HumanLeukocyteAntigens (HLA), also known as histocompatibility antigens, are molecules found on all nucleated cells in the body. Histocompatibility antigens help the immune system to recognize whether or not a cell is foreign to the body, hence the success of an organ transplantation is strongly connected to the HLA systems of the donor-recipient pair. Beyond this important role, the HLA system seems to influence also the clinical course of hepatic cirrhosis, both on viral and autoimmune basis. However, not only different antigens have different importance w.r.t. hepatic cirrhosis, but, to make things more complicated, other not yet well characterized factors could play an important role. Is thus important to assess the existence of associations between haplotypic settings (possibly mixed with clinical and demographical information) and hepatic cirrhosis. Algorithms developed for frequent patterns discovery can help us to this aim. Thanks to their ability in handling a very large number of variables and the associated exponential search space, such techniques can discover interesting haplotypic patterns beyond traditional analysis methods capabilities.

Mining HLA patterns explaining liver diseases

Bonchi F;Giannotti F;
2006

Abstract

HumanLeukocyteAntigens (HLA), also known as histocompatibility antigens, are molecules found on all nucleated cells in the body. Histocompatibility antigens help the immune system to recognize whether or not a cell is foreign to the body, hence the success of an organ transplantation is strongly connected to the HLA systems of the donor-recipient pair. Beyond this important role, the HLA system seems to influence also the clinical course of hepatic cirrhosis, both on viral and autoimmune basis. However, not only different antigens have different importance w.r.t. hepatic cirrhosis, but, to make things more complicated, other not yet well characterized factors could play an important role. Is thus important to assess the existence of associations between haplotypic settings (possibly mixed with clinical and demographical information) and hepatic cirrhosis. Algorithms developed for frequent patterns discovery can help us to this aim. Thanks to their ability in handling a very large number of variables and the associated exponential search space, such techniques can discover interesting haplotypic patterns beyond traditional analysis methods capabilities.
2006
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Frequent patterns
Genetic data
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/62253
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