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Our understanding of genetic regulation would be improved by better knowledge of regulatory elements known as enhancers, which are not located alongside the genes they control. In a recent paper published in Briefings in Bioinformatics, KAUST researchers reviewed the differences between various computational approaches to this problem and outlined some of the major challenges in the field.
Improving our understanding of genetic regulation will have major biotechnological and medical implications, explained Vladimir Bajic from the University’s Computational Bioscience Research Center. Bajic is also the senior author of the paper.
The paper, which has been included in the International Society for Computational Biology’s list of recommended educational and training resources, surveyed more than 30 computational tools and methods for identifying enhancers.
“Each of them is based on different assumptions, and they do not produce the same or very similar results,” said Bajic. “The fact that there are so many methods indicates that there isn’t a single one which is very good, because then the others would have been sidelined.”
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