Data Integration: an Approach to Improve the Preprocessing and Analysis of Gene Expression Data
نویسنده
چکیده
The integration and evaluation of data from multiple DNA microarray datasets for a specific analysis is an important and yet challenging problem. In contrast to the majority of studies, which are focused on a particular biological problem, the present paper examines how the combination of several related microarray datasets affects different areas of preprocessing and analysis of gene expression data, such as missing value imputation, gene clustering and biomarkers detection. For this purpose, three recently suggested integration models are reviewed and discussed. The biological impact of these specific integration algorithms on the three abovementioned analysis tasks is demonstrated on two types of gene expression data: time series and non-time series. The results are evaluated in terms of different validation measures.
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