Biological Data Science
How could we build cutting-edge AI tools to translate biological data into solutions and guide better decision-making?
Our interdisciplinary approach focuses on three key strategies. First, we highlight the importance of mining public datasets using AI-bioinformatics expertise to unveil valuable biological insights that could pave the way for new therapeutics and diagnostics. This highlights the need for innovative tools to classify complex biological patterns and user-friendly databases for easy data comparison. Second, abundant data on nucleic acids and proteins provide a foundation to model factors influencing human health, such as infectious diseases and cancer. Last, generative AI offers powerful solutions for tackling complex biological problems, enhancing tasks like classification and data augmentation. Together, these approaches will enhance our understanding of biological systems through ambitious applications of AI and advanced data analysis methods.
