Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Multivariate statistical approach and machine learning for the evaluation of biogeographical ancestry inference in the forensic field.

Scientific reports - 28 May 2022

Alladio Eugenio, Poggiali Brando, Cosenza Giulia, Pilli Elena

Abstract excerpt

The biogeographical ancestry (BGA) of a trace or a person/skeleton refers to the component of ethnicity, constituted of biological and cultural elements, that is biologically determined. Nowadays, many individuals are interested in exploring their genealogy, and the capability to distinguish biogeographic information about population groups and subgroups via DNA analysis plays an essential role in several fields...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Forensic Genetics
Share to Genetics, Population

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Genotype

Share to Machine Learning

Share to Racial Groups

Source

Open in PubMed Open full text

Identifiers

PMID: 35643723
DOI: 10.1038/s41598-022-12903-0
PMCID: PMC9148302

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Multivariate statistical approach and machine learning for the evaluation of biogeographical ancestry inference in the forensic field.PMID 35643723Read ↗

Biogeographical ancestry, variable selection, and PLS-DA method: a new panel to assess ancestry in forensic samples via MPS technology.Semantic proximity Read ↗

A biogeographical ancestry inference pipeline using PCA-XGBoost model and its application in Asian populations.Semantic proximity Read ↗

A multivariate statistical approach for the estimation of the ethnic origin of unknown genetic profiles in forensic genetics.Semantic proximity Read ↗

Application of machine learning for ancestry inference using multi-InDel markers.Semantic proximity Read ↗

Systematic analyses of AISNPs screening and classification algorithms based on genome-wide data for forensic biogeographic ancestry inference.Semantic proximity Read ↗

Prediction of biogeographical ancestry from genotype: a comparison of classifiers.Semantic proximity Read ↗

Comparative evaluation of the MAPlex, Precision ID Ancestry Panel, and VISAGE Basic Tool for biogeographical ancestry inference.Semantic proximity Read ↗

Genetic structure analysis of a Northwest Chinese population using a self-developed DIP system and machine learning for forensic ancestry inference.Semantic proximity Read ↗

Machine learning-based geographical ancestry inference model for the Han Chinese population.Semantic proximity Read ↗

How to choose sets of ancestry informative markers: A supervised feature selection approach.Semantic proximity Read ↗

Dense SNP-based analyses complement forensic anthropology biogeographical ancestry assessments.Semantic proximity Read ↗

From the "Out of Africa Theory" Study to the Application of "DNA Biogeographic Ancestry Inference" in Criminal Investigation.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.