Principal Investigator: Dr Sai Zhang
Stanford UniversityTags: 41751, Complex Traits, disease, genetics/genotyping, health, Machine Learning, prediction
Aims: A machine learning-based framework will be built to predict various human complex traits and diseases from personal genomes. Meanwhile, key genes and pathways contributing to the trait or disease can be uncovered from the system for further biological and clinical validation.
Rationale: The genome underlies the development of traits and diseases. By extensively exploiting how pathogenic a mutation is, what the function of a gene is, and how genes work together, we can use artificial intelligence to automatically learn the molecular pattern of a specific phenotype from a large amount of genotype or sequencing data.
Duration: The approximate duration of this project is one year.
Impact: Our framework is of great importance for genetic test, clinical screening and drug discovery.