Dresden researchers have developed an intelligent algorithm that automatically identifies significant associations between latent variables in big data sets

An international team of scientists led by Dr. Carlo Vittorio Cannistraci, group leader of the Biomedical Cybernetics lab at the BIOTEChnology Center TU Dresden, developed ‘PC-corr’: an intelligent algorithm that can automatically discover key groups of interacting latent variables generating differences in big data. PC-corr has detected important molecular signatures in more than six different fields of omic science (e.g. lipidomics, metagenomics, genomics and mechanomics), a step forward towards combinatorial biomarker discovery in precision medicine.

Press release