UC San Diego Center for Precision Computational Systems Network (PreCSN)

Precision in data science is critical for the generation of bold hypothesis and innovative downstream applications. Currently, precision is sought using machine learning tools that look beyond individual variability to extract patterns within multidimensional complex data. When combined with high level invariant rules, machine learning and statistical learning approaches can bring precision to a new level that has the power to radically transform the fields of data science. When geared to solve touch challenges (urgent and unmet needs) that are prioritized at the patient's bedside and iteratively refined through steps that are well-rationalized by real-world scenarios relevant to patient care, machine learning can transform the field of medicine by delivering insights that are actionable (i.e., reveal biomarkers, drug targets, treatment strategies, and other tools for precision medicine. By the same token, when directed to tackle some of the most compelling mysteries of foundational importance in biology and biomedical sciences, PreCSN can solve them through protein-protein and atom-atom networks! Our innovative suite of concepts, tools, and platforms have begun to demonstrate how data science can have an immediate impact on human health.