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DIVIS: a semantic DIstance to improve the VISualisation of heterogeneous phenotypic datasets
2022
BioData Mining
Background Thanks to the wider spread of high-throughput experimental techniques, biologists are accumulating large amounts of datasets which often mix quantitative and qualitative variables and are not always complete, in particular when they regard phenotypic traits. In order to get a first insight into these datasets and reduce the data matrices size scientists often rely on multivariate analysis techniques. However such approaches are not always easily practicable in particular when faced
doi:10.1186/s13040-022-00293-y
pmid:35379292
pmcid:PMC8981856
fatcat:xlg5pynydjfyhdeiaav2b2vy4e