abstract = "An important problem of cancer diagnosis and treatment
is to distinguish tumors from malignant or benign.
Classifying tumors correctly leads us to target
specific therapies properly to maximizing efficiency
and reducing toxicity. Through the microarray
technology, it is possible that monitoring expression
in cells for numerous of genes simultaneously.
Therefore we are allowed to use potential information
hidden in the gene expression data to build a more
accurate and more reliable classification model on
tumor samples. In this paper we intend to investigate a
new approach for cancer classification using genetic
programming and microarray gene expression profiles.
The layered architecture genetic programming (LAGEP) is
applied to build the classification model. Some typical
cancer gene expression datasets are validated to
demonstrate the classification accuracy of the proposed