Demo Data from VLDB 2026 / reviewers in the wild / expert
Sudeepa Bhattacharyya
dblp:17/6331
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2018
—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 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › computational microbiology › microbiome analysis
diversity analysis |
0.3 | 1 | 2018 | Dynamic assessment of microbial ecology (DAME): a web app for interactive analysis and visualization of microbial sequencing data · Bioinform. 2018 |
Bioinformatics and computational biology › microbiology
microbial ecology |
0.3 | 1 | 2018 | Dynamic assessment of microbial ecology (DAME): a web app for interactive analysis and visualization of microbial sequencing data · Bioinform. 2018 |
Bioinformatics and computational biology › computational microbiology
microbiome analysis |
0.3 | 1 | 2018 | Dynamic assessment of microbial ecology (DAME): a web app for interactive analysis and visualization of microbial sequencing data · Bioinform. 2018 |
Methods — techniques the papers use, named apart from their topics
shiny · 0.3differential abundance analysis · 0.3d3.js · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Dynamic assessment of microbial ecology (DAME): a web app for interactive analysis and visualization of microbial sequencing dataabstractSummary: Dynamic assessment of microbial ecology (DAME) is a Shiny-based web application for interactive analysis and visualization of microbial sequencing data. DAME provides researchers not familiar with R programming the ability to access the most current R functions utilized for ecology and gene sequencing data analyses. Currently, DAME supports group comparisons of several ecological estimates of α-diversity and β-diversity, along with differential abundance analysis of individual taxa. Using the Shiny framework, the user has complete control of all aspects of the data analysis, including sample/experimental group selection and filtering, estimate selection, statistical methods and visualization parameters. Furthermore, graphical and tabular outputs are supported by R packages using D3.js and are fully interactive. Availability and implementation: DAME was implemented in R but can be modified by Hypertext Markup Language (HTML), Cascading Style Sheets (CSS), and JavaScript. It is freely available on the web at https://acnc-shinyapps.shinyapps.io/DAME/. Local installation and source code are available through Github (https://github.com/bdpiccolo/ACNC-DAME). Any system with R can launch DAME locally provided the shiny package is installed. Contact: [email protected]. Brian D. Piccolo, Umesh D. Wankhade, Sree V. Chintapalli, Sudeepa Bhattacharyya, Luo Chunqiao, Kartik Shankar |
Bioinform. | 4 |