BALDR : A Web-based platform for informed comparison and prioritization of biomarker candidates for type 2 diabetes mellitus
(2023) In PLoS Computational Biology 19(8 August).- 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... (More)
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.
(Less)
- author
- organization
- publishing date
- 2023-08
- type
- Contribution to journal
- publication status
- published
- subject
- in
- PLoS Computational Biology
- volume
- 19
- issue
- 8 August
- article number
- e1011403
- publisher
- Public Library of Science (PLoS)
- external identifiers
-
- scopus:85168773432
- pmid:37590326
- ISSN
- 1553-734X
- DOI
- 10.1371/journal.pcbi.1011403
- language
- English
- LU publication?
- yes
- id
- c6cc388e-ec92-4b12-8c19-cf16e345b7f5
- date added to LUP
- 2023-11-01 11:04:55
- date last changed
- 2024-07-12 10:57:02
@article{c6cc388e-ec92-4b12-8c19-cf16e345b7f5, abstract = {{<p>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.</p>}}, author = {{Lundgaard, Agnete T. and Burdet, Frédéric and Siggaard, Troels and Westergaard, David and Vagiaki, Danai and Cantwell, Lisa and Röder, Timo and Vistisen, Dorte and Sparsø, Thomas and Giordano, Giuseppe N. and Ibberson, Mark and Banasik, Karina and Brunak, Søren}}, issn = {{1553-734X}}, language = {{eng}}, number = {{8 August}}, publisher = {{Public Library of Science (PLoS)}}, series = {{PLoS Computational Biology}}, title = {{BALDR : A Web-based platform for informed comparison and prioritization of biomarker candidates for type 2 diabetes mellitus}}, url = {{http://dx.doi.org/10.1371/journal.pcbi.1011403}}, doi = {{10.1371/journal.pcbi.1011403}}, volume = {{19}}, year = {{2023}}, }