Demo Data from EDBT 2026 / reviewers in the wild / expert
Karena Zhang
dblp:197/8340
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1
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
gene expression analysis |
0.3 | 1 | 2017 | GE-mini: a mobile APP for large-scale gene expression visualization · Bioinform. 2017 |
Bioinformatics and computational biology › gene expression analysis
gene expression visualization |
0.3 | 1 | 2017 | GE-mini: a mobile APP for large-scale gene expression visualization · Bioinform. 2017 |
Bioinformatics and computational biology
cancer genomics |
0.1 | 1 | 2017 | GE-mini: a mobile APP for large-scale gene expression visualization · Bioinform. 2017 |
Methods — techniques the papers use, named apart from their topics
mobile application · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | GE-mini: a mobile APP for large-scale gene expression visualizationabstractSummary: The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) projects produced large-scale RNA sequencing data, which provides an opportunity for performing integrated expression analysis for all genes across tens of thousands of tumor and normal tissue specimens. Rapid access to and easy visualization of such valuable data could facilitate research in a wide biological area. Here, we present the GE-mini APP for smart phones, a mobile visualization tool for integrated gene expression data based on both TCGA and GTEx. This gene-centric expression viewer provides a convenient method for displaying expression profiles of all available tumor and tissue types, while allowing drilling down to detailed views for specific tissue types. Availability and Implementation: Both the iOS and Android APPs are freely available to all non-commercial users in App Store and Google Play. The QR codes of App store and Google play are also provided for scanning and download. The GE-mini web server is also available at http://gemini.cancer-pku.cn/ . Contacts: [email protected] or [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online. Zefang Tang, Chenwei Li, Karena Zhang, Xueda Hu |
Bioinform. | 3 |