The ENCODE project and perspectives on pathways.
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.
Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, GA Utrecht, The Netherlands; Department of Medical Genetics, Biomedical Genetics, University Medical Center Utrecht, CX Utrecht, The Netherlands.
Vinicius
V
Tragante
Jason H
JH
Moore
Folkert W
FW
Asselbergs
D000818:Animals; D001185:Artificial Intelligence; D015894:Genome, Human / Q000235:genetics*; D023281:Genomics; D006801:Humans; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide / Q000235:genetics
ENCODE; evolutionary computing; machine learning; pathway analysis