Results 11 to 20 of about 26,998 (224)
PLoS Computational Biology, 2022 Time series single-cell RNA sequencing (scRNA-seq) data are emerging. However, dynamic inference of an evolving cell population from time series scRNA-seq data is challenging owing to the stochasticity and nonlinearity of the underlying biological ...
Qi Jiang, Shuo Zhang, Lin Wan
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What can causal networks tell us about metabolic pathways? [PDF]
PLoS Computational Biology, 2012 Graphical models describe the linear correlation structure of data and have been used to establish causal relationships among phenotypes in genetic mapping populations. Data are typically collected at a single point in time.
Rachael Hageman Blair +2 more
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Hyperbolastic Models from a Stochastic Differential Equation Point of View
Mathematics, 2021 A joint and unified vision of stochastic diffusion models associated with the family of hyperbolastic curves is presented. The motivation behind this approach stems from the fact that all hyperbolastic curves verify a linear differential equation of the ...
Antonio Barrera +2 more
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REHEATFUNQ (REgional HEAT-Flow Uncertainty and aNomaly Quantification) 2.0.1: a model for regional aggregate heat flow distributions and anomaly quantification [PDF]
Geoscientific Model DevelopmentSurface heat flow is a geophysical variable that is affected by a complex combination of various heat generation and transport processes. The processes act on different lengths scales, from tens of meters to hundreds of kilometers.
M. J. Ziebarth +2 more
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Towards a Stochastic Paradigm: From Fuzzy Ensembles to Cellular Functions
Molecules, 2018 The deterministic sequence → structure → function relationship is not applicable to describe how proteins dynamically adapt to different cellular conditions. A stochastic model is required to capture functional promiscuity, redundant sequence
Monika Fuxreiter
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Inference from gated first-passage times
Physical Review Research, 2023 First-passage times provide invaluable insight into fundamental properties of stochastic processes. Yet, various forms of gating mask first-passage times and differentiate them from actual detection times.
Aanjaneya Kumar +3 more
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Efficient representation of boolean decision structures through Boolean function optimization
Frontiers in Artificial IntelligenceA binary decision tree (BDT) is stochastic and depth-dependent when inference is performed. The lower and upper bounds are derived from the minimum and maximum heights of the leaf nodes.
Maddimsetti Srinivas, Debdoot Sheet
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PLoS Computational Biology, 2022 Understanding and characterising biochemical processes inside single cells requires experimental platforms that allow one to perturb and observe the dynamics of such processes as well as computational methods to build and parameterise models from the ...
Anđela Davidović +3 more
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Limits of Inference in Complex Systems: When Stochastic Models Become Indistinguishable
Physical Review XRobust inference for stochastic dynamical systems is often hampered by sparse sampling and the absence of closed-form likelihoods. We introduce a Monte Carlo path-inference framework that leverages full-path statistics and bridge processes to deliver ...
Javier Aguilar +2 more
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