TY - GEN
T1 - The Performance Enhancement of Statistically Significant Bicluster Using Analysis of Variance
AU - Vengatesan, K.
AU - Mahajan, S. B.
AU - Sanjeevikumar, P.
AU - Moin, Sana
PY - 2018/1/1
Y1 - 2018/1/1
N2 - In this article, the performance enhancement of statistically significant bicluster using analysis of variance is articulated. Various statistical methods are used to analyze the gene expression level. It is found that analysis of variance is one of the efficient methods for aggregation between a pair of genes. It computes the values by comparing the mean value of each group, and results are tested using the hypothesis to calculate the p-value. Various tests are conducted to increase the performance of the gene pair. Various clustering techniques are functional to investigate the gene expression information for both homogeneous and heterogeneous. Statistical approaches are used to identify the relevant information from the subset of genes. Various testing methods were conducted to enhance the performance of correlated genes. When compared with the biclustering methods such as the paired t-test, two-sample tests, the ANOVAs One sample test produces better result.
AB - In this article, the performance enhancement of statistically significant bicluster using analysis of variance is articulated. Various statistical methods are used to analyze the gene expression level. It is found that analysis of variance is one of the efficient methods for aggregation between a pair of genes. It computes the values by comparing the mean value of each group, and results are tested using the hypothesis to calculate the p-value. Various tests are conducted to increase the performance of the gene pair. Various clustering techniques are functional to investigate the gene expression information for both homogeneous and heterogeneous. Statistical approaches are used to identify the relevant information from the subset of genes. Various testing methods were conducted to enhance the performance of correlated genes. When compared with the biclustering methods such as the paired t-test, two-sample tests, the ANOVAs One sample test produces better result.
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U2 - 10.1007/978-981-10-4762-6_64
DO - 10.1007/978-981-10-4762-6_64
M3 - Conference contribution
AN - SCOPUS:85040002382
SN - 9789811047619
T3 - Lecture Notes in Electrical Engineering
SP - 671
EP - 678
BT - Advances in Systems, Control and Automation - ETAEERE-2016
PB - Springer Verlag
T2 - International Conference on Emerging Trends and Advances in Electrical Engineering and Renewable Energy, ETAEERE 2016
Y2 - 17 December 2016 through 18 December 2016
ER -