Discussion Overview
The discussion centers on the theoretical computational complexity of simulating an embryo at a full-atom scale from conception to adulthood. Participants explore the feasibility, challenges, and implications of such simulations, touching on aspects of molecular dynamics, computational power, and biological processes.
Discussion Character
- Exploratory
- Technical explanation
- Debate/contested
Main Points Raised
- One participant estimates that an average human contains approximately 7e27 atoms and questions the computational requirements for simulating such a system over decades.
- Another participant notes that simulating a single cell from conception to adulthood would require immense computational power, far beyond current capabilities, and emphasizes the complexity of biological processes.
- Discussion includes the challenges of simulating protein folding and the need for accurate environmental modeling, with one participant expressing skepticism about the practicality of such simulations.
- Participants mention the current capabilities of supercomputers, comparing them to the theoretical requirements for full-body simulations and highlighting the exponential increase in computational needs with added variables.
- One participant references the Folding@home project, which simulates small proteins and discusses the time required for simulations, emphasizing the need for statistical analysis of multiple runs to ensure reliability.
- Another participant raises the concept of the maternal effect, indicating that developmental instructions are not solely encoded in the embryo's DNA, but also influenced by maternal gene products, complicating the simulation further.
Areas of Agreement / Disagreement
Participants express a general consensus on the immense challenges and current impracticality of simulating a full human life cycle at the atomic level, but there are differing views on the potential usefulness of such simulations and the implications of simulating life.
Contextual Notes
Limitations include the current understanding of biological processes, the dependence on accurate environmental modeling, and the unresolved complexities of simulating interactions between cells and their surroundings.