I should have loved biology (jsomers.net)

Article summary

The article discusses how the author's high school biology education failed to inspire a love for the subject, presenting it as a dry recitation of facts rather than a fascinating exploration of the natural world. The author suggests that biology should be taught in a more engaging and questioning way, highlighting the intricate and complex processes that underlie life. The article also touches on the similarities between biology and computer science, with both fields involving complex systems and codes. The author reflects on their own journey to develop a deeper understanding of biology, including reading books and exploring the physical mechanisms that underlie biological processes.

Main themes

• Biology education
• Complexity of biological systems
• Analogies between biology and computer science
• Evolution of proteins
• Education system failures
• Inspiring a love of learning
• Interconnectedness of biological systems

What commenters say

• The analogy between DNA and computer code is imperfect, as DNA is a dynamic and self-modifying system that cannot be reduced to a simple code.
• The distinction between code and hardware in biology is not clear-cut, with RNA and proteins playing complex and interconnected roles.
• The complexity of biological systems, particularly proteins, is difficult to fully comprehend and may have evolved through a combination of top-down and bottom-up processes.
• The education system often fails to inspire a love of learning in students, particularly in subjects like biology and mathematics, which are frequently taught in a dry and abstract way.
• The idea that life can be understood through the lens of computer science is both insightful and limited, as it highlights the complexity and interconnectedness of biological systems but also oversimplifies their unique characteristics.
• The process of discovering and understanding biological systems is often a gradual and iterative one, requiring patience, curiosity, and a willingness to explore and question.
• The relationship between code, hardware, and runtime in biology is more fluid and dynamic than in computer science, with DNA, RNA, and proteins interacting and influencing one another in complex ways.