Simplifying the generation of insight from protein structures
Nelson Perdigão1,2, Agostinho Rosa1,2, Seán I. O’Donoghue3
Updated: June 2016
This indicates when the Dark Proteome Database (DPD) was last calculated.
PDB structures released since then are not yet available in DPD.
1. University of Lisbon, Portugal
2. Instituto de Sistemas e Robótica, Lisboa, Portugal
3. Garvan Institute of Medical Research, Sydney, Australia
This version covers UniProt KnowledgeBase (UniProtKB/Swiss-Prot) Release 2016_06. It contains annotations for characterisation of dark proteins and dark domains such as: order, disorder, transmembrane, globular and compositional bias from (UniProtKB/Swiss-Prot), PDB (X-Ray and NMR) and predictions from PSSH2 (Aquaria), PP (Predict Protein) and PMP (Protein Model Portal).
Dark Proteome Database: Studies on Disorder
Perdigão, N. et al. High-Throughput, 9.3 (2020): 15.
nih.gov
doi
Dark Proteome Database: Studies on Dark Proteins
Perdigão, N. et al. High-Throughput, 8.2 (2019): 8.
nih.gov
doi
The Dark Proteome Database
Perdigão, N. et al. Biodata Mining, 1 (2017): 10-24.
nih.gov
doi
Unexpected features of the Dark Proteome
Perdigão, N. et al. Proceedings of the National Academy of Sciences, 112.52 (2015): 15898-15903.
nih.gov
doi
DPD uses resources from the following projects
© Copyright 2015-2020 Nelson Perdigão and ISR-IST-ULisboa, All Rights Reserved.
