Demo Data from EDBT 2026 / reviewers in the wild / expert
Xavier Farré
dblp:204/2304
· DBLP profile ↗
3ranked-venue papers
1as first author
1since 2021 · last 2023
0000-0001-6838-9479ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author · 1 since 2021Systems, architecture and hardware · 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
2 papers |
Bioinformatics and computational biology · 100% |
Topics — the 5 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
molecular evolution |
0.7 | 1 | 2023 | CAAStools: a toolbox to identify and test Convergent Amino Acid Substitutions · Bioinform. 2023 |
Bioinformatics and computational biology › statistical genetics
genotype-phenotype association |
0.2 | 1 | 2023 | CAAStools: a toolbox to identify and test Convergent Amino Acid Substitutions · Bioinform. 2023 |
Bioinformatics and computational biology
phylogenetics |
0.2 | 1 | 2023 | CAAStools: a toolbox to identify and test Convergent Amino Acid Substitutions · Bioinform. 2023 |
Bioinformatics and computational biology › statistical genetics › genotype-phenotype association
disease association |
0.1 | 1 | 2020 | Genome-phenome explorer (GePhEx): a tool for the visualization and interpretation of phenotypic relationships supported by genetic evidence · Bioinform. 2020 |
Bioinformatics and computational biology › population genetics
linkage disequilibrium |
0.1 | 1 | 2020 | Genome-phenome explorer (GePhEx): a tool for the visualization and interpretation of phenotypic relationships supported by genetic evidence · Bioinform. 2020 |
Methods — techniques the papers use, named apart from their topics
orthologous protein alignment · 0.7pathway analysis · 0.4linkage disequilibrium analysis · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | CAAStools: a toolbox to identify and test Convergent Amino Acid SubstitutionsabstractMOTIVATION: Coincidence of Convergent Amino Acid Substitutions (CAAS) with phenotypic convergences allow pinpointing genes and even individual mutations that are likely to be associated with trait variation within their phylogenetic context. Such findings can provide useful insights into the genetic architecture of complex phenotypes. RESULTS: Here we introduce CAAStools, a set of bioinformatics tools to identify and validate CAAS in orthologous protein alignments for predefined groups of species representing the phenotypic values targeted by the user. AVAILABILITY AND IMPLEMENTATION: CAAStools source code is available at http://github.com/linudz/caastools, along with documentation and examples. Fabio Barteri, Alejandro Valenzuela, Xavier Farré, David de Juan, Gerard Muntané, Borja Esteve-Altava, Arcadi Navarro |
Bioinform. | 3 |
| 2020 | Genome-phenome explorer (GePhEx): a tool for the visualization and interpretation of phenotypic relationships supported by genetic evidenceabstractMOTIVATION: Association studies based on SNP arrays and Next Generation Sequencing technologies have enabled the discovery of thousands of genetic loci related to human diseases. Nevertheless, their biological interpretation is still elusive, and their medical applications limited. Recently, various tools have been developed to help bridging the gap between genomes and phenomes. To our knowledge, however none of these tools allows users to retrieve the phenotype-wide list of genetic variants that may be linked to a given disease or to visually explore the joint genetic architecture of different pathologies. RESULTS: We present the Genome-Phenome Explorer (GePhEx), a web-tool easing the visual exploration of phenotypic relationships supported by genetic evidences. GePhEx is primarily based on the thorough analysis of linkage disequilibrium between disease-associated variants and also considers relationships based on genes, pathways or drug-targets, leveraging on publicly available variant-disease associations to detect potential relationships between diseases. We demonstrate that GePhEx does retrieve well-known relationships as well as novel ones, and that, thus, it might help shedding light on the patho-physiological mechanisms underlying complex diseases. To this end, we investigate the potential relationship between schizophrenia and lung cancer, first detected using GePhEx and provide further evidence supporting a functional link between them. AVAILABILITY AND IMPLEMENTATION: GePhEx is available at: https://gephex.ega-archive.org/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Xavier Farré, Nino Spataro, Frédéric Haziza, Jordi Rambla De Argila, Arcadi Navarro |
Bioinform. | 1 |
| 2017 | Accelerating FaST-LMM for Epistasis Tests
Héctor Martínez 0002, Sergio Barrachina 0001, María Isabel Castillo, Enrique S. Quintana-Ortí, Jordi Rambla De Argila, Xavier Farré, Arcadi Navarro |
ICA3PP | 6 |