Evidence map›Paper›PMID 39253636›Full record

ArticleArXiv2024

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

Yifan Gao, Zakariyya Mughal, Jose A Jaramillo-Villegas, Marie Corradi, Alexandre Borrel, Ben Lieberman, Suliman Sharif, John Shaffer, Karamarie Fecho, Ajay Chatrath and 5 more

Abstract readPreprint
PubMed Full text at PMC
In one paragraph

Article in ArXiv, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Yifan GaoCenter For Alternative to Animal Testing, Johns Hopkins University, Baltimore, MD, USA.
Zakariyya MughalInsilica, Bethesda, MD, USA.
Jose A Jaramillo-VillegasLaboratory for Research in Complex Systems, Menlo Park, California, USA.
Marie CorradiInnovative Testing in Life Sciences & Chemistry, University of Applied Sciences Utrecht, Utrecht, The Netherlands.
Alexandre BorrelInotiv, Research Triangle Park, North Carolina, USA.
Ben LiebermanInsilica, Bethesda, MD, USA.
Suliman SharifInsilica, Bethesda, MD, USA.
John ShafferInsilica, Bethesda, MD, USA.
Karamarie FechoRenaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Ajay ChatrathDepartment of Neurological Surgery, Washington University in Saint Louis, Saint Louis, Missouri.
Alexandra MaertensCenter For Alternative to Animal Testing, Johns Hopkins University, Baltimore, MD, USA.
Marc A T TeunisInnovative Testing in Life Sciences & Chemistry, University of Applied Sciences Utrecht, Utrecht, The Netherlands.
Nicole KleinstreuerNTP Interagency Center for the Evaluation of Alternative Methods, Research Triangle Park, NC, USA.
Thomas HartungCenter For Alternative to Animal Testing, Johns Hopkins University, Baltimore, MD, USA.
Thomas LuechtefeldCenter For Alternative to Animal Testing, Johns Hopkins University, Baltimore, MD, USA.

Funding

Pilot Project ProgramP30ES032756 · NIEHS · JOHNS HOPKINS UNIVERSITY · PI Marsha Wills-Karp · 2022 to 2026
$6.0M
BioBricks-Env: AI driven, open-source, modular, composable platform to organize, store, retrieve, extract, and integrate environmental health & risk related dataR43ES036069 · NIEHS · INSILICA, LLC · PI LUECHTEFELD, THOMAS · 2024 to 2024
$296k
ToxIndex-CPG: Machine learning driven platform integrating a hazard susceptibility database to quantify chemical toxicity factors, predict risk levels and classify biological responsesR43ES033851 · NIEHS · INSILICA, LLC · PI LUECHTEFELD, THOMAS · 2022 to 2022
$256k
NIEHS NIH HHS P30 ES032756NIEHS NIH HHS R43 ES033851NIEHS NIH HHS R43 ES036069
6 · The paper itself

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.

Indexed as

BioBricks.aiBioinformaticsCheminformaticsData IntegrationMachine LearningPublic Health Data

Identifiers

PMID39253636
PMCPMC11383443

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.