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How to discriminate distal regulatory elements to a gene target is challenging in understanding gene regulation and illustrating causes of complex diseases. Among known distal regulatory elements, enhancers interact with a target gene’s promoter to regulate its expression. Although the emergence of many machine learning approaches has been able to predict enhancer-promoter interactions (EPIs), global and precise prediction of EPIs at the genomic level still requires further exploration.In this paper, we develop an integrated EPIs prediction method, called EpPredictor with improved performance. By using various features of histone modifications, transcription factor binding sites, and DNA sequences among the human genome, a robust supervised machine learning algorithm, named LightGBM, is introduced to predict enhancer-promoter interactions (EPIs). Among six different cell lines, our method effectively predicts the enhancer-promoter interactions (EPIs) and achieves better performance in F1-score and AUC compared to other methods, such as TargetFinder and PEP.

How to supply electricity to the remote areas has become a very pressing issue for some countries which do not have the ability to connect all power grids to the whole country temporarily. At the same time, with the increase of fossil fuel costs and the continuous development of renewable energy generation technology, the construction of a hybrid renewable energy microgrid system seems to become an economic and technical approach to resolve the power shortage problem in the remote areas of some countries. Based on the analysis of local natural resources and load conditions, this paper designed a microgrid system which contains the wind turbines, PV systems, a diesel generator and an energy storage module to meet the power supply needs of the small town Amdjarass in Chad. Then the authors optimized the capacity of this microgrid and estimated the cost of this system with the utilization of HOMER software. In the end, this paper set the optimal configuration scheme with the target of the lowest COE and analyzed the sensitivity of some important parameters which could affect the economic performance.