Demo Data from EDBT 2026 / reviewers in the wild / expert
P. M. Leong
dblp:91/2281
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1995
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author
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 › sequence analysis › sequence visualization
DNA sequence visualization |
0.0 | 1 | 1995 | Random walk and gap plots of DNA sequences · Comput. Appl. Biosci. 1995 |
Bioinformatics and computational biology
sequence analysis |
0.0 | 1 | 1995 | Random walk and gap plots of DNA sequences · Comput. Appl. Biosci. 1995 |
Bioinformatics and computational biology › sequence analysis
genomic sequence analysis |
0.0 | 1 | 1995 | Random walk and gap plots of DNA sequences · Comput. Appl. Biosci. 1995 |
Methods — techniques the papers use, named apart from their topics
random walk · 0.0gap plots · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1995 | Random walk and gap plots of DNA sequencesabstractGenomic sequence analysis is usually performed with the help of specialized software packages written for molecular biologists. The scope of such pre-programmed techniques is quite limited. Because DNA sequences contain a large amount of information, analysis of such sequences without underlying assumptions may provide additional insights. The present article proposes two new graphical representations as examples of such methods. The random walk plot is designed to show the base composition in a compact form, whereas the gap plot visualizes positional correlations. The random walk plot represents the DNA sequence as a curve, a random walk, in a plane. The four possible moves, left/right and up/down, are used to encode the four possible bases. Gap plots provide a tool to exhibit various features in a sequence. They visualize the periodic patterns within a sequence, both with regard to a single type of base or between two types of bases. P. M. Leong, Stephan Morgenthaler |
Comput. Appl. Biosci. | 1 |