Michael Salter‐Townshend

This study identifies candidate genes for trypanotolerance in African cattle by integrating genomic and transcriptomic data from hybrid populations.

The paper identifies genomic regions with increased reciprocal recombination in autism spectrum disorder families, suggesting these regions may contribute to disease through unfavourable haplotypes.

The paper uses an agent-based model to evaluate how sampling strategies affect the accuracy of social network metrics in animal studies, identifying optimal trade-offs between coverage, frequency, and duration.

The paper uses local ancestry inference tools to analyze admixture in African and European cattle populations, identifying functional consequences of ancestry on disease resistance and physiological traits.

The paper shows that random subsamples of animal populations can reliably reveal intrinsic social differences, highlighting the importance of accounting for sampling biases in social network analysis.

The paper uses the Mundlak model to address group-level prediction challenges in UK Biobank data, showing how population structure affects coronary artery disease risk.

aniSNA assesses bias and uncertainty in animal social networks from telemetry data, enabling reliable network metrics and robust analysis.

This study uses whole-genome sequencing and SNP arrays to analyze Criollo cattle from Colombia and Venezuela, revealing African and Asian admixture and selection signatures linked to adaptive traits.

This paper introduces an algorithm to infer ancestry segments and admixture events without prior knowledge of mixing groups, showing improved accuracy over existing methods.