Deep systems insights into the conceptual breakthrough of the noncoding RNA functional network and its role in cancer

Title : Deep systems insights into the conceptual breakthrough of the noncoding RNA functional network and its role in cancer

Abstract:

Noncoding RNAs (ncRNAs) transcribed from noncoding regions of the human genome are highly active and functionally significant; however, the nature of their functional system remains a subject of debate. Recent advances in big data and artificial intelligence have enabled a conceptual breakthrough in understanding this system. Unlike traditional models derived from protein studies and evolutionary conservation patterns, ncRNAs operate through distinct functional mechanisms and serve as critical endogenous regulators across all cancers. This presentation will provide deep systems-level insights into the ncRNA functional network and its universal role in cancer biology, and clarify major misconceptions in the field.
Cancer Research 2025 Youtube link: https://www.youtube.com/watch?v=whQeHl10ptE

Biography:

Dr. Wang graduated from the University of California, Riverside, and is passionate about computational biology, big data, and AI (combai.org). He develops advanced algorithms to extract fundamental insights from large-scale biological data. As a pioneer in mining the world’s largest biological database, he discovered that noncoding RNAs (ncRNAs) operate through a functional system distinct from proteins. This breakthrough helps explain how ncRNAs play a central role in various disease mechanisms and immune responses to environmental fluctuations. Dr. Wang further identified ncRNAs as the primary drivers in all cancers and key determinants of lifespan across animal species, challenging the long-standing protein-centric paradigm. He also developed novel computational tools to trace the evolutionary trajectory and origin of SARS-CoV-2, contributing to the understanding of the COVID-19 pandemic.
2025 Presentation Youtube Video Link: https://www.youtube.com/watch?v=whQeHl10ptE