Info Hub Distinguished Lecture Series - Reverse-Gene-Finder
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Alzheimer’s Disease (AD) affects over 55 million people globally, yet the key genetic contributors remain poorly understood. Leveraging recent advancements in genomic foundation models, we present the innovative Reverse-Gene-Finder technology, a ground-breaking neuron-to-gene-token backtracking approach in a neural network architecture to elucidate the novel causal genetic biomarkers driving AD onset. Reverse-Gene-Finder comprises three key innovations. Firstly, we exploit the observation that genes with the highest probability of causing AD, defined as the most causal genes (MCGs), must have the highest probability of activating those neurons with the highest probability of causing AD, defined as the most causal neurons (MCNs). Secondly, we utilize a gene token representation at the input layer to allow each gene (known or novel to AD) to be represented as a discrete and unique entity in the input space. Lastly, in contrast to the existing neural network architectures, which track neuron activations from the input layer to the output layer in a feed-forward manner, we develop an innovative backtracking method to track backwards from the MCNs to the input layer, identifying the Most Causal Tokens (MCTs) and the corresponding MCGs. Reverse-Gene-Finder is highly interpretable, generalizable, and adaptable, providing a promising avenue for application in other disease scenarios.
Victor O.K. Li is Emeritus Professor, Chair Professor of Information Engineering (Sept 1997 – June 2025) and Cheng Yu-Tung Professor in Sustainable Development (March 2017 – June 2023) at the Department of Electrical and Electronic Engineering (EEE) of the University of Hong Kong, and Director of the HKU AI to Advance Well-being and Society Research Lab. He also directs three HKU-Cambridge University collaborative research platforms. He was the Head of EEE, Assoc. Dean (Research) of Engineering at HKU, and Founding Managing Director of HKU Versitech, the technology transfer and commercial arm of HKU. He also co-founded and is Chairman of the Board of award-winning Fano, Ltd. (fano.ai), Language AI company. His research interests include Artificial Intelligence for Social Good, AI and Healthcare, Clean Energy and Environment, Big Data, and Optimization Techniques. He received SB, SM, EE and ScD degrees in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology in 1977, 1979, 1980, and 1981, respectively. Previously, he was Professor of Electrical Engineering at the University of Southern California (USC), Los Angeles, California, USA, and Director of the USC Communication Sciences Institute. He is a Fellow of the Hong Kong Academy of Engineering, IEEE, and HKIE, and a UK Royal Academy of Engineering Senior Visiting Fellow.