Demo Data from VLDB 2026 / reviewers in the wild / expert
Po-Wen Wang
dblp:309/4395
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 since 2021Applied, 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. | 2 |
| 2021 | DAPA: A Dataflow-Aware Analytical Placement Algorithm for Modern Mixed-Size Circuit DesignsabstractThis article presents an analytical-based placement algorithm to handle dataflow constraint for mixed-size circuits. To quickly obtain a better placement at an early stage, engineers often reference dataflow of a design to determine the relative locations of cells and macros. To achieve this target, this paper presents two methods to make a placement follow this constraint. First, we give larger weights to those nets which connect to datapath-oriented objects in the beginning, and then gradually shrink the values by the modified Gompertz curve according to the status of placement utilization in order to shorten their distances without interfering with object distribution. Second, we define desirable placement regions for each datapath-oriented object and propose a novel sigmoid function to give additional penalties to these objects in the analytical placement formulation if they are not in the regions. The experiment demonstrates that our methodology can obtain better results than the other approach which does not consider dataflow constraint. Not only wirelength but also routability will be improved in the resulting placement. Furthermore, our placer outperforms the RTL-aware dataflow-driven macro placer. Jai-Ming Lin, Wei-Fan Huang, Yao-Chieh Chen, Po-Wen Wang |
ICCAD | 5 |