Architect: a tool for producing high-quality metabolic models through improved enzyme annotation

Motivation: Constraints-based modeling is a powerful framework for understanding growth of organisms. Results from such simulation experiments can be affected at least in part by the quality of the metabolic models used. Reconstructing a metabolic network manually can produce a high-quality metabolic model but is a time-consuming task. At the same time, current methods for automating the process typically transfer metabolic function based on sequence similarity, a process known to produce many false positives. Results: We created Architect, a pipeline for automatic metabolic model reconstruction from protein sequences. First, it performs enzyme annotation through an ensemble approach, whereby a likelihood score is computed for an EC prediction based on predictions from existing tools; for this step, our method shows both increased precision and recall compared to individual tools. Next, Architect uses these annotations to construct a high-quality metabolic network which is then gap-filled based on likelihood scores from the ensemble approach. The resulting metabolic model is output in SBML format, suitable for constraints-based analyses. Through comparisons of enzyme annotations and curated metabolic models, we demonstrate improved performance of Architect over other state-of-the-art tools. Availability: Code for Architect is available at https://github.com/ParkinsonLab/Architect.

A Modular Visual Model of Energy Metabolism in Human Skeletal Muscle

The paper presents a modification of a multi-compartmental mathematical model describing the dynamics of intracellular species concentrations and fluxes in human muscle at rest. A modular representation of a complex model is proposed, which provides the possibility of rapid expansion and modification of the model compartments to account for the complex organization of muscle cells and the limitations of the rate of diffusion of metabolites between intracellular compartments. To illustrate the work of the model, intracellular response in human skeletal muscle to acute aerobic two-legged cycle ergometer training was considered. The model in SBML format is available at http://wiki.biouml.org/index.php/Muscle_metabolism.

PetriScape - A plugin for discrete Petri net simulations in Cytoscape

SummarySystems biology plays a central role for biological network analysis in the post-genomic era. Cytoscape is the standard bioinformatics tool offering the community an extensible platform for computational analysis of the emerging cellular network together with experimental omics data sets. However, only few apps/plugins/tools are available for simulating network dynamics in Cytoscape 3. Many approaches of varying complexity exist but none of them have been integrated into Cytoscape as app/plugin yet. Here, we introduce PetriScape, the first Petri net simulator for Cytoscape. Although discrete Petri nets are quite simplistic models, they are capable of modeling global network properties and simulating their behaviour. In addition, they are easily understood and well visualizable. PetriScape comes with the following main functionalities: (1) import of biological networks in SBML format, (2) conversion into a Petri net, (3) visualization as Petri net, and (4) simulation and visualization of the token flow in Cytoscape. PetriScape is the first Cytoscape plugin for Petri nets. It allows a straightforward Petri net model creation, simulation and visualization with Cytoscape, providing clues about the activity of key components in biological networks.

SimpleSBML: A Python package for creating and editing SBML models

SummaryIn this technical report we describe a simple extension to python-libSBML that allows users of Python to more easily construct SBML based models. The most commonly used package for constructing SBML models in Python is python-libSBML based on the C/C++ library libSBML. python-libSBML supports a comprehensive set of model types, but is difficult for new users to learn and requires long scripts to create even the simplest models. We present SimpleSBML, a package that allows users to add species, parameters, reactions, events, and rules to a libSBML model with only one command for each. Models can be exported to SBML format, and SBML files can be imported and converted to SimpleSBML commands that creates each element in a new model. This allows users to create new models and edit existing models for use with other software.Accessibility and ImplementationSimpleSBML is publicly available and licensed under the liberal Apache 2.0 open source license. It supports SBML levels 2 and 3. Its only dependency is libSBML. It is supported on Windows and Mac OS X. All code has been deposited at the GitHub site https://github.com/sys-bio/[email protected] or [email protected]