Pedro J. Martínez‐García

The paper presents the Almond Expression Atlas, a comprehensive transcriptomic resource integrating RNA-seq data to identify tissue-specific genes and improve gene expression analysis in almond.

This study integrates high-throughput phenomics and genomics to identify marker-trait associations and candidate genes for almond morphology and quality traits.

This study estimates heritability and breeding values for flowering and maturity time in almond using historical data and Bayesian models to improve breeding strategies.

The paper develops an open Python workflow using AI to analyze fruit morphology and morphometric traits in almonds, identifying new heritable traits for improved breeding strategies.

The paper analyzes pedigree data of 222 almond genotypes to identify two main breeding lines derived from three cultivars, highlighting genetic diversity and inbreeding trends across global breeding programs.