# SBOannotator
<img align="right" src="SBOannotator_logo.png" alt="drawing" width="200"/>
**SBOannotator: a Python tool for the automated assignment of Systems Biology Ontology terms**
[](http://opensource.org/licenses/LGPL-3.0)
[](https://github.com/draeger-lab/SBOannotator/releases/)
[](https://badge.fury.io/py/SBOannotator)
[](https://pypistats.org/packages/SBOannotator)
[](https://doi.org/10.1093/bioinformatics/btad437)
*Developers* : [Nantia Leonidou](https://github.com/NantiaL) & Elisabeth Fritze
___________________________________________________________________________________________________________
### How to cite the SBOannotator?
The SBOannotator is described in this article: https://doi.org/10.1093/bioinformatics/btad437
### Overview
SBOannotator is the first standalone tool that automatically assigns SBO terms to multiple entities of a given SBML model,
The main focus lies on the reactions, as the correct assignment of precise SBO annotations requires their extensive classification.
Our implementation does not consider only top-level terms but examines the functionality of the underlying enzymes to
allocate precise and highly specific ontology terms to biochemical reactions.
Transport reactions are examined separately and are classified based on the mechanism of molecule transport.
Pseudo-reactions that serve modeling purposes are given reasonable terms to distinguish between biomass production and the
import or export of metabolites. Finally, other model entities, such as metabolites and genes, are annotated with appropriate terms.
Including SBO annotations in the models will enhance the reproducibility, usability, and analysis of biochemical networks.
### Web Application
Web application hosted at [TueVis](https://tuevis.cs.uni-tuebingen.de/sboannotator/) is accessible and ready to use at [sbo-annotator-tuevis.cs.uni-tuebingen.de/](https://sbo-annotator-tuevis.cs.uni-tuebingen.de/)
### Installation
```
pip install SBOannotator
```
### Prerequisites
This tool has the following dependencies:
python >=3.8.5
Packages:
* sqlite3
* libsbml
* collections
* requests
* json
* time
### Input data
+ `doc`: an SBML document
+ `model_libsbml`: SBML model of interest
+ `modelType`: type of modelling framework (see below)
+ `modelAnnotated`: True, if model already includes annotations with EC numbers
+ `database_name`: name of imported database, without extension
+ `new_filename`: file name for output model
Types of modelling framework accepted:
- constraint-based
- logical
- continuous
- discrete
- hybrid
- logical
### Outputs
+ `model_libsbml`: Annotated libSBML model
### Usage
To run SBOannotator use the `main.py` script and modify the parameters in the `readSBML` and `sbo_annotator`
functions as wished.
If ERROR occurs, check the current version of Python:
- `python --version'`
- `conda install python>=3.8.5`
### Exemplary models and Results
The folder `models/BiGG_Models` contains all the tested models as they were downloaded from
the BiGG database.
The annotated models after using the SBOannotator are listed in the folder named `models/Annotated_Models`.
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