This chapter aims to describe data integration and data mining techniques in the context of systems biology studies. It argues that the different methods available in the field of data integration can be very useful in making research in the field of systems biology easier. Moreover data mining is an important task to take into account in this context, therefore in this chapter, some aspects of data mining applied to systems biology specific case studies shall be discussed. The availability of a large number of specific resources, especially for the experimental researchers, is something difficult for users who tried to explore gene, protein, and pathway data for the first time. This chapter finally aims to highlight the complexity in the systems biology data and to provide an overview of the data integration and mining approaches in the context of systems biology using a specific example for the Cell Cycle database and the Cell Cycle models simulation. © 2009, IGI Global.
Multi-level data integration and data mining in systems biology
Alfieri Roberta;Milanesi Luciano
2008
Abstract
This chapter aims to describe data integration and data mining techniques in the context of systems biology studies. It argues that the different methods available in the field of data integration can be very useful in making research in the field of systems biology easier. Moreover data mining is an important task to take into account in this context, therefore in this chapter, some aspects of data mining applied to systems biology specific case studies shall be discussed. The availability of a large number of specific resources, especially for the experimental researchers, is something difficult for users who tried to explore gene, protein, and pathway data for the first time. This chapter finally aims to highlight the complexity in the systems biology data and to provide an overview of the data integration and mining approaches in the context of systems biology using a specific example for the Cell Cycle database and the Cell Cycle models simulation. © 2009, IGI Global.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.