Sallam Mohammed Abdallah

Sallam applies statistical and computational methods to analyze phenotypic, genotypic, and pedigree data, contributing to genetic improvement on both national and international levels. Additionally, Sallam leverages machine learning for novel digital tools that enhance the efficiency and sustainability of breeding operations

• Digital and genetic tools to improve bones of laying hens (PI: Prof.Dirk-Jan de Koning)

• International genomic evaluation of dairy cattle (Interbull center)

• Genome Analysis BK0002
• Analysis of Genomes P000042
• Biology of Genomes P000043

• Sallam, M., et al. (2025). Genomic prediction of bone strength using differnt information sources. Animal.
• Sallam, M., et al. (2024). A deep learning method segments chicken keel bones from whole-body X-ray images. Poultry Science.
• Sallam, M., et al. (2024). Comparisons among longitudinal radiographic measures of keel bones, tibiotarsal bones, and pelvic bones versus post-mortem measures of keel bone damage in Bovans Brown laying hens housed in an aviary system. Frontier in Veterinary Science.
• Sallam, M., et al. (2024). Genetics of digital phenotypes of keel bones in laying hens. Genetics Selection Evolution. [Under review]
  Sallam, M., et al. (2024). Whole-body X-ray images of laying hens with keel bone
• annotations and masks for training deep learning models. Zenodo.
  Sallam, M., et al. (2023). Genetic markers associated with bone composition in laying hen. Genetics Selection Evolution.
• Sallam, M., et al. (2022). Across-countries genomic prediction using national breeding values or multitrait across-countries evaluation breeding values. Journal of dairy sciences.
• Sallam, M., et al. (2022). Dairy cattle genetic evaluation in EU countries. European Union Reference Centre for Zootechnics (Bovine breeding) 2019-2020 Final Report.