hulilab.orgHu Li Lab | Mayo Clinic

Hu Li Lab | Mayo ClinicHOMEPEOPLE PUBLICATIONS NEWS SOFTWARE + DATA POSITIONS CONTACT Hu Li, Ph.D. and his research team are skilled in formulating novel systems biology concepts that help to guide the development of innovative systems biology and Artificial Intelligence (AI) algorithms to unlock the underlying intricate interplay between genes that confer complex disease phenotypes. The active research areas of Dr. Li’s lab include systems biology, systems pharmacology and individualized systems medicine. The major theme in the research team is to uncover meaningful biological information that explains the properties of Big Data from new systems biology perspectives to foster individualized disease diagnosis, drug discovery, and precision medicine. The developed computational platforms guided by novel systems biology lens can open new angles to better understand disease etiology, drug discovery, modes of action of drugs, and design of treatment regimens from systems aspects. Over the past decades, Dr. Li’s team has helped advance numerous new systems biology concepts and tools including NetDecoder, Personalized Mutation Evaluator (PERMUTOR), Regulostat Inferelator (RSI), Machine Learning Assisted Network Inference (MALANI), Gene Utility Model (GUM), Phenotype Mapping (P-Map), Weight Engineering Artificial Neural Network Encoder (ANNE), Manifold Medicine, Manifold Epigenetics, Multi-Scale Locked State Models (LoSM), Spatially Informed Artificial Intelligence (SPIN-AI) and newly patented Hypothesis-Driven Artificial Intelligence (HD-AI) that each of these advanced models and powerful tools can be employed in broad disease types for novel discovery. Focus areas Practicing rigorous translational research in pharmacogenomics and individualized medicine, with a novel network approach to pharmacogenomics discoveries that leads to a better understanding of drug-response variations and therapeutic treatments for individual patients. Developing novel network tools and integrating various large-scale biomedical omics data to unravel the molecular mechanisms and pathophysiological roots that underpin complex disease systems at the personalized network level.© 2024 H Li • All Rights...