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Kris Gevaert

dblp:35/5926 · DBLP profile ↗
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3ranked-venue papers
0as first author
1since 2021 · last 2026
0000-0002-4237-0283ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 3 · 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
2 papers
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
proteomics
1.122026
DiaReport: reproducible workflow for differential expression analysis and interactive reporting in DIA-based proteomics · Bioinform. 2026
DBToolkit: processing protein databases for peptide-centric proteomics · Bioinform. 2005
Bioinformatics and computational biology › gene expression analysis
differential expression analysis
1.012026
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
0.312026
DiaReport: reproducible workflow for differential expression analysis and interactive reporting in DIA-based proteomics · Bioinform. 2026
Bioinformatics and computational biology › proteomics
mass spectrometry data analysis
0.012005
DBToolkit: processing protein databases for peptide-centric proteomics · Bioinform. 2005

Methods — techniques the papers use, named apart from their topics

statistical modeling · 1.0normalization · 1.0sequence database processing · 0.1
YearPublicationVenuePosition
2026 DiaReport: reproducible workflow for differential expression analysis and interactive reporting in DIA-based proteomics
abstract
MOTIVATION: 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.4
2006 Cell_motility: a cross-platform, open source application for the study of cell motion paths
abstract
BACKGROUND: Migration is an important aspect of cellular behaviour and is therefore widely studied in cell biology. Numerous components are known to participate in this process in a highly dynamic manner. In order to obtain a better insight in cell migration, mutants or drugs are used and their motive phenotype is then linked with the disturbing factors. One of the typical approaches to study motion paths of individual cells relies on fitting mean square displacements to a persistent random walk function. Since the numerous calculations involved often rely on diverse commercial software packages, the analysis can be expensive, labour-intensive and error-prone work. Additionally, due to the nature of algorithms employed the calculations involved are not readily reproducible without access to the exact software package(s) used. RESULTS: We here present the cell_motility software, an open source Java application under the GNU-GPL license that provides a clear and concise analysis workbench for large amounts of cell motion data. Apart from performing the necessary calculations, the software also visualizes the original motion paths as well as the results of the calculations to help the user interpret the data. The application features an intuitive graphical user interface as well as full user and developer documentation and both source and binary files can be freely downloaded from the project website at http://genesis.UGent.be/cell_motility . CONCLUSION: In providing a free, open source software solution for the automated processing of cell motion data, we aim to achieve two important goals: labs can greatly simplify their data analysis pipeline as switching between different computational software packages becomes obsolete (thus reducing the chances for human error during data manipulation and transfer) and secondly, to provide scientists in the field with a freely available common platform to perform their analyses, enabling more efficient data quality control through peer reviewing.
Lennart Martens, Geert Monsieur, Christophe Ampe, Kris Gevaert, Joël Vandekerckhove
BMC Bioinform.4
2005 DBToolkit: processing protein databases for peptide-centric proteomics
abstract
UNLABELLED: DBToolkit is a user-friendly, easily extensible tool that allows the processing of protein sequence databases to peptide-centric sequence databases. This processing is primarily aimed at enhancing the useful information content of these databases for use as optimized search spaces for efficient identification of peptide fragmentation spectra obtained by mass spectrometry. In addition, DBToolkit can be used to reliably solve a range of other typical tasks in processing sequence databases. AVAILABILITY: DBToolkit is open source under the GNU GPL license. The source code, full user and developer documentation and cross-platform binaries are freely downloadable from the project website at http://genesis.UGent.be/dbtoolkit/ CONTACT: [email protected]
Lennart Martens, Joël Vandekerckhove, Kris Gevaert
Bioinform.3