Demo Data from EDBT 2026 / reviewers in the wild / expert
Pierre Alexis Geoffroy
dblp:233/4971
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
0000-0001-9121-209XORCID · reported
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 · 67% Computational science and engineering · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational science and engineering
compositional data analysis |
0.4 | 1 | 2019 | Determination of sets of covariating gene expression using graph analysis on pairwise expression ratios · Bioinform. 2019 |
Bioinformatics and computational biology › gene expression analysis
gene co-expression analysis |
0.4 | 1 | 2019 | Determination of sets of covariating gene expression using graph analysis on pairwise expression ratios · Bioinform. 2019 |
Bioinformatics and computational biology
gene expression analysis |
0.4 | 1 | 2019 | Determination of sets of covariating gene expression using graph analysis on pairwise expression ratios · Bioinform. 2019 |
Methods — techniques the papers use, named apart from their topics
pairwise expression ratio · 0.4graph analysis · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Determination of sets of covariating gene expression using graph analysis on pairwise expression ratiosabstractMotivation: RNA quantification experiments result in compositional data, however usual methods for compositional data analysis [additive log ratio (alr), centered log ratio (clr), isometric log ratio (ilr)] do not apply easily and give results difficult to interpret. To handle this, a method based on disjoint subgraphs in a graph whose nodes are the quantified RNAs is proposed. Edges in the graph are defined by lack of change in ratios of the corresponding RNAs between conditions. Results: The methods is suited for qRT-PCR and RNA-Seq data analyses, and leads to easy-to-interpret, graphical results and the identification of set of genes that share a similar behavior when the studied condition changes. For qRT-PCR data, it has better statistical properties than the common ΔΔCq method. Availability and implementation: Construction of all pairwise ratio analysis P-values matrix, and conversion into a graph was implemented in an R package, named SARP.compo. It is freely available for download on the CRAN repository. Example R script using the package are provided as Supplementary Material; the R package includes the data needed. One of these scripts reproduces the Figure 2 of this paper. Supplementary information: Supplementary data are available at Bioinformatics online. Emmanuel Curis, Cindie Courtin, Pierre Alexis Geoffroy, Jean-Louis Laplanche, Bruno Saubaméa, Cynthia Marie-Claire |
Bioinform. | 3 |