Demo Data from VLDB 2026 / reviewers in the wild / expert
Vasiliki Tzelepi
dblp:399/4429
· 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 › epigenomics
differential methylation analysis |
1.0 | 1 | 2026 | CpGene: a web application for epigenetic signature identification from DNA methylation arrays · Bioinform. 2026 |
Bioinformatics and computational biology › epigenomics › DNA methylation
DNA methylation analysis |
1.0 | 1 | 2026 | CpGene: a web application for epigenetic signature identification from DNA methylation arrays · Bioinform. 2026 |
Bioinformatics and computational biology › epigenomics
epigenetic biomarker discovery |
1.0 | 1 | 2026 | CpGene: a web application for epigenetic signature identification from DNA methylation arrays · Bioinform. 2026 |
Methods — techniques the papers use, named apart from their topics
machine learning-based feature selection · 1.0gene enrichment analysis · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | CpGene: a web application for epigenetic signature identification from DNA methylation arraysabstractMOTIVATION: DNA methylation (DNAme) is the best studied epigenetic mechanism that plays pivotal role in tissue differentiation and epigenetic disruption has been correlated to diverse disease types (e.g. cancer, metabolic disorders). While various DNAme array platforms have been discovered, data analysis remains a challenging task which often requires in-depth bioinformatic expertise. Here, we developed a user-friendly web-based application for data analysis and visualization that accommodates users ranging from early-career basic/translational researchers to experienced bioinformaticians. RESULTS: CpGene is a web application for analyzing DNA methylation array data. It supports Illumina 450K, EPIC, and EPICv2 methylation array platforms and processes .idat files with integrated preprocessing, normalization, and quality control. Biomarker discovery is available through either classic differential methylation point analysis or machine learning-based feature selection as well as gene enrichment analysis. Results are summarized with clear visualizations, to aid interpretation. By combining these functions in a unified interface, CpGene streamlines methylation analysis and helps identify CpG sites and genes with biological and clinical relevance. AVAILABILITY AND IMPLEMENTATION: CpGene is openly accessible as a web service through http://cpgene.duckdns.org:8001/ and it's source code is available on https://github.com/kostaslazaros/cpgenene. Konstantinos Lazaros, Souzana Logotheti, Christopher Logothetis, Vasiliki Tzelepi, Panayiotis M. Vlamos, Aristidis G. Vrahatis |
Bioinform. | 4 |