Demo Data from EDBT 2026 / reviewers in the wild / expert
Carmen Catala
dblp:209/7711
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none
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 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › gene expression analysis
gene expression visualization |
0.3 | 1 | 2017 | The Tomato Expression Atlas · Bioinform. 2017 |
Bioinformatics and computational biology
transcriptomics |
0.1 | 1 | 2017 | The Tomato Expression Atlas · Bioinform. 2017 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | The Tomato Expression AtlasabstractSUMMARY: With the development of new high-throughput DNA sequencing technologies and decreasing costs, large gene expression datasets are being generated at an accelerating rate, but can be complex to visualize. New, more interactive and intuitive tools are needed to visualize the spatiotemporal context of expression data and help elucidate gene function. Using tomato fruit as a model, we have developed the Tomato Expression Atlas to facilitate effective data analysis, allowing the simultaneous visualization of groups of genes at a cell/tissue level of resolution within an organ, enhancing hypothesis development and testing in addition to candidate gene identification. This atlas can be adapted to different types of expression data from diverse multicellular species. AVAILABILITY AND IMPLEMENTATION: The Tomato Expression Atlas is available at http://tea.solgenomics.net/ . Source code is available at https://github.com/solgenomics/Tea . CONTACT: [email protected] or [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Noé Fernández-Pozo, Stephen I. Snyder, Philippe Nicolas, Yoshihito Shinozaki, Zhangjun Fei, Carmen Catala, James J. Giovannoni, Jocelyn K. C. Rose, Lukas A. Mueller |
Bioinform. | 7 |