Decision Trees and Applications.

In many cases, the meaning of information is wrongly related to either the sense of data or the notion of knowledge. There is a crucial sequence of steps before information becomes knowledge and the value of data depends in the existence of information so as to produce knowledge. The most common method for producing knowledge through data is based on data analysis and primarily in the interpretation of results. This is the way humans make decisions, based on their existing knowledge, and thus using this method, they try to simulate several artificial decision tools. Decision trees (DTs) are such a tool. Their goal is consisted of automatic or semiautomatic big data analysis as well as creating new patterns. DT can be applied in various scientific fields such as bioinformatics. The most commonly used applications of decision trees are data mining and data classification. This study reviews these applications in bioinformatics.