Demo Data from EDBT 2026 / reviewers in the wild / expert
Maria da Gloria Carvalho
dblp:00/7969
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2010
0000-0001-5890-8095ORCID · reported
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 › proteomics › shotgun proteomics
data-independent acquisition |
0.1 | 1 | 2010 | XDIA: improving on the label-free data-independent analysis · Bioinform. 2010 |
Bioinformatics and computational biology
proteomics |
0.1 | 1 | 2010 | XDIA: improving on the label-free data-independent analysis · Bioinform. 2010 |
Bioinformatics and computational biology › proteomics
shotgun proteomics |
0.1 | 1 | 2010 | XDIA: improving on the label-free data-independent analysis · Bioinform. 2010 |
Bioinformatics and computational biology › proteomics
mass spectrometry data analysis |
0.0 | 1 | 2010 | XDIA: improving on the label-free data-independent analysis · Bioinform. 2010 |
Methods — techniques the papers use, named apart from their topics
electron transfer dissociation · 0.1collision-activated dissociation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | XDIA: improving on the label-free data-independent analysisabstractSUMMARY: XDIA is a computational strategy for analyzing multiplexed spectra acquired using electron transfer dissociation and collision-activated dissociation; it significantly increases identified spectra (approximately 250%) and unique peptides (approximately 30%) when compared with the data-dependent ETCaD analysis on middle-down, single-phase shotgun proteomic analysis. Increasing identified spectra and peptides improves quantitation statistics confidence and protein coverage, respectively. AVAILABILITY: The software and data produced in this work are freely available for academic use at http://fields.scripps.edu/XDIA CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Paulo C. Carvalho, Xuemei Han, Daniel Cociorva, Maria da Gloria Carvalho, Valmir C. Barbosa, John R. Yates III |
Bioinform. | 5 |