Premium
Heterofusion: Fusing genomics data of different measurement scales
Author(s) -
Smilde Age K.,
Song Yipeng,
Westerhuis Johan A.,
Kiers Henk A. L.,
Aben Nanne,
Wessels Lodewyk F. A.
Publication year - 2021
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.3200
Subject(s) - context (archaeology) , computer science , genomics , measure (data warehouse) , ordinal scale , sensor fusion , interval (graph theory) , binary number , data science , data mining , artificial intelligence , mathematics , biology , statistics , genome , genetics , arithmetic , combinatorics , gene , paleontology
In systems biology, it is becoming increasingly common to measure biochemical entities at different levels of the same biological system. Hence, data fusion problems are abundant in the life sciences. With the availability of a multitude of measuring techniques, one of the central problems is the heterogeneity of the data. In this paper, we discuss a specific form of heterogeneity, namely, that of measurements obtained at different measurement scales, such as binary, ordinal, interval, and ratio‐scaled variables. Three generic fusion approaches are presented of which two are new to the systems biology community. The methods are presented, put in context, and illustrated with a real‐life genomics example.