Demo Data from EDBT 2026 / reviewers in the wild / expert
Julián Herrera Braga
dblp:184/4656
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › genomics
genetic variant analysis |
0.2 | 1 | 2016 | PinSnps: structural and functional analysis of SNPs in the context of protein interaction networks · Bioinform. 2016 |
Bioinformatics and computational biology › protein analysis › protein-protein interaction
protein-protein interaction network analysis |
0.2 | 1 | 2016 | PinSnps: structural and functional analysis of SNPs in the context of protein interaction networks · Bioinform. 2016 |
Bioinformatics and computational biology
protein structure analysis |
0.2 | 1 | 2016 | PinSnps: structural and functional analysis of SNPs in the context of protein interaction networks · Bioinform. 2016 |
Bioinformatics and computational biology › genomics › variant annotation
SNP functional annotation |
0.2 | 1 | 2016 | PinSnps: structural and functional analysis of SNPs in the context of protein interaction networks · Bioinform. 2016 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | PinSnps: structural and functional analysis of SNPs in the context of protein interaction networksabstractUNLABELLED: We present a practical computational pipeline to readily perform data analyses of protein-protein interaction networks by using genetic and functional information mapped onto protein structures. We provide a 3D representation of the available protein structure and its regions (surface, interface, core and disordered) for the selected genetic variants and/or SNPs, and a prediction of the mutants' impact on the protein as measured by a range of methods. We have mapped in total 2587 genetic disorder-related SNPs from OMIM, 587 873 cancer-related variants from COSMIC, and 1 484 045 SNPs from dbSNP. All result data can be downloaded by the user together with an R-script to compute the enrichment of SNPs/variants in selected structural regions. AVAILABILITY AND IMPLEMENTATION: PinSnps is available as open-access service at http://fraternalilab.kcl.ac.uk/PinSnps/ CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Hui-Chun Lu, Julián Herrera Braga, Franca Fraternali |
Bioinform. | 2 |