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DAPPLE specifications

Information


Unique identifier OMICS_05948
Name DAPPLE
Interface Web user interface
Restrictions to use None
Computer skills Basic
Version 2.0
Stability Stable
Maintained Yes

Maintainer


Additional information


http://saphire.usask.ca/saphire/dapple2/about.html Previous version of the tool available at http://saphire.usask.ca/saphire/dapple/index.html

Publications for DAPPLE

DAPPLE citations

 (8)
library_books

Heterogeneous contribution of microdeletions in the development of common generalised and focal epilepsies

2017
J Med Genet
PMCID: 5574393
PMID: 28756411
DOI: 10.1136/jmedgenet-2016-104495

[…] s did not show significant differences after correction for multiple testing (online ). Finally, to evaluate the entire pool of genes exclusively deleted in patients in a network context, we used the DAPPLE to assess protein–protein interactions networks with a higher number of interconnections than expected. As DAPPLE uses a non-brain-specific network, we filtered the input genes based on brain e […]

library_books

Molecular characterization of breast cancer cell lines through multiple omic approaches

2017
PMCID: 5460504
PMID: 28583138
DOI: 10.1186/s13058-017-0855-0

[…] phosphorylation events. Phosphorylation events represented on the array were selected from databases of experimentally defined phosphorylation events and from those predicted by the software program DAPPLE2 []. Additional peptide substrates were included to represent proteins, and their associated phosphorylation events, that were shown in the literature to be differentially regulated in a number […]

library_books

Comparative analysis of protein interactome networks prioritizes candidate genes with cancer signatures

2016
Oncotarget
PMCID: 5346681
PMID: 27791983
DOI: 10.18632/oncotarget.12879

[…] ion. In order to evaluate the power of different interactome datasets, we used network centrality to rank genes in this study. Although other well-established disease gene prioritization methods like DAPPLE [], Metaranker [], PRINCE [] and some random walk methods [, ] have been demonstrated to be valuable methods for predicting disease related genes, it is complex to compare these different metho […]

library_books

Computational Analysis of the Predicted Evolutionary Conservation of Human Phosphorylation Sites

2016
PLoS One
PMCID: 4821552
PMID: 27046079
DOI: 10.1371/journal.pone.0152809

[…] ntally-determined phosphorylation sites in many species is limited, it is difficult to accurately calculate the fi’s using experimental data. Thus, we calculated the fi’s by employing the online tool DAPPLE [] to predict phosphorylation sites in the various species using experimentally-determined phosphorylation sites from human (the species with the greatest number of known phosphorylation sites) […]

library_books

High density genotyping of immune related loci identifies new SLE risk variants in individuals with Asian ancestry

2016
Nat Genet
PMCID: 4767573
PMID: 26808113
DOI: 10.1038/ng.3496

[…] In order to investigate how our novel loci interact with other genes, we used curated network interactions using the Disease Association Protein-Protein Link Evaluator database (DAPPLE V2.0). We used a seed of all our novel loci (both left and right flanking genes were also used for intergenic signals) and 20,000 within-degree-node permutations. We chose to simplify our netwo […]

library_books

A Comparison of the Chicken and Turkey Proteomes and Phosphoproteomes in the Development of Poultry Specific Immuno Metabolism Kinome Peptide Arrays

2014
PMCID: 4668846
PMID: 26664921
DOI: 10.3389/fvets.2014.00022

[…] ruit fly have relatively well-annotated proteomes and phosphoproteomes, other species such as chicken, turkey, sheep, and honey-bee are less well-studied. Within the custom-designed software pipeline DAPPLE (), one uses databases of experimentally determined phosphorylation sites from other organisms to query the complete proteome of the species of interest for orthologous phosphorylation sites. U […]


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DAPPLE institution(s)
Vaccine and Infectious Disease Organization, University of Saskatchewan, Saskatoon, SK, Canada; Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada; Department of Biochemistry, University of Saskatchewan, Saskatoon, SK, Canada

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