https://github.com/saezlab/shinycnor
Shiny application for the CellNOptR packages
https://github.com/saezlab/shinycnor
Last synced: 11 months ago
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Shiny application for the CellNOptR packages
- Host: GitHub
- URL: https://github.com/saezlab/shinycnor
- Owner: saezlab
- License: gpl-3.0
- Created: 2019-04-05T15:56:18.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2022-06-10T14:35:52.000Z (about 4 years ago)
- Last Synced: 2025-01-22T07:37:41.721Z (over 1 year ago)
- Language: R
- Size: 370 KB
- Stars: 2
- Watchers: 3
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
## Welcome to the Shiny application for the CellNOpt packages
CellNOpt (from CellNetOptimizer; a.k.a. CNO) is a software used for creating logic-based models of signal transduction networks using different logic formalisms (Boolean, probabilistic logic, or differential equations). CellNOpt uses information on signaling pathways encoded as a Prior Knowledge Network, and trains it against high-throughput biochemical data to create cell-specific models.
### Implemented Approaches
ShinyCNOR is still under development, and the following approaches are implemented or in the process of being implemented.
#### CellNOptR
CellNOptR for Boolean formalism. It contains the core functions as well as the boolean and steady states version. It implements the workflow described in Saez-Rodriguez et al Mol Sys Bio 2009, with extended capabilities for multiple time points.
#### CNORprob
CNORprob for Probablistic Logic formalism. It is a probabilistic logic variant of CellNOpt which allows for quantitative optimisation of logical network for (quasi-)steady-state data. The core optimisation pipeline is derived from FALCON: a toolbox for the fast contextualization of logical networks.
#### CNORode
CNORode for logic-based ODE formalism. It is an ODE add-on to CellNOptR. It is based on the method of (Wittmann et al BMC Sys Bio 2009), also implemented in the tool Odefy (Krusiek et al BMC Bioinf 2010).