lu_tp_01_06.ab

是一个遗传算法的C++实现

CLASSIFICATION AND DIAGNOSTIC PREDICTION OF CANCERS USING GENE
EXPRESSION PROFILING AND ARTIFICIAL NEURAL NETWORKS

Javed Khan, Jun S. Wei, Markus Ringn閞, Lao H. Saal, Marc Ladanyi,
Frank Westermann, Frank Berthold, Manfred Schwab, 
Cristina R. Antonescu, Carsten Peterson, and Paul S. Meltzer


Abstract

The purpose of this study was to develop a method of classifying
cancers to specific diagnostic categories based on their gene
expression signatures using artificial neural networks (ANNs). We
trained the ANNs using the small round blue cell tumors (SRBCTs) as a
model. These cancers belong to four distinct diagnostic categories,
and often present diagnostic dilemmas in clinical practice. The ANNs
correctly classified all samples and identified the genes most
relevant to the classification. Expression of several of these genes
has been reported in SRBCTs, but most have not been associated with
these cancers. To test the ability of the trained ANN models to
recognize SRBCT, we analyzed additional blinded samples that were not
previously used for the training procedure, and correctly classified
them in all cases. This study demonstrates the potential applications
of these methods for tumor diagnosis and the identification of
candidate targets for therapy.

LU TP 01-06