Demo Data from VLDB 2026 / reviewers in the wild / expert
Marjan Mansouvar
dblp:424/4432
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
—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 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › systems biology
metabolic modeling |
0.8 | 1 | 2024 | Shu: visualization of high-dimensional biological pathways · Bioinform. 2024 |
Bioinformatics and computational biology › systems bioinformatics › pathway analysis
metabolic pathway visualization |
0.8 | 1 | 2024 | Shu: visualization of high-dimensional biological pathways · Bioinform. 2024 |
Bioinformatics and computational biology › omics data analysis
omics data visualization |
0.8 | 1 | 2024 | Shu: visualization of high-dimensional biological pathways · Bioinform. 2024 |
Methods — techniques the papers use, named apart from their topics
grammar of graphics · 0.8Python API · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Shu: visualization of high-dimensional biological pathwaysabstractSUMMARY: Shu is a visualization tool that integrates diverse data types into a metabolic map, with a focus on supporting multiple conditions and visualizing distributions. The goal is to provide a unified platform for handling the growing volume of multi-omics data, leveraging the metabolic maps developed by the metabolic modeling community. In addition, shu offers a streamlined python API, based on the Grammar of Graphics, for easy integration with data pipelines. AVAILABILITY AND IMPLEMENTATION: Freely available at https://github.com/biosustain/shu under MIT/Apache 2.0 license. Binaries are available in the release page of the repository and the web application is deployed at https://biosustain.github.io/shu. Jorge Carrasco Muriel, Nicholas Cowie, Shannara Taylor Parkins, Marjan Mansouvar, Teddy Groves, Lars Keld Nielsen |
Bioinform. | 4 |