K-Means Clustering on 3rd order polynomial based normalization of Acute Myeloid Leukemia (AML) and Acute Lymphocyte Leukemia (ALL)

Mehdi, Ahmed M., Sehgal, Mohammad Shoabib, Zayegh, Aladin, Begg, Rezaul and Manan, Abdul (2009). K-Means Clustering on 3rd order polynomial based normalization of Acute Myeloid Leukemia (AML) and Acute Lymphocyte Leukemia (ALL). In: 2009 Third International Conference on Electrical Engineering (ICEE 2009). Proceedings. ICEE 2009: 3rd International Conference on Electrical Engineering, Lahore, Pakistan, (36-40). 9-11 April, 2009. doi:10.1109/ICEE.2009.5173170


Author Mehdi, Ahmed M.
Sehgal, Mohammad Shoabib
Zayegh, Aladin
Begg, Rezaul
Manan, Abdul
Title of paper K-Means Clustering on 3rd order polynomial based normalization of Acute Myeloid Leukemia (AML) and Acute Lymphocyte Leukemia (ALL)
Formatted title
K-Means Clustering on 3rd order polynomial based normalization of Acute Myeloid Leukemia (AML) and Acute Lymphocyte Leukemia (ALL)
Conference name ICEE 2009: 3rd International Conference on Electrical Engineering
Conference location Lahore, Pakistan
Conference dates 9-11 April, 2009
Proceedings title 2009 Third International Conference on Electrical Engineering (ICEE 2009). Proceedings
Place of Publication Piscataway, NJ, USA
Publisher IEEE
Publication Year 2009
Sub-type Fully published paper
DOI 10.1109/ICEE.2009.5173170
Open Access Status
ISBN 9781424443604
9781424443611
Start page 36
End page 40
Total pages 5
Language eng
Formatted Abstract/Summary
Microarray expression data is one of the most widely used to find patterns in genetic expressions. The DNA Microarray Technique participates as one of the leading methods in Cancer Research. Due to the presence of immense noise, fewer numbers of samples and huge amount of genes, the useful genomic knowledge extraction from this technique is an important question in today's Biological Research. Scientists and Researchers are exploring efficient mathematical procedure to find realistic gene expressed knowledge. In this study K-Means Clustering technique is used on an efficient 3rd order polynomial based technique to normalize the genomic data of Acute Myeloid Leukemia (AML) and Acute Lymphocyte Leukemia (ALL). AML was used as a model to generate the coefficients of the polynomial by considering non trending, decorellation and offset based techniques. The K nearest Neighbor technique is used to estimate the missing values of microarray data and avoid the impact of missing data on clustering algorithm. The data can be regenerated easily using 3rd order polynomial normalization based on model generated by AML. Top ranked genes in each cluster have been presented in this paper which helps in finding functionally coregulated genes in ALL and AML.
Subjects 2208 Electrical and Electronic Engineering
Keyword Microarray
Clustering algorithm
Acute myeloid leukemia
Acute lymphocyte leukemia
Decorrelation
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Conference Paper
Collection: Institute for Molecular Bioscience - Publications
 
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