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In nature, population dynamics are subject to multiple sources of stochasticity. State-space models (SSMs) provide an ideal framework for incorporating both environmental noises and measurement errors into dynamic population models. In this paper, we present a recently developed method, Particle Markov Chain Monte Carlo (Particle MCMC), for parameter(More)
Cyclic AMP response element-binding protein (CREB) family can regulate biological functions of various types of cells and has relation with esophageal cancer cell migration and invasion. Cyclic AMP response element modulator-1 (CREM-1) is one member of the family with limited acquaintance. This study was conducted to investigate the effect of CREM-1 on(More)
Spatial aggregation and self-similarity are two important properties in species spatial distribution analysis and modeling. The aggregation parameter k in the negative binomial distribution model and fractal dimension are two widely used measures of spatial aggregation and self-similarity, respectively. In this paper, we attempt to describe spatial(More)
BACKGROUND Human hepatocellular carcinoma (HCC) is one of the most common fatal cancers and an important health problem worldwide, but its mechanism is still unclear. Microtubule (MT) kinesin motor proteins orchestrate a variety of cellular processes (e.g. mitosis, motility and organelle transportation) and have been involved in human carcinogenesis. KIF3B,(More)
Stochastic dynamical systems have been increasingly used in natural sciences. Data assimilation, which can effectively combine observation data and theoretical models, improves the applicability of dynamical models. In this study, a statistical data assimilation method, Bayesian filtering, is presented. Its performance is examined with a dynamical model of(More)
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