Demo Data from EDBT 2026 / reviewers in the wild / expert
Sen Wang 0012
dblp:69/6403-12
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0008-7180-7473ORCID · verified
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 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › single-cell analysis › single-cell data preprocessing
demultiplexing |
0.8 | 1 | 2024 | mgikit: demultiplexing toolkit for MGI fastq files · Bioinform. 2024 |
Bioinformatics and computational biology
genomics |
0.8 | 1 | 2024 | mgikit: demultiplexing toolkit for MGI fastq files · Bioinform. 2024 |
Bioinformatics and computational biology › sequence analysis
sequencing data processing |
0.8 | 1 | 2024 | mgikit: demultiplexing toolkit for MGI fastq files · Bioinform. 2024 |
Bioinformatics and computational biology › sequence analysis › sequencing data processing
sequencing quality control |
0.2 | 1 | 2024 | mgikit: demultiplexing toolkit for MGI fastq files · Bioinform. 2024 |
Methods — techniques the papers use, named apart from their topics
quality report generation · 0.8demultiplexing · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | mgikit: demultiplexing toolkit for MGI fastq filesabstractSUMMARY: MGI sequencing is reported to be an inexpensive solution to obtain genomics information. There is a growing need for software and tools to analyse MGI's outputs efficiently. mgikit is a tool collection to demultiplex MGI fastq data, reformat it effectively and produce visual quality reports. mgikit overcomes several limitations of the standard MGI demultiplexer. It is highly customizable to suit different kinds of datasets and is designed to achieve high performance and optimal memory utilization. AVAILABILITY AND IMPLEMENTATION: The tool and its documentation are available at: https://sagc-bioinformatics.github.io/mgikit/. Ziad Al Bkhetan, Sen Wang 0012 |
Bioinform. | 2 |