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In systems biology, it is becoming increasingly common to measure biochemicalentities at different levels of the same biological system. Hence, data fusionproblems are abundant in the life sciences. With the availability of amultitude of measuring techniques, one of the central problems is theheterogeneity of the data. In this paper, we discuss a specific form ofheterogeneity, namely that of measurements obtained at different measurementscales, such as binary, ordinal, interval and ratio-scaled variables. Threegeneric fusion approaches are presented of which two are new to the systemsbiology community. The methods are presented, put in context and illustratedwith a real-life genomics example.

Heterofusion: Fusing genomics data of different measurement scales