Demo Data from EDBT 2026 / reviewers in the wild / expert
Alison Laufer Halpin
dblp:311/2904
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
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 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › metagenomics
antimicrobial resistance gene detection |
0.6 | 1 | 2022 | GAMMA: a tool for the rapid identification, classification and annotation of translated gene matches from sequencing data · Bioinform. 2022 |
Bioinformatics and computational biology › genome annotation
gene annotation |
0.6 | 1 | 2022 | GAMMA: a tool for the rapid identification, classification and annotation of translated gene matches from sequencing data · Bioinform. 2022 |
Bioinformatics and computational biology › genome annotation
gene prediction |
0.6 | 1 | 2022 | GAMMA: a tool for the rapid identification, classification and annotation of translated gene matches from sequencing data · Bioinform. 2022 |
Bioinformatics and computational biology › genomics
microbial genomics |
0.6 | 1 | 2022 | GAMMA: a tool for the rapid identification, classification and annotation of translated gene matches from sequencing data · Bioinform. 2022 |
Methods — techniques the papers use, named apart from their topics
protein coding-level identity matching · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | GAMMA: a tool for the rapid identification, classification and annotation of translated gene matches from sequencing dataabstractMOTIVATION: Tools used to identify genes in microbial sequences using a reference database generally report matches as a percent identity, which can be difficult to interpret in cases with <100% sequence identity, as changes to specific amino acids can have dramatic effects on protein function, such as when they occur in substrate binding regions or enzyme active sites, which in turn can have dramatic effects on phenotypes like antimicrobial resistance or virulence. RESULTS: Here, we present GAMMA, an open-source tool for Gene Allele Mutation Microbial Assessment, which uses protein coding-level identity to make gene calls from any gene database and generates a classification (e.g. mutant, truncation) and translated annotation (e.g. Y190S mutation, truncation at residue 110) for these calls. GAMMA accurately called antimicrobial resistance genes from a large set of genomes faster than three other tools. It can also be used with any gene database, as we demonstrated by identifying virulence genes in the same genome set. Because of its speed and flexibility, GAMMA can be used to rapidly find and annotate any gene matches of interest in microbial sequencing data. AVAILABILITY AND IMPLEMENTATION: GAMMA is freely available as a Bioconda package (https://bioconda.github.io/recipes/gamma/README.html) and as a command line script (https://github.com/rastanton/GAMMA). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Richard A. Stanton, Nicholas Vlachos, Alison Laufer Halpin |
Bioinform. | 3 |