A survey of recently emerged genome-wide computational enhancer predictor tools

Chung, Hung Hui (2018) A survey of recently emerged genome-wide computational enhancer predictor tools. A survey of recently emerged genome-wide computational enhancer predictor tools, 74. pp. 132-141. ISSN 1476-9271

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Abstract

The race for the discovery of enhancers at a genome-wide scale has been on since the commencement of next generation sequencing decades after the discovery of the first enhancer, SV40. A few enhancer-predicting features such as chromatin feature, histone modifications and sequence feature had been implemented with varying success rates. However, to date, there is no consensus yet on the single enhancer marker that can be employed to ultimately distinguish and uncover enhancers from the enormous genomic regions. Many supervised, unsupervised and semi-supervised computational approaches had emerged to complement and facilitate experimental approaches in enhancer discovery.In this review, we placed our focus on the recently emerged enhancer predictor tools that work on general enhancer features such as sequences, chromatin states and histone modifications, eRNA and of multiple feature approach. Comparisons of their prediction methods and outcomes were done across their functionally similar counterparts. We provide some recommendations and insights for future development of more comprehensive and robust tools.

Item Type: Article
Uncontrolled Keywords: Enhancer prediction, Supervised learning, Unsupervised learning, Semi-supervised learning, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak
Subjects: Q Science > Q Science (General)
Divisions: Academic Faculties, Institutes and Centres > Faculty of Resource Science and Technology
Depositing User: Hui
Date Deposited: 04 Apr 2018 01:04
Last Modified: 04 Apr 2018 01:04
URI: http://ir.unimas.my/id/eprint/19977

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