Juan Pedro Steibel

This study compares dyadic and marginal models for analyzing social interaction traits, showing that dyadic models better estimate genetic and environmental effects while marginal models can introduce bias.

This study applies social network analysis to AI-assisted automated monitoring data to analyze social structures in pigs, revealing changes in group dynamics and individual traits over time.

This study measures the maximum vertical height hens reach during wing flapping using a depth camera, finding an average of 51.0 cm with no physical correlates.

This study improves genetic mapping resolution in pigs by developing a high-density haplotype reference panel and a public imputation server.

This paper optimizes deep learning hyperparameters for genomic prediction using differential evolution, showing improved performance and reduced overfitting across livestock datasets.

This paper develops a local Bayesian regression method to detect sex-specific genetic interactions in complex traits, finding many new interactions with small effects.

This paper compares different prior distributions and genomic window strategies for genome-wide association analysis, finding that heavy-tailed and variable selection priors with adaptive windows perform best.

The paper identifies widespread RNA editing in pig transcriptomes, showing ADAR-mediated A-to-G transitions, particularly in repetitive regions like the PRE-1 SINE retrotransposon.