Enhancer Prediction in Proboscis Monkey Genome: A Comparative Study


  • Norshafarina Omar Department of Cognitive Sciences, Universiti Malaysia Sarawak.
  • Yu Shiong Wong Department of Cognitive Sciences, Universiti Malaysia Sarawak.
  • Xi Li Life Science Informatics, Data 61, CSIRO.
  • Yee Ling Chong Faculty of Resource Sciences and Technology , Universiti Malaysia Sarawak.
  • Mohd Tajuddin Abdullah Kenyir Research Institute, Universiti Malaysia Terengganu.
  • Nung Kion Lee Department of Cognitive Sciences, Universiti Malaysia Sarawak.


Enhancer Annotation, Enhancer Prediction, Motif Discovery, Proboscis Monkey,


Genome annotation is an essential task for understanding and analyzing the whole genome and its function. We have sequenced the complete proboscis Monkey (Nasalis larvatus) genome due to its importance for medical and evolutionary studies. We have performed an initial annotation of the genes genome using the MAKER gene annotation pipeline. 3084 genes were predicted from chromosome 18 of the genome using six eukaryotic model species. Intergenic regions possibly enriched with enhancers are then predicted using five different tools: DeepBind, LS-GKM, GMFR-CNN, CSI-ANN and iEnhancer-2L. These tools find the enhancers of the complex intergenic regions based on epigenetic features, in which intergenic regions are seen as a potential region for enhancers with a certain epigenetic features bound to it. Empirical results demonstrate competitive performance using different prediction tools with multiple epigenetic features to predict the enhancers for chromosome 18 in proboscis monkey. Based on the findings of this study, predicted enhancers can be used for the purpose of scientific and genomic discoveries.

Author Biography

Yu Shiong Wong, Department of Cognitive Sciences, Universiti Malaysia Sarawak.



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How to Cite

Omar, N., Wong, Y. S., Li, X., Chong, Y. L., Abdullah, M. T., & Lee, N. K. (2017). Enhancer Prediction in Proboscis Monkey Genome: A Comparative Study. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2-9), 175–179. Retrieved from https://jtec.utem.edu.my/jtec/article/view/2694