Demo Data from SIGIR 2026 / reviewers in the wild / expert
Paul Delmar
dblp:41/2860
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2005
—ORCID · unresolved
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 › gene expression analysis
differential expression analysis |
0.1 | 1 | 2005 | VarMixt: efficient variance modelling for the differential analysis of replicated gene expression data · Bioinform. 2005 |
Bioinformatics and computational biology
gene expression analysis |
0.1 | 1 | 2005 | VarMixt: efficient variance modelling for the differential analysis of replicated gene expression data · Bioinform. 2005 |
Bioinformatics and computational biology › gene expression analysis
microarray data analysis |
0.1 | 1 | 2005 | VarMixt: efficient variance modelling for the differential analysis of replicated gene expression data · Bioinform. 2005 |
Methods — techniques the papers use, named apart from their topics
mixture model · 0.1false discovery rate control · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2005 | VarMixt: efficient variance modelling for the differential analysis of replicated gene expression dataabstractMOTIVATION: Identifying differentially regulated genes in experiments comparing two experimental conditions is often a key step in the microarray data analysis process. Many different approaches and methodological developments have been put forward, yet the question remains open. RESULTS: Varmixt is a powerful and efficient novel methodology for this task. It is based on a flexible and realistic variance modelling strategy. It compares favourably with other popular techniques (standard t-test, SAM and Cyber-T). The relevance of the approach is demonstrated with real-world and simulated datasets. The analysis strategy was successfully applied to both a 'two-colour' cDNA microarray and an Affymetrix Genechip. Strong control of false positive and false negative rates is proven in large simulation studies. AVAILABILITY: The R package is freely available at http://www.inapg.inra.fr/ens_rech/mathinfo/recherche/mathematique/outil.html CONTACT: [email protected] SUPPLEMENTARY INFORMATION: http://www.inapg.inra.fr/ens_rech/mathinfo/recherche/mathematique/outil.html. Paul Delmar, Stéphane Robin, Jean-Jacques Daudin |
Bioinform. | 1 |