EDBT 2026 Demo / reviewers in the wild / expert
Sam T. Benedict
dblp:428/3910
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
—ORCID · none
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 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › molecular informatics › cheminformatics
chemical genomic screen analysis |
1.0 | 1 | 2026 | ChemGenXplore: an interactive tool for exploring and analysing chemical genomic data · Bioinform. 2026 |
Bioinformatics and computational biology › molecular informatics › cheminformatics
chemogenomics |
1.0 | 1 | 2026 | ChemGenXplore: an interactive tool for exploring and analysing chemical genomic data · Bioinform. 2026 |
Bioinformatics and computational biology › functional genomics
functional enrichment analysis |
1.0 | 1 | 2026 | ChemGenXplore: an interactive tool for exploring and analysing chemical genomic data · Bioinform. 2026 |
Methods — techniques the papers use, named apart from their topics
shiny web application · 1.0heatmap visualization · 1.0GO and KEGG enrichment · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | ChemGenXplore: an interactive tool for exploring and analysing chemical genomic dataabstractMOTIVATION: Chemical genomics is a powerful high-throughput approach to systematically link phenotypes to genotypes. However, the vast datasets generated remain challenging to explore due to the lack of integrated, interactive tools for visualization and analysis. Existing workflows often require multiple independent software tools, limiting data accessibility and collaboration. Therefore, we created a user-friendly platform that enables efficient exploration and sharing of chemical genomics data. RESULTS: We developed ChemGenXplore, a web-based Shiny application designed to streamline the visualization and analysis of chemical genomic screens. It offers two primary functionalities: one for exploring pre-implemented datasets and another for analysing user-uploaded datasets. ChemGenXplore enables users to visualize phenotypic profiles, assess gene-gene and condition-condition correlations, perform GO and KEGG enrichment analysis, and generate customizable, interactive heatmaps. To further support collaborative research, ChemGenXplore also facilitates the comparative analysis of chemical genomic and other omics datasets. By consolidating these features into a single interactive and accessible tool, ChemGenXplore facilitates data sharing, enhances reproducibility, and promotes collaboration within the research community. AVAILABILITY AND IMPLEMENTATION: ChemGenXplore is freely accessible as a web application at https://chemgenxplore.kaust.edu.sa/. Source code and documentation, including instructions for local installation, are provided on GitHub (https://github.com/Hudaahmadd/ChemGenXplore). A Docker image is also available on DockerHub (https://hub.docker.com/r/hudaahmad/chemgenxplore) to ensure reproducibility and simplify installation. Huda Ahmad, Hannah M. Doherty, Sam T. Benedict, James R. J. Haycocks, Ge Zhou, Patrick J. Moynihan, Danesh Moradigaravand, Manuel Banzhaf |
Bioinform. | 3 |