BioASP

Answer Set Programming for Systems Biology

Overview | Applications | Answer Set Programming | Who we are

Applications

The BioASP software collection includes the following applications. For more details on each application, please visit the corresponding Application page. BioASP applications are freely available as python packages under General Public License (GPL) and they can be easily installed on your system. However you may want to try their Web service before doing so (example input data is provided in-place).


Reasoning on metabolic network models

meneco - Metabolic network completion

This application can be used to check if a draft metabolic network provides the synthesis routes to comply with certain functionality. If this fails, meneco can automatically complete the network using reactions from a reference network stemming from other organisms until the observed functionality is provided.

Application page | Web service | Citation


precursor - Compute minimal metabolic precursors

Given a metabolic reaction network and a set of target metabolites, this application computes the subset minimal sets of precursor metabolites needed to produce the targets.

Application page | Web service


Reasoning on Boolean models

caspo - Reasoning on the response of logical signaling networks

The aim of this application is to implement a pipeline for automated reasoning on logical signaling networks. Features provided by caspo include, learning of logical networks from experiments, design new experiments in order to reduce the uncertainty, and finding intervention strategies to control the biological system.

Application page | Web service | Citation


Reasoning on influence graph models

ExDesi - Experiment planning to discriminate influence graph models

Modern methods for the inference of cellular networks from experimental data often express nondeterminism by proposing an ensemble of candidate models with similar properties. To further discriminate among these model candidates, and to find the biological truth, new experiments need to be carried out. Building upon a notion of consistency between biochemical/genetic regulations and measurements profiles of cell activity, ExDesi determines those experiments that discriminate most of the candidates while minimizing the costs. ExDesi implements experiment planning with interaction graph models and sign consistency methods to determine experiments which are most suitable to deliver results that allow for a refinement of the model.

Application page

iggy - Consistency of influence graphs models and observed systems behaviors

This application is a further development of ingranalyze it supports the incorporation of uncertain data and discovers inconsistencies in data or network, applies minimal repairs and predicts the behavior of unmeasured species. In particular, it distinguishes strong predictions (e.g. increase of a node level) and weak predictions (e.g., node level increases or remains unchanged) enlarging the overall predictive power of the approach. Also included is a the tool opt_graph which computes networks which have an optimal fitness regarding the data of not only a single experiment but a set of experiments. #### Our latest opt_graph implementation is included in this package! ####

Application page | Citation


ingranalyze - Sign consistency on influence graphs

This application confronts biological networks given as interaction graphs with experimental data given as signs that represent the concentration changes between two measurements. It allows to decover inconsistencies in data or network, proposes minimal repairs and predicts the behavior of unmeasured species.

Application page | Web service | Citation

Other projects using ingranalyze

CytoASP is a Cytoscape plugin that enables consistency checking, prediction and repair of network models while providing customizable visualizations in Cytoscape. Citation | Sources


Reasoning on integrated metabolic gene regulation models

shogen - Identification of functional gene units

This application combines gene sequence information and metabolic reaction network into one model. Together with data about metabolites involved in a chemical pathway, the Shortest Gene Segments (SGS) are proposed which activate the metabolic reactions of such a pathway.

Application page | Web service | Citation