# SPONGE: simple prior omics network GEnerator

## TL;DR

SPONGE is a Python tool that generates updated gene regulatory and protein interaction networks using biological databases to improve network modeling.

## Contribution

SPONGE provides an updated and easily adaptable way to generate prior biological networks for use with tools like PANDA.

## Key findings

- SPONGE integrates data from JASPAR and STRING to create gene regulatory and protein interaction networks.
- The tool is compatible with PANDA and the NetZoo family of tools while offering customizable parameters.
- SPONGE simplifies the use of prior biological knowledge in network modeling with sensible defaults.

## Abstract

Gene regulatory networks modelled from experimental data can be improved through the use of prior biological knowledge, e.g. transcription factor binding. There are several tools that utilize this information. However, the prior networks used with them are often not updated and may fail to reflect the most up-to-date information. Here we present SPONGE, a Python module designed to access information across biological databases, chiefly JASPAR and STRING, to model two types of networks—a prior gene regulatory network mapping transcription factors to genes based on their predicted binding sites, and a prior protein-protein interaction network mapping potential interactions between transcription factors. SPONGE is mainly designed to work with the PANDA algorithm and the corresponding NetZoo family of tools. However, the networks are provided in an easily adaptable format for other tools. SPONGE was designed with ease of use in mind, and it provides sensible default values for all of its parameters while giving the users the freedom to fine-tune them.

The code for the Python module and the documentation can be found in our GitHub repository.