Thanks to technological advances, animal geneticists have an ever-expanding tool chest with which to study the inheritance of traits in livestock in order to improve production. Our long-range goal is to develop integrated resources that leverage prior investments in cyberinfrastructure to help maximize the utility of genotype-to-phenotype data to functionally annotate livestock genomes. The objectives of this particular application are: 1) development of machine learning-assisted data curation and automated semantic annotation, and 2) manual curation of genotype/phenotype, correlation, and heritability data. With the growing volume and breadth of information, it is increasingly difficult for curators to keep abreast of publications.
