Multi-omic data integration enables discovery of hidden biological regularities

@article{Ebrahim2016MultiomicDI,
  title={Multi-omic data integration enables discovery of hidden biological regularities},
  author={Ali Ebrahim and Elizabeth Brunk and Justin Tan and Edward J. O'Brien and Donghyuk Kim and Richard Szubin and Joshua A. Lerman and Anna Lechner and Anand V. Sastry and Aarash Bordbar and Adam M. Feist and Bernhard O. Palsson},
  journal={Nature Communications},
  year={2016},
  volume={7}
}
Rapid growth in size and complexity of biological data sets has led to the ‘Big Data to Knowledge' challenge. We develop advanced data integration methods for multi-level analysis of genomic, transcriptomic, ribosomal profiling, proteomic and fluxomic data. First, we show that pairwise integration of primary omics data reveals regularities that tie cellular processes together in Escherichia coli: the number of protein molecules made per mRNA transcript and the number of ribosomes required per… 

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