Computational models for inferring biochemical networks [PDF]
, 2014 Biochemical networks are of great practical importance. The interaction of biological compounds in cells has been enforced to a proper understanding by the numerous bioinformatics projects, which contributed to a vast amount of biological information ...
Crina Grosan +20 more
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A reaction network approach to the convergence to equilibrium of quantum Boltzmann equations for Bose gases [PDF]
E S A I M: Control, Optimisation and Calculus of Variations, 2016 When the temperature of a trapped Bose gas is below the Bose-Einstein transition temperature and above absolute zero, the gas is composed of two distinct components: the Bose-Einstein condensate and the cloud of thermal excitations.
G. Craciun, Minh-Binh Tran
semanticscholar +1 more source
Estimation and discrimination of stochastic biochemical circuits from time-lapse microscopy data. [PDF]
PLoS ONE, 2012 The ability of systems and synthetic biologists to observe the dynamics of cellular behavior is hampered by the limitations of the sensors, such as fluorescent proteins, available for use in time-lapse microscopy.
David Thorsley, Eric Klavins
doaj +1 more source
Generic Strategies for Chemical Space Exploration [PDF]
, 2014 Computational approaches to exploring "chemical universes", i.e., very large sets, potentially infinite sets of compounds that can be constructed by a prescribed collection of reaction mechanisms, in practice suffer from a combinatorial explosion.
Andersen, Jakob L. +3 more
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Efficient multi-fidelity computation of blood coagulation under flow.
PLoS Computational Biology, 2023 Clot formation is a crucial process that prevents bleeding, but can lead to severe disorders when imbalanced. This process is regulated by the coagulation cascade, a biochemical network that controls the enzyme thrombin, which converts soluble fibrinogen
Manuel Guerrero-Hurtado +8 more
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A chemical-reaction-optimization-based neuro-fuzzy hybrid network for stock closing price prediction
Financial Innovation, 2019 Accurate prediction of stock market behavior is a challenging issue for financial forecasting. Artificial neural networks, such as multilayer perceptron have been established as better approximation and classification models for this domain.
S. Nayak, B. Misra
semanticscholar +1 more source
Permutation invariant graph-to-sequence model for template-free retrosynthesis and reaction prediction [PDF]
Journal of Chemical Information and Modeling, 2021 Synthesis planning and reaction outcome prediction are two fundamental problems in computer-aided organic chemistry for which a variety of data-driven approaches have emerged.
Zhengkai Tu, Connor W. Coley
semanticscholar +1 more source
Spatial and Temporal Sensing Limits of Microtubule Polarization in Neuronal Growth Cones by Intracellular Gradients and Forces [PDF]
, 2012 Neuronal growth cones are the most sensitive amongst eukaryotic cells in responding to directional chemical cues. Although a dynamic microtubule cytoskeleton has been shown to be essential for growth cone turning, the precise nature of coupling of the ...
Athale, Chaitanya A., Mahajan, Saurabh
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RuleMonkey: software for stochastic simulation of rule-based models
BMC Bioinformatics, 2010 Background The system-level dynamics of many molecular interactions, particularly protein-protein interactions, can be conveniently represented using reaction rules, which can be specified using model-specification languages, such as the BioNetGen ...
Hlavacek William S +5 more
doaj +1 more source
Constructing and visualizing chemical reaction networks from pi-calculus models [PDF]
Formal Aspects of Computing, 2013 Abstract The π -calculus, in particular its stochastic version the stochastic π -calculus, is a common modeling formalism to concisely describe the chemical reactions occurring in biochemical systems.
John, M. +4 more
openaire +5 more sources