VLDB 2026 Research / reviewers in the wild / expert
Jinsen Li
dblp:348/5379
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2025
0000-0002-1015-5263ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › synthetic biology
DNA sequence design |
0.9 | 1 | 2025 | DNAdesign: feature-aware in silico design of synthetic DNA through mutation · Bioinform. 2025 |
Bioinformatics and computational biology
synthetic biology |
0.9 | 1 | 2025 | DNAdesign: feature-aware in silico design of synthetic DNA through mutation · Bioinform. 2025 |
Bioinformatics and computational biology
genomics |
0.3 | 1 | 2025 | DNAdesign: feature-aware in silico design of synthetic DNA through mutation · Bioinform. 2025 |
Methods — techniques the papers use, named apart from their topics
deep learning · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | DNAdesign: feature-aware in silico design of synthetic DNA through mutationabstractMOTIVATION: DNA sequence and shape readout represent different modes of protein-DNA recognition. Current tools lack the functionality to simultaneously consider alterations in different readout modes caused by sequence mutations. DNAdesign is a web-based tool to compare and design mutations based on both DNA sequence and shape characteristics. Users input a wild-type sequence, select sites to introduce mutations and choose a set of DNA shape parameters for mutation design. RESULTS: DNAdesign utilizes Deep DNAshape to provide ultra-fast predictions of DNA shape based on extended k-mers and offers multiple encoding methods for nucleotide sequences, including the physicochemical encoding of DNA through their functional groups in the major and minor groove. DNAdesign provides all mutation candidates along the sequence and shape dimensions, with interactive visualization comparing each candidate with the wild-type DNA molecule. DNAdesign provides an approach to studying gene regulation and applications in synthetic biology, such as the design of synthetic enhancers and transcription factor binding sites. AVAILABILITY AND IMPLEMENTATION: The DNAdesign webserver and documentation are freely accessible at https://dnadesign.usc.edu. Yingfei Wang, Jinsen Li, Tsu-Pei Chiu, Nicolas Gompel, Remo Rohs |
Bioinform. | 2 |
| 2023 | FedUTN: federated self-supervised learning with updating target network
Simou Li, Yuxing Mao, Jinsen Li, Xueshuo Chen, Xianping Zhao |
Appl. Intell. | 5 |