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

Scalable CNN-based classification of selective sweeps using derived allele frequencies.

Bioinformatics (Oxford, England) - 1 Sept 2024

van den Belt Sjoerd, Zhao Hanqing, Alachiotis Nikolaos

Abstract excerpt

MOTIVATION: Selective sweeps can successfully be distinguished from neutral genetic data using summary statistics and likelihood-based methods that analyze single nucleotide polymorphisms (SNPs). However, these methods are sensitive to confounding factors, such as severe population bottlenecks and old migration. By virtue of machine learning, and specifically convolutional neural networks (CNNs), new accurate...

Read the complete abstract on PubMed

Topics

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

Share to Algorithms
Share to Gene Frequency
Share to Machine Learning

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Neural Networks, Computer

Share to Polymorphism, Single Nucleotide

Share to Selection, Genetic

Source

Open in PubMed Open full text

Identifiers

PMID: 39230693
DOI: 10.1093/bioinformatics/btae385
PMCID: PMC11373383

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Scalable CNN-based classification of selective sweeps using derived allele frequencies.PMID 39230693Read ↗

Distinguishing between recent balancing selection and incomplete sweep using deep neural networks.Semantic proximity Read ↗

On convolutional neural networks for selection inference: revealing the lurking role of preprocessing, and the surprising effectiveness of summary statisticsSemantic proximity Read ↗

The persistence and loss of hard selective sweeps amid admixture in ancient EurasiansSemantic proximity Read ↗

Efficient detection and characterization of targets of natural selection using transfer learningSemantic proximity Read ↗

A likelihood approach for uncovering selective sweep signatures from haplotype dataSemantic proximity Read ↗

diploS/HIC: An Updated Approach to Classifying Selective Sweeps.Semantic proximity Read ↗

Deep estimation of the intensity and timing of selection from ancient genomesSemantic proximity Read ↗

Deep estimation of the intensity and timing of natural selection from ancient genomes.Semantic proximity Read ↗

S/HIC: Robust identification of soft and hard sweeps using machine learningSemantic proximity Read ↗

Identifying and classifying shared selective sweeps from multilocus dataSemantic proximity Read ↗

Detecting adaptive introgression in human evolution using convolutional neural networks.Semantic proximity Read ↗

Scalable ARG-free Detection of Denisovan-mediated Superarchaic Introgression Reveals Heterogeneous Patterns across PopulationsSemantic proximity Read ↗

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