Chemogenomics data are often difficult to analyze, given their large amounts, heterogeneity, and multi-dimensional nature. Network representations and other graphical methods are utilized to aid in data analysis. This review covers several recently introduced visualization methods for multi- or high-dimensional compound activity data that are designed for specific applications.
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Hu et al. (2013) studied this question.
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