Knowledge discovery within precision medicine big data is crucial for advancing clinical translational applications. By leveraging biomedical knowledge, we can facilitate the uncovering of new insights in biomedicine. We have developed a suite of methods and tools, including: (1) pioneering biological theme comparison for complex experimental designs, (2) universal enrichment analysis methods for omics data interpretation, (3) semantic similarity measurement to aid in biological knowledge discovery, (4) cistromic data mining for identifying co-regulators, (5) integration of biological knowledge to enhance single-cell clustering interpretability, and (6) characterization of single-cell functional states and identification of spatial specific biological functions. These methods and software broaden the application of biomedical knowledge across diverse species, facilitating biological big data mining and uncovering novel disoveries.
