基于信噪比的蛋白质相互作用的预测

Prediction of Protein-Protein Interactions in Term of Signal-to-Noise Ratio

蛋白质间的相互作用在生命体中扮演着关键的角色.将改进的共鸣识别模型应用于预测酵母蛋白质间的相互作用,并改用信噪比为判别参数.此判别参数与之前的判别参数——峰值相比,在保证较高预测精度的基础上,还可以很好地区分阳性数据和随机数据,从而也就能较好地处理过度拟合的问题.

Protein-protein interactions play a critical role in the living body. In this work, the modified resonant recognition model is applied to predict interactions of the yeast proteins. Signal-to-noise ratio （SNR） is selected as a discriminant parameter. Comparing with the previously used peak value, SNR can show significant differences between the positive data and the random data more clearly without compromising prediction precision. Therefore, the proposed method can solve the over-fitting problem.