Core Viewpoint - James Watson, a pivotal figure in 20th-century science and co-discoverer of the DNA double helix structure, passed away at the age of 97, marking the end of an era in molecular biology [2][11]. Group 1: Discovery of DNA Structure - Watson and Francis Crick proposed the double helix structure of DNA, inspired by Rosalind Franklin's X-ray images, with their findings published in Nature on April 25, 1953 [3][9]. - The discovery of the DNA double helix is regarded as a landmark in biology, comparable to Darwin's theory of evolution, and it laid the foundation for the field of molecular biology [9][11]. Group 2: Academic and Research Contributions - From 1956 to 1976, Watson taught at Harvard University, advancing molecular biology research [10]. - Watson served as the director of Cold Spring Harbor Laboratory starting in 1968, significantly enhancing its funding and research capabilities, and later became its honorary president [10]. Group 3: Controversies and Legacy - Watson faced controversy in 2007 for suggesting a genetic link between intelligence and race, leading to his resignation from Cold Spring Harbor Laboratory [10]. - His works include the textbook "Molecular Biology of the Gene" (1965) and the bestseller "The Double Helix" (1968), and he played a role in establishing the Human Genome Project, completed in 2003 [10].

Group 1 - The article discusses the historical context and implications of the Human Genome Project (HGP), initiated in 2000, which aimed to map the human genome and its significance in understanding life [2][4] - It highlights the misleading metaphors often used to describe the genome, such as "blueprint" and "instruction manual," which oversimplify the complexity of genetic information [4][5] - The article emphasizes that decoding the genome has proven to be more complex than initially thought, leading to more questions rather than definitive answers about life processes [6][8] Group 2 - The author argues for a new perspective on biology that moves away from viewing life as a machine, suggesting that life operates through self-organizing principles rather than strict genetic control [7][9] - It is noted that life is a multi-layered process with each level having its own rules, and understanding life requires looking at these complex organizational structures rather than just genetic components [11][12] - The article concludes by suggesting that the intricacies of life should inspire awe and appreciation, rather than being reduced to simplistic comparisons with machines or divine creation [12][13]

Core Insights - Chen Runsheng is a pioneer in non-coding gene research and a participant in the Human Genome Project, which is one of the largest life science projects globally [1][2] - He emphasizes that the future of AI in China lies not in the quantity of chips but in the density of intelligent computing [1] Group 1: Contributions to Genomics - Under Chen's leadership, China became the sixth country globally to possess large-scale genome sequencing capabilities [2][6] - In 1999, China joined the International Human Genome Project, taking on the task of sequencing approximately 30 million base pairs of the human chromosome 3 short arm, which represented 1% of the entire project [6] - Chen's team innovated sequencing methods, completing their tasks two years ahead of schedule, demonstrating significant advancements in genomic research [6] Group 2: Discoveries in Non-Coding DNA - Chen discovered that only 2%-3% of the human genome encodes proteins, while 97% consists of non-coding sequences previously deemed "junk DNA" [6][7] - His team focused on these non-coding regions, leading to the identification of new disease-related loci, particularly in cancer research [7] Group 3: Open Science and Collaboration - Since 1993, Chen's team has established a comprehensive database of 640,000 non-coding molecular information, which they chose to share openly with the global scientific community [7] - Chen believes that science is a collective human contribution and emphasizes the importance of sharing research findings for the advancement of knowledge [7] Group 4: AI and Future Innovations - Chen has been involved in AI research since the late 1980s, applying artificial neural networks to predict coding genes [8] - His current work involves integrating traditional Chinese medicine data into AI models, aiming to create a platform that merges different medical perspectives [8] - He advocates for viewing AI not merely as a tool but as a new center for innovation, which could lead to more creative possibilities in research and development [8]