Call For Paper Volume:4 Issue:10 Oct'2017 |

Discovering Phenotype Structures in Mining Discriminative Signature

Publication Date : 28/02/2015

Author(s) :

Sudha.C , Sathiya.A , Divya.K , Jones Merlin.E , Jones Merlin.E.

Volume/Issue :
Volume 2
Issue 2
(02 - 2015)

Abstract :

Data Mining is the process of extracting the information from a dataset and transforms it into an understandable structure. An essential problem in microarray data analysis is to discover phenotype structures. The existing techniques for phenotype structure discovery are singleton discriminability based approach and combination discriminability based approach.The goal is to discovery groups of samples equivalent to different phenotypes (such as disease or normal). Novel sequence dissimilarity is to be proposed for systematic expression values among genes. This is important for the subsequent analysis by the biologists.  The sequence model is that only a small number of genes are needed to achieve  high phenotype discriminability.A g* sequence model to characterize the phenotype structure.This property helps to improve the  robustness of the proposed model and enables to identify the highly discriminative signatures with only a small number of genes.

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Discovering Phenotype Structures in Mining Discriminative Signature

February 27, 2015