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This paper attempts to employ learning based pattern classification technique to extract events from biological literature. Although various approaches to extract events have been explored, none is suitable for designing a practical system of event extraction. Extracting events more precisely is still an ongoing process. In this paper, new features that seem to be relevant for the given task are investigated...
Statistical analysis and association rule mining are two most efficient techniques, where the first one is used to identify differentially expressed/methylated genes across different types of samples or experimental conditions and the second one is used to determine expression/methylation relationships among them. In this article, we have performed an integrated analysis of statistical methods and...
MicroRNAs (miRNAs) are a class of small noncoding RNAs that are known to have critical functions across various biological processes. Simultaneous activities of multiple miRNAs can be monitored from their expression profiles under various conditions. We often build up coexpression networks from such profiles. Unfortunately, due to the change of experimental setups (or conditions), the expression profiles...
Clustering methods are used for unsupervised classification of tumor subclasses in microarray gene expression data sets organized in a fashion where the rows represent the tumor samples and columns represent the genes. Clustering algorithms can be very sensitive with respect to the set of features (genes) considered in the clustering process. It is important to select the set of informative and relevant...
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