Mining gene expression data based on template theory

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چکیده

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Mining gene expression data based on template theory

MOTIVATION It is understood that clustering genes are useful for exploring scientific knowledge from DNA microarray gene expression data. The explored knowledge can be finally used for annotating biological function for novel genes. Representing the explored knowledge in an efficient manner is then closely related to the classification accuracy. However, this issue has not yet been paid the att...

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The field of gene expression data analysis has grown in the past few years from being purely data-centric to integrative, aiming at complementing microarray analysis with data and knowledge from diverse available sources. In this review, we report on the plethora of gene expression data mining techniques and focus on their evolution toward knowledge-based data analysis approaches. In particular...

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Mining Gene Expression Data

Micro-array data has enabled us to obtain an overview of the cell by measuring the expression levels of thousands of genes simultaneously. It has also opened the possibility for predicting possible cancerous cells accurately. Since these data sets are very large, we need to utilize machine learning techniques to analyse them efficiently. However, micro-array data also poses challenging problems...

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Template-Based Gene Expression Analysis

Analysis of gene expression profiles of genome-wide data created in cDNA-microarray experiments is a complex task that seems to require an inclusion of biological knowledge. We have attempted to express this knowledge by using an approach of the so-called templates. An analysis method has been defined and implemented. It has been tested on the fibroblast data set [3]. Preliminary results sugges...

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2004

ISSN: 1367-4803,1460-2059

DOI: 10.1093/bioinformatics/bth323