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Genetics, Population

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A Machine-Learning-Based Approach to Prediction of Biogeographic Ancestry within Europe.

International journal of molecular sciences
Data obtained with the use of massive parallel sequencing (MPS) can be valuable in population genetics studies. In particular, such data harbor the potential for distinguishing samples from different populations, especially from those coming from adj...

On convolutional neural networks for selection inference: Revealing the effect of preprocessing on model learning and the capacity to discover novel patterns.

PLoS computational biology
A central challenge in population genetics is the detection of genomic footprints of selection. As machine learning tools including convolutional neural networks (CNNs) have become more sophisticated and applied more broadly, these provide a logical ...

Domain-adaptive neural networks improve supervised machine learning based on simulated population genetic data.

PLoS genetics
Investigators have recently introduced powerful methods for population genetic inference that rely on supervised machine learning from simulated data. Despite their performance advantages, these methods can fail when the simulated training data does ...

Simplified detection of genetic background admixture using artificial intelligence.

Clinical genetics
Admixture refers to the mixing of genetic ancestry from different populations. Admixture is important for genomic medicine because it can affect how an individual responds to certain medications, how they metabolize drugs, and susceptibility to certa...

Interpreting generative adversarial networks to infer natural selection from genetic data.

Genetics
Understanding natural selection and other forms of non-neutrality is a major focus for the use of machine learning in population genetics. Existing methods rely on computationally intensive simulated training data. Unlike efficient neutral coalescent...

Ancestry analysis using a self-developed 56 AIM-InDel loci and machine learning methods.

Forensic science international
Insertion/deletion (InDel) polymorphisms can be used as one of the ancestry-informative markers in ancestry analysis. In this study, a self-developed panel consisting of 56 ancestry-informative InDels was used to investigate the genetic structures an...

Computationally Efficient Demographic History Inference from Allele Frequencies with Supervised Machine Learning.

Molecular biology and evolution
Inferring past demographic history of natural populations from genomic data is of central concern in many studies across research fields. Previously, our group had developed dadi, a widely used demographic history inference method based on the allele...

Artificial intelligence enables unified analysis of historical and landscape influences on genetic diversity.

Molecular phylogenetics and evolution
While genetic variation in any species is potentially shaped by a range of processes, phylogeography and landscape genetics are largely concerned with inferring how environmental conditions and landscape features impact neutral intraspecific diversit...

Tracing the genealogy origin of geographic populations based on genomic variation and deep learning.

Molecular phylogenetics and evolution
Assigning a query individual animal or plant to its derived population is a prime task in diverse applications related to organismal genealogy. Such endeavors have conventionally relied on short DNA sequences under a phylogenetic framework. These met...

Using Runs of Homozygosity and Machine Learning to Disentangle Sources of Inbreeding and Infer Self-Fertilization Rates.

Genome biology and evolution
Runs of homozygosity (ROHs) are indicative of elevated homozygosity and inbreeding due to mating of closely related individuals. Self-fertilization can be a major source of inbreeding which elevates genome-wide homozygosity and thus should also creat...