Demo Data from EDBT 2026 / reviewers in the wild / expert
Lizhen Jiang
dblp:379/9725
· 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 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
cancer genomics |
1.0 | 1 | 2026 | CMAtlas: a comprehensive DNA methylation atlas for exploring epigenetic alterations in 34 human cancer types · Bioinform. 2026 |
Bioinformatics and computational biology › epigenomics
epigenetic biomarker discovery |
0.3 | 1 | 2026 | CMAtlas: a comprehensive DNA methylation atlas for exploring epigenetic alterations in 34 human cancer types · Bioinform. 2026 |
Bioinformatics and computational biology
multi-omics data integration |
0.3 | 1 | 2026 | CMAtlas: a comprehensive DNA methylation atlas for exploring epigenetic alterations in 34 human cancer types · Bioinform. 2026 |
Methods — techniques the papers use, named apart from their topics
technology-tailored pipelines · 1.0survival association analysis · 1.0multi-omics annotation · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | CMAtlas: a comprehensive DNA methylation atlas for exploring epigenetic alterations in 34 human cancer typesabstractMOTIVATION: Aberrant DNA methylation is a fundamental epigenetic hallmark of cancer. However, existing resources often lack technological diversity and comprehensive cancer coverage. Furthermore, most platforms fail to achieve deep multi-omics integration and tend to ignore cancer-type-specific methylation features, limiting their utility in precision oncology and drug discovery. RESULTS: We developed Cancer Methylation Atlas (CMAtlas), a comprehensive platform integrating 13 753 samples across 34 cancer types. By applying technology-tailored pipelines to data from various profiling technologies, we identified 830 725 tumor-specific differentially methylated elements (DMEs) and 1 480 098 differentially methylated regions (DMRs), alongside 1 154 256 cancer-type-specific DMEs and 329 154 DMRs. The platform demonstrates high cross-platform consistency and strong concordance between tumor tissues and cell lines, ensuring the robustness of our findings. All DMEs and DMRs are annotated with multi-omics data (RNA expression, somatic mutations, and chromatin accessibility) and clinical relevance (survival associations and cell-free DNA profiling). We further demonstrate the utility of CMAtlas by identifying prognostic aberrant methylation in colorectal cancer driver genes. AVAILABILITY AND IMPLEMENTATION: CMAtlas is freely accessible at {{https://cmatlas.renlab.cn/}}. The platform offers an intuitive web interface supporting gene-centric and cancer-centric queries, alongside customizable analysis modules designed to facilitate user-specific research needs. Mengni Liu, Lizhen Jiang, Luowanyue Zhang, Tianjian Chen, Xingzhe Wang, Xianping Shi, Jian Ren 0002, Yueyuan Zheng |
Bioinform. | 2 |