4.3 Review

The ENCODE Project and Perspectives on Pathways

期刊

GENETIC EPIDEMIOLOGY
卷 38, 期 4, 页码 275-280

出版社

WILEY
DOI: 10.1002/gepi.21802

关键词

evolutionary computing; ENCODE; machine learning; pathway analysis

资金

  1. NIH grants [LM010098, LM009012, LM011360, EY022300, GM103506, GM103534]
  2. European Union FP7 Grant [601456-2]

向作者/读者索取更多资源

The recently completed ENCODE project is a new source of information on metabolic activity, unveiling knowledge about evolution and similarities among species, refuting the myth that most DNA is junk and has no actual function. With this expansive resource comes a challenge: integrating these new layers of information into our current knowledge of single-nucleotide polymorphisms and previously described metabolic pathways with the aim of discovering new genes and pathways related to human diseases and traits. Further, we must determine which computational methods will be most useful in this pursuit. In this paper, we speculate over the possible methods that will emerge in this new, challenging field.

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