【摘 要】
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Protein-protein interactions(PPIs)are of vital importance to most biological processes.Plenty of PPIs have been identified by wet-lab experiments in the past decades,but there are still abundant uncov
【出 处】
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第二届中国计算机学会生物信息学会议
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Protein-protein interactions(PPIs)are of vital importance to most biological processes.Plenty of PPIs have been identified by wet-lab experiments in the past decades,but there are still abundant uncovered PPIs.Furthermore,wet-lab experiments are expensive and limited by the adopted experimental protocols.Although various computational models have been proposed to automatically predict PPIs,and provided reliable interactions for experimental verification,the problem is still far from being solved.Novel and competent models are still anticipated.In this study,a neural network based approach called EnsDNN(Ensemble Deep Neural Networks)is proposed to predict PPIs based on different representations of amino acids.
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