EDBT 2026 Demo / reviewers in the wild / expert
Zachary J. Nolen
dblp:425/3402
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2025
0000-0001-8146-8016ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 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 · 50% Computational science and engineering · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › population genetics
population genomics |
0.9 | 1 | 2025 | PopGLen - a Snakemake pipeline for performing population genomic analyses using genotype likelihood-based methods · Bioinform. 2025 |
Computational science and engineering › workflow management
workflow automation |
0.9 | 1 | 2025 | PopGLen - a Snakemake pipeline for performing population genomic analyses using genotype likelihood-based methods · Bioinform. 2025 |
Methods — techniques the papers use, named apart from their topics
snakemake workflow · 0.9genotype likelihood · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | PopGLen - a Snakemake pipeline for performing population genomic analyses using genotype likelihood-based methodsabstractSUMMARY: PopGLen is a Snakemake workflow for performing population genomic analyses within a genotype-likelihood framework, integrating steps for raw sequence processing of both historical and modern DNA, quality control, multiple filtering schemes, and population genomic analysis. Currently, the population genomic analyses included allow for estimating linkage disequilibrium, kinship, genetic diversity, genetic differentiation, population structure, inbreeding, and allele frequencies. Through Snakemake, it is highly scalable, and all steps of the workflow are automated, with results compiled into an HTML report. PopGLen provides an efficient, customizable, and reproducible option for analyzing population genomic datasets across a wide variety of organisms. AVAILABILITY AND IMPLEMENTATION: PopGLen is available under GPLv3 with code, documentation, and a tutorial at https://github.com/zjnolen/PopGLen. An example HTML report using the tutorial dataset is included in the Supplementary Material. Zachary J. Nolen |
Bioinform. | 1 |