Demo Data from SIGIR 2026 / reviewers in the wild / expert
Pedro A. Bernaola-Galván
dblp:06/2348
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 1999
0000-0002-2895-3116ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2Applied, 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 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
DNA sequence analysis |
0.0 | 1 | 1999 | SEGMENT: identifying compositional domains in DNA sequences · Bioinform. 1999 |
Bioinformatics and computational biology › sequence analysis › sequence annotation
sequence segmentation |
0.0 | 1 | 1999 | SEGMENT: identifying compositional domains in DNA sequences · Bioinform. 1999 |
Bioinformatics and computational biology › sequence analysis
sequence complexity analysis |
0.0 | 1 | 1999 | SEGMENT: identifying compositional domains in DNA sequences · Bioinform. 1999 |
Methods — techniques the papers use, named apart from their topics
local optimization · 0.0heuristic segmentation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1999 | SEGMENT: identifying compositional domains in DNA sequencesabstractMOTIVATION: DNA sequences are formed by patches or domains of different nucleotide composition. In a few simple sequences, domains can simply be identified by eye; however, most DNA sequences show a complex compositional heterogeneity (fractal structure), which cannot be properly detected by current methods. Recently, a computationally efficient segmentation method to analyse such nonstationary sequence structures, based on the Jensen-Shannon entropic divergence, has been described. Specific algorithms implementing this method are now needed. RESULTS: Here we describe a heuristic segmentation algorithm for DNA sequences, which was implemented on a Windows program (SEGMENT). The program divides a DNA sequence into compositionally homogeneous domains by iterating a local optimization procedure at a given statistical significance. Once a sequence is partitioned into domains, a global measure of sequence compositional complexity (SCC), accounting for both the sizes and compositional biases of all the domains in the sequence, is derived. SEGMENT computes SCC as a function of the significance level, which provides a multiscale view of sequence complexity. José L. Oliver, Ramón Román-Roldán, Javier Pérez, Pedro A. Bernaola-Galván |
Bioinform. | 4 |
| 1996 | Application of information theory to DNA sequence analysis: A review
Ramón Román-Roldán, Pedro A. Bernaola-Galván, José L. Oliver |
Pattern Recognit. | 2 |
| 1994 | Entropic feature for sequence pattern through iterated function systems
Ramón Román-Roldán, Pedro A. Bernaola-Galván, José L. Oliver |
Pattern Recognit. Lett. | 2 |