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By Yanqing Zhang, Jagath C. Rajapakse, Albert Y. Zomaya, Yi Pan. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization.
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