Modeling evolutionary dynamics of persistent viral infections using data mining techniques
نویسندگان
چکیده
In recent years, large datasets combining virological, therapy and clinical parameters have been become available for research. Data mining can help virologists exploit these data to acquire new insights into virus dynamics and the interaction with the host. Data mining consists of a collection of techniques which find useful patterns in large amounts of data. Techniques such as hierarchical clustering or Bayesian networks have been successfully applied to HIV data [1].
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