The exploration of such questions in larger, multi-attractor GRNs, that are grounded on experimental data and underlie realistic cases of cell differentiation, and in which the state-space presents a more complex structure, has largely been left behind.
Recently, it has become possible to postulate GRN models grounded on experimental data.
In Fig. 1(a) we show a GRN network, grounded on experimental data, proposed in Ref. [9].
We illustrate and test our proposal with a GRN model grounded on experimental data for cell fate specification during organ formation in early Arabidopsis thaliana flower development.
Albeit highly abstract at first sight, the applicability of Boolean GRNs, as well as derived conceptual implications, have been supported extensively both by experimental observations [ 5, 16, 17] and by theoretical GRNs grounded on experimental data [ 11, 18].
This paper deals with the tomographic inversion of experimental data acquired by a stepped-frequency ground penetrating radar (SFGPR).
The validity and feasibility of the self-developed ground-based ELF/VLF receiver system is evaluated by first results of experimental data that show the temporal variation of broadband ELF/VLF wave spectral intensity in Wuhan (30.54 °N, 114.37 °E).
The functionality of the algorithms, and ultimately the proposed technology, is demonstrated using a variety of experimental data, obtained from both moving receivers (roof top railways, ground moving vehicle and a helicopter) as well as a stationary one.
Many ground-based, aircraft-based, and satellite-borne experiments have been conducted, and a huge amount of experimental data has been recorded using dedicated receivers.
The ground reaction force is modelled as the force supported by this nonlinear element, whose parameters are identified from several sets of experimental data.
