Genomics data is crucial for understanding genetic diseases, personalizing medicine, and unlocking secrets of human evolution. However, progress in sequencing human genomic data is slow due to inherent challenges such as its complexity and size, variability, errors, and interpretation of results. Now, how can genomic studies such as the SG100K improve health outcomes and advance biomedical innovation? And in the age of AI, how can it be leveraged to overcome the challenges of decoding complex genomic data? To learn about the work so far, the lessons already learned, and the opportunities ahead, Tech Journalist Paul Mah speakers with Dr. Sebastian Maurer-Stroh, Executive Director of the Bioinformatics Institute at A*STAR and Matt Johnson, Managing Director for AI and Data at Temus.
