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Machine learning applied to transcriptomic data to identify genes associated with feed efficiency in pigs.

Miriam PilesCarlos Fernandez-LozanoMaría Velasco-GalileaOlga González-RodríguezJuan Pablo SánchezDavid TorrallardonaMaria BallesterRaquel Quintanilla
Published in: Genetics, selection, evolution : GSE (2019)
ML algorithms and RNA-Seq expression data were found to provide good performance for classifying pigs into high or low RFI groups. Classification was better with gene expression data from liver than from duodenum. Genes associated with FE in liver and duodenum tissue that can be used as predictive biomarkers for this trait were identified.
Keyphrases
  • machine learning
  • rna seq
  • big data
  • single cell
  • gene expression
  • electronic health record
  • deep learning
  • artificial intelligence
  • poor prognosis
  • dna methylation
  • data analysis
  • genome wide
  • binding protein