EDBT 2026 Demo / reviewers in the wild / expert
Adrian Baez-Ortega
dblp:167/1728
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 2019
0000-0002-9201-4420ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2 · 2 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% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
High-performance computing · 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 › genomics › microbial genomics
bacterial genome analysis |
0.2 | 1 | 2015 | IonGAP: integrative bacterial genome analysis for Ion Torrent sequence data · Bioinform. 2015 |
Bioinformatics and computational biology
comparative genomics |
0.1 | 1 | 2015 | IonGAP: integrative bacterial genome analysis for Ion Torrent sequence data · Bioinform. 2015 |
High-performance computing
scientific computing systems |
0.1 | 1 | 2015 | IonGAP: integrative bacterial genome analysis for Ion Torrent sequence data · Bioinform. 2015 |
Methods — techniques the papers use, named apart from their topics
sequence assembly · 0.4genome annotation · 0.4bacterial classification · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Computational approaches for discovery of mutational signatures in cancerabstractThe accumulation of somatic mutations in a genome is the result of the activity of one or more mutagenic processes, each of which leaves its own imprint. The study of these DNA fingerprints, termed mutational signatures, holds important potential for furthering our understanding of the causes and evolution of cancer, and can provide insights of relevance for cancer prevention and treatment. In this review, we focus our attention on the mathematical models and computational techniques that have driven recent advances in the field. Adrian Baez-Ortega, Kevin Gori |
Briefings Bioinform. | 1 |
| 2015 | IonGAP: integrative bacterial genome analysis for Ion Torrent sequence dataabstractUNLABELLED: We introduce IonGAP, a publicly available Web platform designed for the analysis of whole bacterial genomes using Ion Torrent sequence data. Besides assembly, it integrates a variety of comparative genomics, annotation and bacterial classification routines, based on the widely used FASTQ, BAM and SRA file formats. Benchmarking with different datasets evidenced that IonGAP is a fast, powerful and simple-to-use bioinformatics tool. By releasing this platform, we aim to translate low-cost bacterial genome analysis for microbiological prevention and control in healthcare, agroalimentary and pharmaceutical industry applications. AVAILABILITY AND IMPLEMENTATION: IonGAP is hosted by the ITER's Teide-HPC supercomputer and is freely available on the Web for non-commercial use at http://iongap.hpc.iter.es. CONTACT: [email protected] or [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Adrian Baez-Ortega, Fabian Lorenzo-Diaz, Mariano Hernandez, Carlos Ignacio Gonzalez-Vila, José Luis Roda García, Marcos Colebrook |
Bioinform. | 1 |