A stochastic quasi-Newton method for large-scale nonconvex optimization with applications
Ensuring the positive definiteness and avoiding ill conditioning of the Hessian update in the
stochastic Broyden-Fletcher-Goldfarb-Shanno (BFGS) method are significant in solving …
stochastic Broyden-Fletcher-Goldfarb-Shanno (BFGS) method are significant in solving …
Global optimization approach for parameter estimation in stochastic dynamic models of biosystems
C Sequeiros, I Otero-Muras, C Vázquez… - … /ACM Transactions on …, 2022 - ieeexplore.ieee.org
Mechanistic dynamic models have become an essential tool for understanding biomolecular
networks and other biological systems. Biochemical stochasticity can be extremely important …
networks and other biological systems. Biochemical stochasticity can be extremely important …
Bayesian inference using qualitative observations of underlying continuous variables
ED Mitra, WS Hlavacek - Bioinformatics, 2020 - academic.oup.com
Motivation Recent work has demonstrated the feasibility of using non-numerical, qualitative
data to parameterize mathematical models. However, uncertainty quantification (UQ) of such …
data to parameterize mathematical models. However, uncertainty quantification (UQ) of such …
Modeling the temporal dynamics of master regulators and CtrA proteolysis in Caulobacter crescentus cell cycle
The cell cycle of Caulobacter crescentus involves the polar morphogenesis and an
asymmetric cell division driven by precise interactions and regulations of proteins, which …
asymmetric cell division driven by precise interactions and regulations of proteins, which …
Algorithm 1007: QNSTOP—quasi-Newton algorithm for stochastic optimization
BD Amos, DR Easterling, LT Watson… - ACM Transactions on …, 2020 - dl.acm.org
QNSTOP consists of serial and parallel (OpenMP) Fortran 2003 codes for the quasi-Newton
stochastic optimization method of Castle and Trosset for stochastic search problems. A …
stochastic optimization method of Castle and Trosset for stochastic search problems. A …
Parameter estimation of stochastic models based on limited data
Progress in experimental techniques enables a more accurate quantification of genes,
mRNA, and proteins at the single cell level. Provided with limited time series data from …
mRNA, and proteins at the single cell level. Provided with limited time series data from …
Mathematical Model of the Cell Cycle Control and Asymmetry Development in Caulobacter crescentus
C Xu - 2022 - vtechworks.lib.vt.edu
Caulobacter crescentus goes through a classic dimorphic cell division cycle to adapt to the
stringent environment and reduce intraspecific competition. Caulobacter mother cell gives …
stringent environment and reduce intraspecific competition. Caulobacter mother cell gives …
[PDF][PDF] Systems Approaches to the Biology of the Spindle Pole Body
R Howell, P Thorpe, A Csikász-Nagy - 2020 - kclpure.kcl.ac.uk
The yeast centrosome or Spindle Pole Body (SPB) is an organelle situated in the nuclear
membrane, where it nucleates spindle microtubules and acts as a signalling hub. The SPB …
membrane, where it nucleates spindle microtubules and acts as a signalling hub. The SPB …
[HTML][HTML] Finding acceptable parameter regions of stochastic Hill functions for multisite phosphorylation mechanism
Multisite phosphorylation plays an important role in regulating switch-like protein activity and
has been used widely in mathematical models. With the development of new experimental …
has been used widely in mathematical models. With the development of new experimental …
Stochastic Modeling and Simulation of Multiscale Biochemical Systems
M Chen - 2019 - vtechworks.lib.vt.edu
Numerous challenges arise in modeling and simulation as biochemical networks are
discovered with increasing complexities and unknown mechanisms. With the improvement …
discovered with increasing complexities and unknown mechanisms. With the improvement …