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[Preprint]. 2024 Aug 30:arXiv:2408.17320v1.

BioBricks.ai: A Versioned Data Registry for Life Sciences Data Assets

Yifan Gao  1 , Zakariyya Mughal  2 , Jose A Jaramillo-Villegas  3   4 , Marie Corradi  5 , Alexandre Borrel  6 , Ben Lieberman  2 , Suliman Sharif  2 , John Shaffer  2 , Karamarie Fecho  7   8 , Ajay Chatrath  9 , Alexandra Maertens  1 , Marc A T Teunis  5 , Nicole Kleinstreuer  10 , Thomas Hartung  1   11 , Thomas Luechtefeld  1   2
Affiliations

BioBricks.ai: A Versioned Data Registry for Life Sciences Data Assets

Yifan Gao et al. ArXiv. .

Update in

  • BioBricks.ai: a versioned data registry for life sciences data assets.
    Gao Y, Mughal Z, Jaramillo-Villegas JA, Corradi M, Borrel A, Lieberman B, Sharif S, Shaffer J, Fecho K, Chatrath A, Maertens A, Teunis MAT, Kleinstreuer N, Hartung T, Luechtefeld T. Gao Y, et al. Front Artif Intell. 2025 Aug 13;8:1599412. doi: 10.3389/frai.2025.1599412. eCollection 2025. Front Artif Intell. 2025. PMID: 40880880 Free PMC article.

Abstract

Researchers in biomedical research, public health and the life sciences often spend weeks or months discovering, accessing, curating, and integrating data from disparate sources, significantly delaying the onset of actual analysis and innovation. Instead of countless developers creating redundant and inconsistent data pipelines, BioBricks.ai offers a centralized data repository and a suite of developer-friendly tools to simplify access to scientific data. Currently, BioBricks.ai delivers over ninety biological and chemical datasets. It provides a package manager-like system for installing and managing dependencies on data sources. Each 'brick' is a Data Version Control git repository that supports an updateable pipeline for extraction, transformation, and loading data into the BioBricks.ai backend at https://biobricks.ai. Use cases include accelerating data science workflows and facilitating the creation of novel data assets by integrating multiple datasets into unified, harmonized resources. In conclusion, BioBricks.ai offers an opportunity to accelerate access and use of public data through a single open platform.

Keywords: BioBricks.ai; Bioinformatics; Cheminformatics; Data Integration; Machine Learning; Public Health Data.

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Conflict of interest statement

10.Conflict of Interest The authors declare the following potential conflicts of interest regarding the research and publication of this paper: BioBricks is a product developed by Insilica LLC, and many of the authors are employees of Insilica LLC. As such, there may be a perceived or real financial interest in the outcomes of the research and the development of BioBricks. The authors affirm that their contributions to the research and the manuscript were conducted with scientific integrity and without bias influenced by their association with Insilica LLC.

Figures

Figure 1
Figure 1
Top left - A code example to install, load, and analyze ToxRefDB data. Bottom left - the result of running the code example. Right - tabular data in bar chart form.
Figure 2
Figure 2
Left - truncated versions of the (1) .bb/dependencies.txt and (2) dvc.yaml file in the ChemHarmony BioBrick. Center, the 3-table schema of ChemHarmony, a simple chemical activities dataset with a substances, properties, and activities table. Right shows how to count activities by source by installing the ChemHarmony brick and using it with Apache Spark with the resulting table in lower right.
See this image and copyright information in PMC

References

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