# SIDURI: from an integrative information system to a user-friendly portal for data analysis and visualisation dedicated to fermentation

Agnès Barnabé, Erwan Le Floch, Jonathan Duperrier, Mariène Wan, Aaron Millan-oropeza, Thomas Lacroix, Jonathan Mineau-Cesari, Sophie Schbath, Valentin Loux

<figure><img src="image_1.png" /></figure>

## To cite this version:

Agnès Barnabé, Erwan Le Floch, Jonathan Duperrier, Mariène Wan, Aaron Millan-oropeza, et al. SIDURI: from an integrative information system to a user-friendly portal for data analysis and visualisation dedicated to fermentation. Journées Ouvertes Biologie, Informatique, Mathématiques 2025, Jul 2025, Bordeaux, France. pp.1. hal-05142051

HAL Id: hal-05142051

https://hal.inrae.fr/hal-05142051v1

Submitted on 3 Jul 2025

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

<figure><img src="image_2.png" /></figure>
# SIDURI: from an integrative information system to a user-friendly portal for data analysis and visualisation dedicated to fermentation

Global warming highlights the need to renew our dietary habits and develop sustainable, durable, safe and healthy foods. The public-private partnership "Ferments du Futur" (FdF), led by INRAE and Ania, was launched in 2022 to fund research projects submitted by public laboratories or companies to accelerate research and innovation in food systems. One of its engagements is to provide a data warehouse named **Siduri**, which will centralise data produced and selected public datasets.

The **Migale** bioinformatics facility manages the conception and deployment of **Siduri**. Its development is based on the existing ontology-driven information system (IS) OpenSILEX [1]. Additionally, recommended bioinformatics tools and pipelines will be proposed for all types of data analyses related to fermentation within **Siduri**. To achieve this, we built a tools catalogue, at first for genomics analyses, and explored interoperability between **Galaxy** and **Siduri**.

<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /></figure>

OpenSILEX comes with a swagger API in Python. This API enables the extraction of a dataset and the associated metadata by simply providing a URI, which is available through the web interface.

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

BioBlend [4] is the Python client for using the Galaxy API. It enables interoperability with Siduri by uploading data in a Galaxy history from a URL, accessing the list of workflows, launching an analysis and retrieving outputs.

## Conclusion and Perspectives

In this poster, we present the bioinformatics work in Siduri and the plus-value of data analysis in an information system. The development of an evolutive bioinformatics catalogue offers a wide range of possibilities to analyse raw and elaborated data stored in Siduri.

In the near future, we expect to expand the bioinformatics catalogue due to a larger variety of fermentation data that will be welcomed in Siduri. The following achievements concern the interactive visualisation of raw data and results produced by Galaxy, enabling cross-projects analyses.

Siduri data warehouse is accessible at https://siduri.migale.inrae.fr/ (registration required).

## References

1. Neveu et al. (2019). Dealing with multi-source and multi-scale information in plant phenomics: the ontology-driven Phenotyping Hybrid Information System. New Phytologist, 221 (1), p.588-601.
2. Ison J et al. (2019). The bio.tools registry of software tools and data resources for the life sciences. Genome Biol., 20(1), p.164.
3. Ison J et al. (2013). EDAM: an ontology of bioinformatics operations, types of data and identifiers, topics and formats. Bioinformatics, 29(10) p.1325-32.
4. Sloggett et al. (2013). BioBlend: automating pipeline analyses within Galaxy and CloudMan. Bioinformatics, 29 (13), p. 1685-1686.

## Acknowledgment

This work benefited from French government funding managed by the "Agence Nationale de la Recherche" as part of France 2030 under the reference ANR-22-GDFF-0001.