Demo Data from EDBT 2026 / reviewers in the wild / expert
Esperanza Fernández
dblp:441/6685
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › gene expression analysis
differential expression analysis |
1.0 | 1 | 2026 | DiaReport: reproducible workflow for differential expression analysis and interactive reporting in DIA-based proteomics · Bioinform. 2026 |
Bioinformatics and computational biology
proteomics |
1.0 | 1 | 2026 | DiaReport: reproducible workflow for differential expression analysis and interactive reporting in DIA-based proteomics · Bioinform. 2026 |
Bioinformatics and computational biology › proteomics › shotgun proteomics
data-independent acquisition |
0.3 | 1 | 2026 | DiaReport: reproducible workflow for differential expression analysis and interactive reporting in DIA-based proteomics · Bioinform. 2026 |
Methods — techniques the papers use, named apart from their topics
statistical modeling · 1.0normalization · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | DiaReport: reproducible workflow for differential expression analysis and interactive reporting in DIA-based proteomicsabstractMOTIVATION: Data-independent acquisition (DIA) has become the preferred data acquisition method for mass spectrometry-based proteomics, yet, reproducible workflows for differential expression (DE) analysis and results reporting remain limited. We present DiaReport, an R package that performs precursor- and protein-level DE analysis from DIA-NN output using MSqRob and QFeatures, while generating high-quality, interactive HTML reports through Quarto. DiaReport integrates precursor data, filtering of missing values, normalization, protein summarization and statistical modeling within a single function, supporting both simple pairwise as well as complex experimental designs. The package provides structured outputs and configuration files to ensure computational reproducibility across different studies. To accommodate diverse research needs, DiaReport includes multiple reporting templates tailored to different proteomic applications. Applying DiaReport to an extracellular vesicle (EV) proteomics dataset demonstrates its ability to efficiently analyze DIA data and provide rapid insights into sample quality and protein level differences. AVAILABILITY: DiaReport is an open-source R package available at https://github.com/Gevaert-Lab/diareport (DOI: 10.5281/zenodo.20120604). The package is platform-independent and distributed under the MIT license. Reports are generated using Quarto and require only standard R dependencies. Detailed documentation, installation guides and usage vignettes are provided within the repository. The interactive HTML reports discussed in this study, including the UPS2 benchmark and EV case study, are archived on Zenodo (10.5281/zenodo.20122506 and 10.5281/zenodo.20123378). Andrea Argentini, Esperanza Fernández, Jarne Pauwels, Kris Gevaert |
Bioinform. | 2 |