Prof. Ming Chen
Zhejiang University, China
Title: Data-driven Bioinformatics Approaches for Biological Age Prediction and Human Aging & Longevity Knowledge Graph
Abstract:
mingchen (0000-0002-9677-1699) - ORCID
The latest trends in bioinformatics and computational biology are increasingly driven by the incorporation of artificial intelligence (AI) techniques, which play a crucial role in analyzing large, complex biological datasets, understanding molecular mechanisms of life and disease, and accelerating the development of novel therapies. This talk will focus on the intersection of AI and bioinformatics, specifically on machine learning-based biological age prediction, and the human aging and longevity knowledge graph.
We propose a composite machine learning-based biological age (ML-BA) model based on biomarkers obtained from medical examination data, which combines multiple machine learning algorithms to generate a more accurate prediction of biological age. The composite ML-BA model is strongly associated with healthy risk indicators and various diseases, providing improved aging measurement capabilities and supporting the application potential of machine learning in aging research.
In addition, we introduce HALD, a text mining-based human aging and longevity knowledge graph containing essential entities in the field of aging and longevity, as well as related literature curated from PubMed. HALD enables comprehensive understanding of aging and longevity mechanisms, providing a foundation for developing anti-aging therapies for aging-related diseases. Our approach leverages state-of-the-art AI algorithms and techniques to advance the field of bioinformatics and computational biology, paving the way for future breakthroughs in aging research.
Keywords: Bioinformatics, Artificial intelligence, Machine learning, Biological age prediction, Aging and longevity knowledge graph
Biography:
Prof. Ming Chen received his PhD in Bioinformatics from Bielefeld University, Germany, in 2004. Currently he is working as a full Professor in Bioinformatics at College of Life Sciences, Zhejiang University. His group research work mainly focuses on, computational and functional analysis of transcriptomics, systems biology, and generally bioinformatics education, research and application. Prof. Chen is serving as an academic leader in Bioinformatics at Zhejiang University. He chairs the Bioinformatics society of Zhejiang Province, China. He serves as a committee member of Chinese societies for “Modelling and Simulation of Biological Systems”, “Computational Systems Biology”, “Functional Genomics & Systems Biology”, and “Biomedical Information Technology”. More info is available via his personal webpage: http://bis.zju.edu.cn/binfo/members/ming_chen.htm