- A long-form analogy compared cellular biochemistry to analog electronics: concentrations of chemical species behave like voltages on conductors, reactions act as n-terminal components, and the “debugger” we need is a million-channel non-invasive oscilloscope that tracks every molecular species in a vacuole rather than voltages on wires.  
- The same contributor argued that knowing protein crystal structures is overrated; what is missing for predictive biology is exhaustive, quantitative reaction-kinetics data (rate constants) for every pairwise molecular interaction, which would let us compute stable cell-type “fixed points” and simulate developmental lineages deterministically.  
- A practical route was outlined: measure concentrations in a fertilized-egg-like state, use gradient descent on the full reaction network to discover daughter cell-type attractors after each division, and iteratively map the complete tree of human cell types without further brute-force searches.  
- Magneto-thermal genetic stimulation was highlighted: TRPV1-expressing neurons in mice were remotely activated by alternating magnetic fields heating superparamagnetic nanoparticles, producing locomotion, rotation, or freezing behaviors without implanted hardware (eLife 2017 paper).  
- Additional magnetogenetics references included engineering cellular biomineralization for magnetism (Nature Sci. Rep. 2016), negative results on MagR alone for calcium responses, and a proposed electron-transfer mechanism for avian magnetoreception (arXiv 2017).  
- Links to AI acceleration research were shared: “DeepRebirth” for mobile DNN execution, “SMASH” for one-shot neural architecture search via hypernetworks, and the survey “When will AI exceed human performance?” (arXiv 1705.08807).  
- A cautionary Hacker News anecdote recounted failed catalytic-antibody work that relied on a metalloprotease domain later revealed to be part of Homme Hellinga’s fraudulent enzyme-design papers, underscoring reproducibility risks in protein engineering.  
- Discussion of software/data rot cited obsolete 454 sequencing formats as an example of how loss of tooling—not data loss—can render archived biological datasets unreadable, prompting debate on long-term software archivability.