Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Gonzalo Oteo-García

dblp:432/4264 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2026
0000-0002-0957-4014ORCID · reported

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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › population genetics
admixture analysis
1.012026
Mixtum: a graphical tool for two-way admixture analysis in population genetics based on f -statistics · Bioinform. 2026
Bioinformatics and computational biology
population genetics
1.012026
Mixtum: a graphical tool for two-way admixture analysis in population genetics based on f -statistics · Bioinform. 2026
Bioinformatics and computational biology › population genetics
ancestry inference
0.312026
Mixtum: a graphical tool for two-way admixture analysis in population genetics based on f -statistics · Bioinform. 2026

Methods — techniques the papers use, named apart from their topics

geometric interpretation · 1.0f-statistics · 1.0
YearPublicationVenuePosition
2026 Mixtum: a graphical tool for two-way admixture analysis in population genetics based on f -statistics
abstract
SUMMARY: Mixtum is a Python-based code that estimates ancestry contributions in a process of two-way admixture based on bi-allelic genotype data. The outcomes of Mixtum come from the geometric interpretation of the f-statistics formalism. Designed with user-friendliness as a priority, Mixtum allows to interactively handle a menu of user-supplied populations to build different mixture models in conjunction with the set of auxiliary populations required by the framework. The results are presented graphically and numerically. Importantly, Mixtum provides a novel index (an angle) that assesses the quality of the ancestral reconstruction of the model under scrutiny. The use and interpretation of the outcomes of Mixtum are explained and illustrated with case studies. AVAILABILITY AND IMPLEMENTATION: The open source code is available on GitHub at https://github.com/jmcastelo/mixtum and on Zenodo at https://doi.org/10.5281/zenodo.17789375. Mixtum is implemented in Python and runs on Linux, Windows and macOS.
José-María Castelo, José Ángel Oteo, Gonzalo Oteo-García
Bioinform.3