Modelling cell metabolism: a review on constraint-based steady-state and kinetic approaches
Studying cell metabolism serves a plethora of objectives such as the enhancement of
bioprocess performance, and advancement in the understanding of cell biology, of drug …
bioprocess performance, and advancement in the understanding of cell biology, of drug …
NNV: the neural network verification tool for deep neural networks and learning-enabled cyber-physical systems
This paper presents the Neural Network Verification (NNV) software tool, a set-based
verification framework for deep neural networks (DNNs) and learning-enabled cyber …
verification framework for deep neural networks (DNNs) and learning-enabled cyber …
[PDF][PDF] Selected Topics in Mathematical Modeling: Some New Trends
N Kyurkchiev - … to Academician Blagovest Sendov (1932-2020) …, 2020 - researchgate.net
1.1 Introduction 12 1.2 Preliminaries 13 1.3 Main Results 14 1.3. 1 Approximating the” real
wealth data” 18 1.3. 2 Approximating the” growth data (mean height) of sunflower plants” 18 …
wealth data” 18 1.3. 2 Approximating the” growth data (mean height) of sunflower plants” 18 …
Phenotypic memory in quorum sensing
Quorum sensing (QS) is a regulatory mechanism used by bacteria to coordinate group
behavior in response to high cell densities. During QS, cells monitor the concentration of …
behavior in response to high cell densities. During QS, cells monitor the concentration of …
On the chemical meaning of some growth models possessing Gompertzian‐type property
Growth models are often used when modelling various processes in life sciences, ecology,
demography, social sciences, etc. Dynamical growth models are usually formulated in terms …
demography, social sciences, etc. Dynamical growth models are usually formulated in terms …
Biochemical parameter estimation vs. benchmark functions: A comparative study of optimization performance and representation design
Computational Intelligence methods, which include Evolutionary Computation and Swarm
Intelligence, can efficiently and effectively identify optimal solutions to complex optimization …
Intelligence, can efficiently and effectively identify optimal solutions to complex optimization …
[BOOK][B] Some New Logistic Differential Models: Properties and Applications
Some New Logistic Differential Models Page 1 Vesselin Kyurkchiev Anton Iliev Asen Rahnev
Nikolay Kyurkchiev Some New Logistic Differential Models Properties and Applications In this …
Nikolay Kyurkchiev Some New Logistic Differential Models Properties and Applications In this …
New approach to the stability of chemical reaction networks: Piecewise linear in rates Lyapunov functions
Piecewise-linear in rates (PWLR) Lyapunov functions are introduced for a class of chemical
reaction networks (CRNs). In addition to their simple structure, these functions are robust …
reaction networks (CRNs). In addition to their simple structure, these functions are robust …
[HTML][HTML] Nonlinearity and anthocyanin colour expression: A mathematical analysis of anthocyanin association kinetics and equilibria
Anthocyanins are polyphenolic compounds that provide pigmentation in plants as reflected
by pH-dependent structural transformations between the red flavylium cation, purple …
by pH-dependent structural transformations between the red flavylium cation, purple …
Computational intelligence for parameter estimation of biochemical systems
In the field of Systems Biology, simulating the dynamics of biochemical models represents
one of the most effective methodologies to understand the functioning of cellular processes …
one of the most effective methodologies to understand the functioning of cellular processes …