Demo Data from VLDB 2026 / reviewers in the wild / expert
Chunlong Guo
dblp:132/8268
· DBLP profile ↗
3ranked-venue papers
1as first author
1since 2021 · last 2021
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1Computer networks · 1 · 1 first-authorSoftware engineering, systems software and programming languages · 1Applied, 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 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › structural bioinformatics › protein structure representation
protein structure visualization |
0.5 | 1 | 2021 | VRmol: an integrative web-based virtual reality system to explore macromolecular structure · Bioinform. 2021 |
Bioinformatics and computational biology › molecular informatics › molecular modeling
molecular docking |
0.1 | 1 | 2021 | VRmol: an integrative web-based virtual reality system to explore macromolecular structure · Bioinform. 2021 |
Bioinformatics and computational biology
structural bioinformatics |
0.1 | 1 | 2021 | VRmol: an integrative web-based virtual reality system to explore macromolecular structure · Bioinform. 2021 |
Methods — techniques the papers use, named apart from their topics
cloud-based drug docking · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | VRmol: an integrative web-based virtual reality system to explore macromolecular structureabstractSUMMARY: Structural visualization and analysis are fundamental to explore macromolecular functions. Here, we present a novel integrative web-based virtual reality (VR) system-VRmol, to visualize and study molecular structures in an immersive virtual environment. Importantly, it is integrated with multiple online databases and is able to couple structure studies with associated genomic variations and drug information in a visual interface by cloud-based drug docking. VRmol thus can serve as an integrative platform to aid structure-based translational research and drug design. AVAILABILITY AND IMPLEMENTATION: VRmol is freely available (https://VRmol.net), with detailed manual and tutorial (https://VRmol.net/docs). The code of VRmol is available as open source under the MIT license at http://github.com/kuixu/VRmol. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Kui Xu 0004, Jingle Xu, Chunlong Guo, Qiangfeng Cliff Zhang |
Bioinform. | 4 |
| 2001 | Design methodology for PicoRadio networksabstractOne of the most compelling challenges of the next decade is the "last-meter" problem, extending the expanding data network into end-user data-collection and monitoring devices. PicoRadio supports the assembly of an ad hoc wireless network of self-contained mesoscale, low-cost, low-energy sensor and monitor nodes. While technology advances have made it conceivable to deploy wireless networks of heterogeneous nodes, the design of a low-power, low-cost, adaptive node in a reduced time to market is still a challenge. We present a design methodology for PicoRadio Networks, from system conception and optimization to silicon platform implementation. For each phase of the design, we demonstrate the applicability of our methodology through promising experimental results. Julio Leao da Silva Jr., J. Shamberger, M. Josie Ammer, Chunlong Guo, Suet-Fei Li, Rahul C. Shah, Tim Tuan, Michael Sheets, Jan M. Rabaey, Borivoje Nikolic, Alberto L. Sangiovanni-Vincentelli, Paul K. Wright |
DATE | 4 |
| 2001 | Low power distributed MAC for ad hoc sensor radio networksabstractTargeted at multi-hop wireless sensor networks, a set of low power MAC design principles have been proposed, and a novel ultra-low power MAC is designed to be distributed in nature to support scalability, survivability and adaptability requirements. Simple CSMA and spread spectrum techniques are combined to trade off bandwidth and power efficiency. A distributed algorithm is used to do dynamic channel assignment. A novel wake-up radio scheme is incorporated to take advantage of new radio technologies. The notion of mobility awareness is introduced into an adaptive protocol to reduce network maintenance overhead. The resulting protocol shows much higher power efficiency for typical sensor network applications. Chunlong Guo, Lizhi C. Zhong, Jan M. Rabaey |
GLOBECOM | 1 |