Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Aug 17;19(8):e1011403.
doi: 10.1371/journal.pcbi.1011403. eCollection 2023 Aug.

BALDR: A Web-based platform for informed comparison and prioritization of biomarker candidates for type 2 diabetes mellitus

Agnete T Lundgaard  1 , Frédéric Burdet  2 , Troels Siggaard  1 , David Westergaard  1 , Danai Vagiaki  1 , Lisa Cantwell  1 , Timo Röder  1 , Dorte Vistisen  3   4 , Thomas Sparsø  5 , Giuseppe N Giordano  6 , Mark Ibberson  2 , Karina Banasik  1 , Søren Brunak  1
Affiliations

BALDR: A Web-based platform for informed comparison and prioritization of biomarker candidates for type 2 diabetes mellitus

Agnete T Lundgaard et al. PLoS Comput Biol. .

Abstract

Novel biomarkers are key to addressing the ongoing pandemic of type 2 diabetes mellitus. While new technologies have improved the potential of identifying such biomarkers, at the same time there is an increasing need for informed prioritization to ensure efficient downstream verification. We have built BALDR, an automated pipeline for biomarker comparison and prioritization in the context of diabetes. BALDR includes protein, gene, and disease data from major public repositories, text-mining data, and human and mouse experimental data from the IMI2 RHAPSODY consortium. These data are provided as easy-to-read figures and tables enabling direct comparison of up to 20 biomarker candidates for diabetes through the public website https://baldr.cpr.ku.dk.

PubMed Disclaimer

Conflict of interest statement

I have read the journal’s policy and the authors of this manuscript have the following competing interests: D.Vi. is employed at Novo Nordisk A/S and holds shares in Novo Nordisk A/S. T.Sp. is employed at Novo Nordisk A/S and holds shares in Novo Nordisk A/S. T.Si. holds shares in Armata Pharmaceuticals Inc., Intellia Therapeutics Inc., Moderna Inc., and IGM Biosciences Inc. S.B. holds shares in Intomics A/S, Hoba Therapeutics Aps, Novo Nordisk A/S, Lundbeck A/S, and managing board memberships in Proscion A/S and Intomics A/S. All other authors have no conflicts of interest to declare.

Figures

Fig 1
Fig 1. Schematic representation of the BALDR pipeline.
The BALDR pipeline consists of three steps: Data integration, Query, and User report. In the Data integration step, data from multiple data sources is captured and consolidated into the BALDR database accessible to the BALDR source code. In the query step, the user selects up to 20 candidates using UniProt IDs or gene names. The targets are linked by UniProt IDs to the BALDR database and the BALDR source code runs using Rmarkdown. Lastly, a User report is produced containing five main sections: Functional information, Experimental evidence, Disease association, Mechanistic evidence, and Biomarker potential. Image credit: Openclipart.org.
See this image and copyright information in PMC

References

    1. Obermayer A, Dong L, Hu Q, Golden M, Noble JD, Rodriguez P, et al.. DRPPM-EASY: A Web-Based Framework for Integrative Analysis of Multi-Omics Cancer Datasets. Biology (Basel). 2022;11. doi: 10.3390/biology11020260 - DOI - PMC - PubMed
    1. Castellano-Escuder P, Gonzalez-Domnguez R, Carmona-Pontaque F, Andrés-Lacueva C, Sanchez-Pla A. POMAShiny: A user-friendly web-based workflow for metabolomics and proteomics data analysis. PLoS Comput Biol. 2021;17: e1009148. doi: 10.1371/journal.pcbi.1009148 - DOI - PMC - PubMed
    1. Becker AK, Dörr M, Felix SB, Frost F, Grabe HJ, Lerch MM, et al.. From heterogeneous healthcare data to disease-specific biomarker networks: A hierarchical Bayesian network approach. PLoS Comput Biol. 2021;17. doi: 10.1371/journal.pcbi.1008735 - DOI - PMC - PubMed
    1. Roglic G, World Health Organization. Global report on diabetes. 2016.
    1. NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4.4 million participants. Lancet. 2016;387: 1513–1530. doi: 10.1016/S0140-6736(16)00618-8 - DOI - PMC - PubMed

Publication types