Search results
Results From The WOW.Com Content Network
The eukaryotic cell cycle is very complex and is one of the most studied topics, since its misregulation leads to cancers. It is possibly a good example of a mathematical model as it deals with simple calculus but gives valid results. Two research groups [1] [2] have produced several models of the cell cycle simulating several organisms. They ...
Cell-based models are mathematical models that represent biological cells as discrete entities. Within the field of computational biology they are often simply called agent-based models [1] of which they are a specific application and they are used for simulating the biomechanics of multicellular structures such as tissues. to study the influence of these behaviors on how tissues are organised ...
The original model proposed by Graner and Glazier contains cells of two types, with different adhesion energies for cells of the same type and cells of a different type. Each cell type also has a different contact energy with the medium, and the cell volume is assumed to remain close to a target value. The Hamiltonian is formulated as:
A cellular automaton (pl. cellular automata, abbrev. CA) is a discrete model of computation studied in automata theory. Cellular automata are also called cellular spaces, tessellation automata, homogeneous structures, cellular structures, tessellation structures, and iterative arrays. [2]
This page was last edited on 23 January 2022, at 09:23 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.
The Hata model is a radio propagation model for predicting the path loss of cellular transmissions in exterior environments, valid for microwave frequencies from 150 to 1500 MHz. It is an empirical formulation based on the data from the Okumura model , and is thus also commonly referred to as the Okumura–Hata model . [ 1 ]
Cell lineage denotes the developmental history of a tissue or organ from the fertilized egg. [1] This is based on the tracking of an organism's cellular ancestry due to the cell divisions and relocation as time progresses, this starts with the originator cells and finishing with a mature cell that can no longer divide. [2] [3]
In the original Chua-Yang CNN (CY-CNN) processor, the state of the cell was a weighted sum of the inputs and the output was a piecewise linear function.However, like the original perceptron-based neural networks, the functions it could perform were limited: specifically, it was incapable of modeling non-linear functions, such as XOR.