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Including gene networks to predict calving difficulty in Holstein, Brown Swiss and Jersey cattle.

Francesco TiezziMaria E ArceoJohn B ColeChristian Maltecca
Published in: BMC genetics (2018)
Regions identified in the genome were in the proximity of previously described quantitative trait loci that would most likely affect calving difficulty by altering the feto-pelvic proportion. Inclusion of identified networks did not increase prediction accuracy. The approach used in this paper could be extended to any instance with asymmetric distribution of phenotypes, for example, resistance to disease data.
Keyphrases
  • genome wide
  • dna methylation
  • copy number
  • electronic health record
  • rectal cancer
  • heat stress
  • high resolution
  • big data
  • dairy cows
  • gene expression
  • machine learning
  • genome wide identification