Demo Data from EDBT 2026 / reviewers in the wild / expert
Guillaume Payen
dblp:98/6956
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1
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 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › sequence analysis
DNA sequence analysis |
0.1 | 1 | 2007 | A 3D pattern matching algorithm for DNA sequences · Bioinform. 2007 |
Bioinformatics and computational biology › structural biology
DNA structure |
0.0 | 1 | 2007 | A 3D pattern matching algorithm for DNA sequences · Bioinform. 2007 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2007 | A 3D pattern matching algorithm for DNA sequencesabstractMOTIVATION: Biologists usually work with textual DNA sequences (succession of A, C, G and T). This representation allows biologists to study the syntax and other linguistic properties of DNA sequences. Nevertheless, such a linear coding offers only a local and a one-dimensional vision of the molecule. The 3D structure of DNA is known to be very important in many essential biological mechanisms. By using 3D conformation models, one is able to construct a 3D trajectory of a naked DNA molecule. From the various studies that we performed, it turned out that two very different textual DNA sequences could have similar 3D structures. RESULTS: In this article, we address a new research work on 3D pattern matching for DNA sequences. The aim of this work is to enhance conventional pattern matching analyses with 3D-augmented criteria. We have developed an algorithm, based on 3D trajectories, which compares angles formed by these trajectories and thus quantifies the difference between two 3D DNA sequences. This analysis performs from a global scale to al local one. AVAILABILITY: Available on request from the authors. Joan Hérisson, Guillaume Payen, Rachid Gherbi |
Bioinform. | 2 |