Kasim, Shahreen and Deris, Safaai and Othman, Muhammad Razib (2008) The incorporation of biological knowledge in gene expression analysis: a review. In: Trends and directions in Bioinformatics, Vol. 1. Penerbit UTM, Johor, pp. 95-147. ISBN 978-983-52-0566-8
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Official URL: http://www.penerbit.utm.my/bookchapterdoc/FSKSM/bo...
In an attempt to understand complicated biological systems, large amount of gene expression data have been generated by many researchers. Because of large number of genes and the complexity of biological networks, clustering is a useful exploratory technique for analysis of gene expression data. However, there are still little research done in combining of biological knowledge especially GO as a guidance in the clustering process. This process is vital in determine the similarity of both biological and expression before the clustering process start. In addition to deal with large amount of gene expression data, researcher has to take account on the missing values and gene expression dimension datasets. It is also important in identify which clustering algorithms is the best to find the optimal cluster. Thus, comprehensive computational method is needed in order to give more ideal and simplest tool for researchers for searching the optimal cluster. This paper will describe in details about gene expression and gene ontology including related works in clustering algorithms, missing values imputation, dimension reduction, and tools of clustering gene expression data.
|Item Type:||Book Section|
|Uncontrolled Keywords:||biological systems, gene,|
|Subjects:||Q Science > QA Mathematics > QA76 Computer software|
Q Science > QH Natural history > QH301 Biology
|Divisions:||Computer Science and Information System (Formerly known)|
|Deposited By:||Fazli Masari|
|Deposited On:||16 Aug 2012 08:11|
|Last Modified:||05 Feb 2017 01:10|
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