inst/shiny-examples/GeneVyuha/about.md

In TheJacksonLaboratory/GeneVyuha: GeneVyuha is a systems biology tool to study the role of noise and parameter variation in gene regulatory circuits.

Gene Circuit Explorer: Visualize, simulate, and analyze gene regulatory networks

Simulate a single model with specific parameters or use random circuit perturbation with and without stochastic effects (RACIPE and sRACIPE) for a comprehensive understanding of gene regulatory networks in cell populations using systems-biology approaches.

Gene Circuit Explorer implements a randomization-based method for gene circuit modeling. It allows us to study the effect of both the gene expression noise and the parametric variation on any gene regulatory circuit (GRC) using only its topology, and simulates an ensemble of models with random kinetic parameters at multiple noise levels. Statistical analysis of the generated gene expressions reveals the basin of attraction and stability of various phenotypic states and their changes associated with intrinsic and extrinsic noises. sRACIPE provides a holistic picture to evaluate the effects of both the stochastic nature of cellular processes and the parametric variation.

If you use this website, please consider citing the papers Interrogating the topological robustness of gene regulatory circuits by randomization published in PLoS computational biology 13 (3), e1005456 and Role of noise and parametric variation in the dynamics of gene regulatory circuits published in npj Systems Biology and Applications, 4, 40 (2018).

Tutorial

Using GeneVyuha

GeneVyuha tab can be used to simulate the time series of a gene regulatory network with any parameters. User can upload a topology and then Gene Circuit Explorer will generate a simulation with some random parameter values. User can modify any or all of these parameters and generate time trajectories with these modified parameter values. Stochastic trajectories can also be generated by changing the noise level (which is set to zero by default). User can draw bifurcation plots for any parameter to analyze how parameteric variation affects the gene expression patterns. For more details on how to use this tab, please click on the image below to watch a video on youtube.

Using RACIPE

RACIPE (random circuit perturbation) approach generates a large number of models with random parameters to mimic the parameters in a cell population. The models with these parameters are simulated and the final gene expressions obtained for each model are used for further statistical analysis. RACIPE tab shows these statistical behavior of models mimicking a cell population. The data can be filtered for various parameters so that one can observe how a change in parameter value affects the gene expression patterns. For example, limiting the production rate of a gene can be considered as knockdown of that particular gene. For more details on how to use RACIPE tab, please click on the image below to watch a video on youtube.

Using sRACIPE

sRACIPE (stochastic random circuit perturbation) approach incorporates stochastic effects in the RACIPE approach to better model a cell population. The statistiics are calculated at multiple noise levels using two simulation schemes: (a) constant noise based method which estimates the basin of attraction of various phenotypic states and (b) annelaing based method which provides an estimate of the relative stability of the different phenotypic states. For more details on how to use sRACIPE tab, please click on the image below to watch a video on youtube.

Using Database

In addition to allowing the users to simulate any gene regulatory network, Gene Circuit Explorer keeps a database of network simulations for specific cases (for example, published networks from the literature). The database will be updated over time to include more networks. Networks with "_TS" in their name depit the time trajectories for specific model parameters, for example, trajectories for limit cycle oscillations in a three gene network. Similarly, network with "_stochastic" in their name have been simulated with non zero noise levels. The database can be searched by network name as well as by genes in the network. For more details on how to use the database, please click on the image below to watch a video on youtube.

TheJacksonLaboratory/GeneVyuha documentation built on May 5, 2019, 2:44 a.m.