We are pleased to announce the Uehara International Symposium 2023 "Big Data-Driven Approaches with AI in Life Sciences" sponsored by the Uehara Memorial Foundation will be held from June 5 to 7, 2023.
The tremendous improvements in computing power and data measurement capabilities are drastically changing the methodology of research in life sciences. The technologies for measuring intracellular molecules such as genomes and proteins, as typified by the next-generation sequencers, and the advancement and scale of imaging through the development of various sensors are generating big data at the molecular, individual, and population levels of life. This big data combines volume and complexity that far exceeds the level of analysis that can be done by humans based on just conventional knowledge and thus requires more than human intelligence to unravel true pictures behind it. This indicates that life sciences from now on will transform from hypothesis-driven to data-driven. To this end, it is essential to utilize the power of artificial intelligence (AI) that enables to link various types of biomedical big data to scientific discoveries. Furthermore, the discoveries made should lead to improved health, disease prevention, and innovative treatments through deeper understanding of life.
At this turning point in the methodology of science, the Uehara Memorial Foundation has established the 11th Special Research Project, "Big Data-Driven Approaches with AI in Life Sciences" and has been supporting 18 Japanese scientists for three years from 2020. Their activities cover the data-driven approaches with AI to big data of intracellular molecules, cells, individuals, and populations in various biomedical research fields.
In this international symposium, we invite 10 world-leading experts in this field from overseas and have an opportunity to listen to their cutting-edge studies together with outcome presentations by the 18 Uehara Research Grant recipients. Here we together with all attendants create a forum to discuss new generation of life sciences by data-driven approach with AI.