Demo Data from EDBT 2026 / reviewers in the wild / expert
Tzu-Wen Huang
dblp:330/4935
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—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 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › metagenomics › amplicon sequencing
amplicon sequencing analysis |
0.6 | 1 | 2022 | MOCHI: a comprehensive cross-platform tool for amplicon-based microbiota analysis · Bioinform. 2022 |
Methods — techniques the papers use, named apart from their topics
taxonomic assignment · 0.6GUI tool · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | MOCHI: a comprehensive cross-platform tool for amplicon-based microbiota analysisabstractMOTIVATION: Microbiota analyses have important implications for health and science. These analyses make use of 16S/18S rRNA gene sequencing to identify taxa and predict species diversity. However, most available tools for analyzing microbiota data require adept programming skills and in-depth statistical knowledge for proper implementation. While long-read amplicon sequencing can lead to more accurate taxa predictions and is quickly becoming more common, practitioners have no easily accessible tools with which to perform their analyses. RESULTS: We present MOCHI, a GUI tool for microbiota amplicon sequencing analysis. MOCHI preprocesses sequences, assigns taxonomy, identifies different abundant species and predicts species diversity and function. It takes either taxonomic count table or FASTQ of partial 16S/18S rRNA or full-length 16S rRNA gene as input. It performs analyses in real time and visualizes data in both tabular and graphical formats. AVAILABILITY AND IMPLEMENTATION: MOCHI can be installed to run locally or accessed as a web tool at https://mochi.life.nctu.edu.tw. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Jun-Jie Zheng, Po-Wen Wang, Tzu-Wen Huang, Yao-Jong Yang, Hua-Sheng Chiu, Pavel Sumazin, Ting-Wen Chen |
Bioinform. | 3 |