We decipher the underlying mechanisms of complex pathology of brain diseases from omics data and other available data acquired from high-throughput screening experiments. For this purpose, we also develop computational models and algorithms to interpret massive biodata.
We study on genes and pathways associated with disease progression of many neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, etc, and develop virtual disease models to identify promising therapeutic target genes and therapeutic chemicals. We also validate predictions through experiments as well.
We develop computer algorithms to obtain novel knowledge from accumulated but non-organized biological data and knowledge, and develop new disease databases to provide reliable data to construct accurate virtual models for drug discovery and disease studies.
We develop AI models for facilitating drug discovery, specifically therapeutic target prediction and ADME-Tox prediction.