Many of these pipelines are mainly data-driven and enable clustering and supervised machine learning techniques to find essential patterns of features contributing to the identification of, for example, proteins that are associated with NDDs [286], or to reveal cross-talk patterns in multi-omics data [287]

Many of these pipelines are mainly data-driven and enable clustering and supervised machine learning techniques to find essential patterns of features contributing to the identification…