TY - JOUR
T1 - BALDR
T2 - A Web-based platform for informed comparison and prioritization of biomarker candidates for type 2 diabetes mellitus
AU - Lundgaard, Agnete T
AU - Burdet, Frédéric
AU - Siggaard, Troels
AU - Westergaard, David
AU - Vagiaki, Danai
AU - Cantwell, Lisa
AU - Röder, Timo
AU - Vistisen, Dorte
AU - Sparsø, Thomas
AU - Giordano, Giuseppe N
AU - Ibberson, Mark
AU - Banasik, Karina
AU - Brunak, Søren
N1 - Copyright: © 2023 Lundgaard et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2023/8
Y1 - 2023/8
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85168773432&partnerID=8YFLogxK
U2 - 10.1371/journal.pcbi.1011403
DO - 10.1371/journal.pcbi.1011403
M3 - Journal article
C2 - 37590326
SN - 1553-734X
VL - 19
SP - e1011403
JO - PLOS Computational Biology
JF - PLOS Computational Biology
IS - 8
M1 - e1011403
ER -