A novel approach for highly-diverse multi-modal data fusion:
- It does not require preprocessing of any of the input data to perform heterogeneous data fusion; thus enabling simple integration of categorical as well as different types of numerical data,
- It does not demand a certain (possibly different) number of replicates for each type of measure and,
- It is specially suited for cases where highly-diverse kinds of variables (measures) have to be compared or clustered, in particular when they are not available for all the biological material under analysis.
Contact: Milton Pividori