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palmerito0 edited this page Apr 24, 2023 · 8 revisions

Welcome to the kboolnet wiki! You'll find documentation for the various scripts and functions of the Kufareva Lab's rxncon pipeline here.

What is kboolnet?

kboolnet is an R package and set of associated R and Python scripts created for the automated verification, validation, and visualization (VVV) of rxncon models.

What is rxncon?

The rxncon formalism, developed by Marcus Krantz and Edda Klipp at Humboldt University, represents a signaling network as a bipartite directed graph of nodes of two types, states and reactions. State nodes represent the state of proteins at the domain/residue level. These states are connected to each other by reaction nodes, which represent uni- or bi-molecular transformations which consume a state(s) and produce another state(s). State nodes are also connected to reaction nodes by contingency edges, which indicate how a particular state regulates a reaction.

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A rxncon model's specification consists of a list of reactions, a list of contingencies upon these reactions, a list of reaction types, and a list of modification types. These are typically encoded as spreadsheets in the Microsoft XLS/XLSX format; a simplified example of such a spreadsheet may be downloaded here.

Where does kboolnet come in?

Once written, a rxncon model can be converted into an executable Boolean network. This network can then be simulated beginning at an initial state until it reaches a finite-size loop of Boolean states (hereafter an "attractor"). The kboolnet toolkit can be used to verify, validate, and visualize the behavior of these Boolean networks and the associated rxncon model. The toolkit also provides an interface with Google Drive, allowing for the cloud storage and collaborative editing of rxncon models.

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Verification

Verification is the process of ensuring a model is internally consistent and is carried out by the VerifyModel.R script.

Validation

Visualization

How do I use kboolnet?

Who developed kboolnet?

The kboolnet package and associated scripts were developed by Willow Carretero Chavez, Marcus Krantz, Edda Klipp, and Irina Kufareva. Many thanks are given to Alexis Llona and other members of the Kufareva Lab for assistance in testing kboolnet.

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