Demo Data from SIGIR 2026 / reviewers in the wild / expert
Christoph Harmel
dblp:321/4418
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 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 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › bioimage informatics
bioimage analysis |
0.6 | 1 | 2022 | VisuStatR: visualizing motility and morphology statistics on images in R · Bioinform. 2022 |
Bioinformatics and computational biology › bioimage informatics
live cell imaging analysis |
0.6 | 1 | 2022 | VisuStatR: visualizing motility and morphology statistics on images in R · Bioinform. 2022 |
Methods — techniques the papers use, named apart from their topics
statistical visualization · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | VisuStatR: visualizing motility and morphology statistics on images in RabstractMOTIVATION: Live-cell microscopy has become an essential tool for analyzing dynamic processes in various biological applications. Thereby, high-throughput and automated tracking analyses allow the simultaneous evaluation of large numbers of objects. However, to critically assess the influence of individual objects on calculated summary statistics, and to detect heterogeneous dynamics or possible artifacts, such as misclassified or -tracked objects, a direct mapping of gained statistical information onto the actual image data would be necessary. RESULTS: We present VisuStatR as a platform independent software package that allows the direct visualization of time-resolved summary statistics of morphological characteristics or motility dynamics onto raw images. The software contains several display modes to compare user-defined summary statistics and the underlying image data in various levels of detail. AVAILABILITY AND IMPLEMENTATION: VisuStatR is a free and open-source R-package, containing a user-friendly graphical-user interface and is available via GitHub at https://github.com/grrchrr/VisuStatR/ under the MIT+ license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Christoph Harmel, Samy Sid Ahmed, Robin Koch, Jana Tünnermann, Tania Distler, Andrea Imle, Luca Giorgetti, Emanuel Bahn, Oliver T. Fackler, Frederik Graw |
Bioinform. | 1 |