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DNA-binding proteins are a class of proteins which have a specific or general affinity to DNA and include three important components: transcription factors; nucleases, and histones. DNA-binding proteins also perform important roles in many types of cellular activities. In this paper we describe machine learning systems for the prediction of DNA-binding proteins where a Support Vector Machine and a Cascade Correlation Neural Network are optimized and then compared to determine the learningdoi:10.5121/ijbb.2012.2201 fatcat:jozzoltixjfvfdhdjoddnad3v4