Demo Data from EDBT 2026 / reviewers in the wild / expert
Bernd Wollscheid
dblp:143/4990
· DBLP profile ↗
2ranked-venue papers
0as first author
1since 2021 · last 2024
0000-0002-3923-1610ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2 · 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 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › systems bioinformatics
pathway analysis |
0.8 | 1 | 2024 | Probabilistic pathway-based multimodal factor analysis · Bioinform. 2024 |
Bioinformatics and computational biology › protein analysis
protein visualization |
0.2 | 1 | 2014 | Protter: interactive protein feature visualization and integration with experimental proteomic data · Bioinform. 2014 |
Bioinformatics and computational biology
proteomics |
0.2 | 1 | 2014 | Protter: interactive protein feature visualization and integration with experimental proteomic data · Bioinform. 2014 |
Methods — techniques the papers use, named apart from their topics
probabilistic factor analysis · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Probabilistic pathway-based multimodal factor analysis
Alexander Immer, Stefan Stark, Francis Jacob, Ximena Bonilla, Tinu Thomas, André Kahles, Sandra Götze, Emanuela S. Milani, Bernd Wollscheid, Gunnar Rätsch, Kjong-Van Lehmann |
Bioinform. | 9 |
| 2014 | Protter: interactive protein feature visualization and integration with experimental proteomic dataabstractSUMMARY: The ability to integrate and visualize experimental proteomic evidence in the context of rich protein feature annotations represents an unmet need of the proteomics community. Here we present Protter, a web-based tool that supports interactive protein data analysis and hypothesis generation by visualizing both annotated sequence features and experimental proteomic data in the context of protein topology. Protter supports numerous proteomic file formats and automatically integrates a variety of reference protein annotation sources, which can be readily extended via modular plug-ins. A built-in export function produces publication-quality customized protein illustrations, also for large datasets. Visualizations of surfaceome datasets show the specific utility of Protter for the integrated visual analysis of membrane proteins and peptide selection for targeted proteomics. AVAILABILITY AND IMPLEMENTATION: The Protter web application is available at http://wlab.ethz.ch/protter. Source code and installation instructions are available at http://ulo.github.io/Protter/. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Ulrich Omasits, Christian H. Ahrens, Sebastian Müller 0004, Bernd Wollscheid |
Bioinform. | 4 |