Demo Data from VLDB 2026 / reviewers in the wild / expert
José Fernández Navarro
dblp:209/7810
· DBLP profile ↗
3ranked-venue papers
2as first author
0since 2021 · last 2019
0000-0002-4035-5258ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3 · 2 first-author
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
3 papers |
Bioinformatics and computational biology · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › transcriptomics
spatial transcriptomics |
1.0 | 3 | 2019 | ST viewer: a tool for analysis and visualization of spatial transcriptomics datasets · Bioinform. 2019 ST Spot Detector: a web-based application for automatic spot and tissue detection for spatial Transcriptomics image datasets · Bioinform. 2018 ST Pipeline: an automated pipeline for spatial mapping of unique transcripts · Bioinform. 2017 |
Bioinformatics and computational biology › transcriptomics
spatial gene expression |
0.1 | 1 | 2018 | ST Spot Detector: a web-based application for automatic spot and tissue detection for spatial Transcriptomics image datasets · Bioinform. 2018 |
Bioinformatics and computational biology
transcriptomics |
0.1 | 1 | 2018 | ST Spot Detector: a web-based application for automatic spot and tissue detection for spatial Transcriptomics image datasets · Bioinform. 2018 |
Bioinformatics and computational biology › transcriptomics
RNA-seq analysis |
0.1 | 1 | 2017 | ST Pipeline: an automated pipeline for spatial mapping of unique transcripts · Bioinform. 2017 |
Bioinformatics and computational biology › transcriptomics › RNA-seq analysis
RNA-seq data processing |
0.1 | 1 | 2017 | ST Pipeline: an automated pipeline for spatial mapping of unique transcripts · Bioinform. 2017 |
Methods — techniques the papers use, named apart from their topics
interactive visualization · 0.4image processing · 0.3automated pipeline · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | ST viewer: a tool for analysis and visualization of spatial transcriptomics datasetsabstractMOTIVATION: Spatial Transcriptomics (ST) is a technique that combines high-resolution imaging with spatially resolved transcriptome-wide sequencing. This novel type of data opens up many possibilities for analysis and visualization, most of which are either not available with standard tools or too complex for normal users. RESULTS: Here, we present a tool, ST Viewer, which allows real-time interaction, analysis and visualization of Spatial Transcriptomics datasets through a seamless and smooth user interface. AVAILABILITY AND IMPLEMENTATION: The ST Viewer is open source under a MIT license and it is available at https://github.com/SpatialTranscriptomicsResearch/st_viewer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. José Fernández Navarro, Joakim Lundeberg, Patrik L. Ståhl |
Bioinform. | 1 |
| 2018 | ST Spot Detector: a web-based application for automatic spot and tissue detection for spatial Transcriptomics image datasetsabstractMotiviation: Spatial Transcriptomics (ST) is a method which combines high resolution tissue imaging with high troughput transcriptome sequencing data. This data must be aligned with the images for correct visualization, a process that involves several manual steps. Results: Here we present ST Spot Detector, a web tool that automates and facilitates this alignment through a user friendly interface. Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online. Kim Wong, José Fernández Navarro, Ludvig Bergenstråhle, Patrik L. Ståhl, Joakim Lundeberg |
Bioinform. | 2 |
| 2017 | ST Pipeline: an automated pipeline for spatial mapping of unique transcriptsabstractMOTIVATION: In recent years we have witnessed an increase in novel RNA-seq based techniques for transcriptomics analysis. Spatial transcriptomics is a novel RNA-seq based technique that allows spatial mapping of transcripts in tissue sections. The spatial resolution adds an extra level of complexity, which requires the development of new tools and algorithms for efficient and accurate data processing. RESULTS: Here we present a pipeline to automatically and efficiently process RNA-seq data obtained from spatial transcriptomics experiments to generate datasets for downstream analysis. AVAILABILITY AND IMPLEMENTATION: The ST Pipeline is open source under a MIT license and it is available at https://github.com/SpatialTranscriptomicsResearch/st_pipeline. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. José Fernández Navarro, Joel Sjöstrand, Fredrik Salmén, Joakim Lundeberg, Patrik L. Ståhl |
Bioinform. | 1 |