A Comparative Study of Neural Network Architectures for Predicting Gene Expression in M. Tuberculosis
نویسنده
چکیده
Identification and classification of differentially expressed genes is a challenging process.The study was performed to find applicability of supervised feed forward neural networks to solve classification problems in microarray data.We used two neural network learning algorithms namely RBF and MLP for the classification of gene expression of mycobacterium tuberculosis.The result showed that MLP and RBF classifier have similar performance and both have given high prediction.
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