e., untruncated) random variable. The purpose of approximating the MGF is to enable the…

Statistics Theory · Mathematics 2007-06-13 Ronald W. Butler , Andrew T. A. Wood

Accurate identification of protein-nucleotide binding sites is fundamental to deciphering molecular mechanisms and accelerating drug discovery. However, current computational methods often struggle with suboptimal performance due to…

Machine Learning · Computer Science 2026-03-17 Yiming Gao , Liuyi Xu , Pengshan Cui , Yining Qian , An-Yang Lu , Xianpeng Wang

In this paper, we combine ideas from two different scientific traditions: 1) graph transformation systems (GTSs) stemming from the theory of formal languages and concurrency, and 2) mean field approximations (MFAs), a collection of…

Logic in Computer Science · Computer Science 2020-09-11 Vincent Danos , Tobias Heindel , Ricardo Honorato-Zimmer , Sandro Stucki

Magnetic resonance fingerprinting (MRF) can successfully recover quantitative multi-parametric maps of human tissue in a very short acquisition time. Due to their pseudo-random nature, the large spatial undersampling artifacts can be…

Many fundamental cellular processes involve small numbers of molecules. When numbers are small, fluctuations dominate, and stochastic models, which account for these fluctuations, are required. In this chapter, we describe minimal…

Molecular Networks · Quantitative Biology 2015-10-05 Andrew Mugler , Sean Fancher

The inference of gene regulatory networks (GRNs) is a foundational stride towards deciphering the fundamentals of complex biological systems. Inferring a possible regulatory link between two genes can be formulated as a link prediction…

Machine Learning · Computer Science 2025-04-25 Binon Teji , Swarup Roy

Simulating the mechanical response of advanced materials can be done more accurately using concurrent multiscale models than with single-scale simulations. However, the computational costs stand in the way of the practical application of…

Machine Learning · Computer Science 2024-02-21 J. Storm , I. B. C. M. Rocha , F. P. van der Meer

Generating graph-structured data requires learning the underlying distribution of graphs. Yet, this is a challenging problem, and the previous graph generative methods either fail to capture the permutation-invariance property of graphs or…

Machine Learning · Computer Science 2022-06-16 Jaehyeong Jo , Seul Lee , Sung Ju Hwang

We propose a new score-based model with one-step sampling. Previously, score-based models were burdened with heavy computations due to iterative sampling. For substituting the iterative process, we train a standalone generator to compress…

Computer Vision and Pattern Recognition · Computer Science 2023-09-21 Senmao Ye , Fei Liu

Gene expression in individual cells is highly variable and sporadic, often resulting in the synthesis of mRNAs and proteins in bursts. Bursting in gene expression is known to impact cell-fate in diverse systems ranging from latency in HIV-1…

Molecular Networks · Quantitative Biology 2016-02-17 Niraj Kumar , Abhyudai Singh , Rahul V. Kulkarni

Quantitative modeling of post-transcriptional regulation process is a challenging problem in systems biology. A mechanical model of the regulatory process needs to be able to describe the available spatio-temporal protein concentration and…

Machine Learning · Statistics 2016-10-18 Mu Niu , Zhenwen Dai , Neil Lawrence , Kolja Becker

Graph Generation is a recently introduced enhanced Column Generation algorithm for solving expanded Linear Programming relaxations of mixed integer linear programs without weakening the expanded relaxations which characterize these methods.…

Optimization and Control · Mathematics 2022-02-04 Julian Yarkony , Amelia Regan

Proteins are polymerized by cyclic machines called ribosome which use their messenger RNA (mRNA) track also as the corresponding template and the process is called translation. We explore, in depth and detail, the stochastic nature of the…

Biological Physics · Physics 2009-11-13 Ashok Garai , Debashish Chowdhury , T. V. Ramakrishnan

The dynamics of short-lived mRNA results in bursts of protein production in gene regulatory networks. We investigate the propagation of bursting noise between different levels of mathematical modelling, and demonstrate that conventional…

Molecular Networks · Quantitative Biology 2016-01-14 Yen Ting Lin , Tobias Galla

Semi-autogenous grinding (SAG) mills play a pivotal role in the grinding circuit of mineral processing plants. Accurate prediction of SAG mill throughput as a crucial performance metric is of utmost importance. The potential of applying…

Neural and Evolutionary Computing · Computer Science 2024-01-30 Zahra Ghasemi , Mehdi Nesht , Chris Aldrich , John Karageorgos , Max Zanin , Frank Neumann , Lei Chen