Raman Cajal vs Francis Crick

[Physics-Lee]

Raman Cajal once wrote

We realized that all of the various conformations of the neuron and its various components are simply morphological adaptations governed by laws of conservation for time, space, and material.

However, Francis Crick wrote

Arguments about “efficiency” are thus almost always to be mistrusted in biology since we don’t know the exact problems faced by myriads of organisms in evolution. And without knowing that, how can we decide what form of efficiency paid off?

Who do you agree with?

[Physics-Lee]

Francis Crick's Explanation:

The genetic code is a very good example of what I mean. Who could possibly invent such a complex allocation of the sixty-four triplets (see appendix B)? Surely the comma-free code (page 99) was all that a theory should be. An elegant solution based on very simple assumptions—yet completely wrong. Even so, there is a simplicity of a sort in the genetic code. The codons all have just three bases. The Morse code, by contrast, has symbols of different lengths, the shorter ones coding the more frequent letters. This allows the code to be more efficient, but such a property may have been too difficult for nature to evolve at that early time.

These sentences are from What Mad Pursuit

[Physics-Lee]

I will upload my personal opinion 1 day later.

[Yue9Shang]

我更支持Francis的观点，即使是最简单的热力学系统，我们也不能仅仅根据能量最低确定态流动方向，我们也要考虑熵（thermal的效应），因此有了自由能等概念。更何况复杂如生命系统呢。

[Physics-Lee]

My Personal Opinion

Paul Dirac's quote

Paul Dirac once said

My equation is so beautiful that it can not be wrong.

However, we all know that many beautiful models are wrong.

2 criterion

You can raise your model based on anything: efficiency, beauty, simplicity, imagination, or anything else you like. But you must go back to experiments, instead of keeping daydreaming and arguing.

There are 2 criterion to check if your model is a good/useful model.

• Explain the existing experiment phenomena well.
• Predict new experiment phenomena. The more unexpected, the better.

So, think about the models in the history of biology, which are good models and which are bad?

Good

	Model	Unexpected Experiments Results Predicted
Darwin	Nature Selection	You can force the pet to evolve different colors in very short period (30 years)
Mendel	Mendel Laws	9:3:3:1
Morgen, Bridges, Sturtevant, Muller [1]	Genes locate in chromosome	Sex-linked-inheritance (伴性遗传); linked-inheritance (连锁遗传); Crossover (交叉互换); Drosophila Atlas (果蝇图谱)[2]
Salvador Luria, Max Delbruck	Luria-Delbruck Distribution	see Here
Watson, Crick, Wilkins, Franklin	DNA Double Helix	semi conservative replication
Watson, Crick, George Gamow	Triplet code	exps of Nirenberg
Alan Hodgkin, Andrew Huxley	HH Model	You can do many things to a single neuron in vitro. [3]
Many	Cable Theory	You can do many things to axons in vitro. [3]

[1] Morgen gave his Nobel Prize money to his group, including Bridges, Sturtevant and Muller.

[2] see CH3.3 of Biological Physics by Philip Nelson

[3] For example, use $K_2SO_4$ to replace cytoplasmic matrix.

bad

• Comma-free code by Francis Crick.
• Theory of two currents in vision.

Think about Physics

In physics, there are more cases. I list a little, leaving you to supplement them. You may get bonus points for it.

	Model	Unexpected Experiments Results Predicted
Copernicus	heliocentrism	annual paralla (周年视差)
Newton	Newton 3 laws and Law of universal gravitation	Neptune
Faraday, Maxwell	Use field to replace action at a distance	electromagnetic wave
Einstein	Special Relativity	$\mu$ in the cosmic ray

Summary

All in all, efficiency, beauty, simplicity, imagination are all good ways to build a theoretical model, but, your model should not only explain current experiment results, but also predict new experiment phenomena.