Sunday, June 26, 2016

The Ignorance of Some Academics

In a recent review of the book Life’s Greatest Secret: The Race to Crack the Genetic Code by Matthew Cobb, a book I admit I have neither read nor do I have any intent to waste my time thereupon, there is however a letter to the editor of the New York Review of Books, NYRB, a generally leftist oriented opinion publication, which stated some rather revealing opinions.

In the above mentioned letter to the NYRB the author states regarding the original review[1]:

He notes that developments in mathematical information theory and cybernetics soon after World War II had a strong influence on the way biologists began to talk about life and heredity —specifically the idea that DNA contains a “genetic code” replete with “information.” Much the same point can be made about psychology and neuroscience: they too were influenced by these developments in the mathematical theory of information, introducing this notion into the heart of theories of the mind and the brain. But Orr goes on to remark:

"In the end, the information sciences provided biologists with loose but useful metaphors and analogies, a language that allowed scientists to think and speak in new ways. But the high-powered mathematics of these fields proved mostly impotent in biology [I would add in psychology and neuroscience too]. No one, for instance, used Shannon’s equations to say anything especially interesting about organisms…"
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This raises a troubling question: If these recent ways of talking in biology, psychology, and neuroscience are really just loose but useful metaphors, now deeply ingrained in these sciences, what is the literally true way of speaking for which they substitute? How can we reformulate these sciences in such a way that the information metaphors are replaced by sober statement of fact? And do scientists now agree that the borrowed way of talking really is just loose metaphor, or have they come to take it for literal truth? This question seems to me not sufficiently addressed, though very important.
Now the original Reviewer notes[2]:

A second theme concerns the respective roles of theory (of any sort) versus experiment in biology. In the early 1960s, mathematicians confidently declared that “it will be interesting to see how much of the final solution [to the coding problem] will be proposed by mathematicians before the experimentalists find it.” As Cobb concludes, the “answer. . was simple: not one single part of it.” The interesting question is why theory failed here. Part of the answer, as Cobb emphasizes, is related to Crick’s idea of the frozen accident. The genetic code seems at least partly arbitrary. It represents a half-decent arrangement arrived at by the imperfect, tinkering process of evolution by natural selection and, once settled on, it couldn’t be “improved,” or made somehow more systematic. In such a situation theory is likely useless.

Let me examine these statement a bit in detail.

First:

Let me reiterate Wiener and Cybernetics. He made basically the following observations:

1. The world is filled with uncertainty. Things are random, and we have to acknowledge and accept that.

2. Many organic entities are systems. Namely they have actuators and effectors. They have cause and effect. They are in effect a system which means we can model cause and effect, albeit under condition 1 above it may very well be random.

3. Systems have feedback elements, namely inputs yield outputs which in turn can effect inputs. That means we have systems whose dynamics are uncertain systems with dynamic effects.

In simple terms the Cybernetic world is a stochastic dynamic system. Now what about cells, DNA and their functions? They are stochastic dynamic systems. Ligands attached to receptors which activate pathways which start DNA reading via a promoter and conversion which produces RNA and then produce proteins which then become ligands. Some proteins actually modulate the pathways and receptors. Thus the dynamics of cells is a stochastic dynamic system. Almost all studies in cancer pathways revolve about that fact. Cybernetics from a Wienerian mindset is fully accepted in systems biology. It is the very heart of systems biology.

The letter writer is thus in error. The Cybernetic model is hardly a loose model. It is at the very heart of understanding cancer dynamics. It is necessary. The Reviewer, the Author and the Letter Writer are in gross error in their understanding and articulation of cybernetics.

Furthermore, as we have shown in repeated malignancies, one can view cancer as a separate dynamic stochastic organism, growing apart from the human host. Yet if one accepts such a model, then it is possible using systems approaches to use systems identification theory to identify the system and systems control theory to mitigate the threat from this organism. One misses the point in examining single cells, one must view the amalgam, albeit a heterogeneous organism genetically.

Second:

Now for Shannon. Frankly his approach is quite limited. I started teaching Information Theory at MIT more than fifty years ago, and even earlier with a Wienerian view. Shannon and Information work on communications. Frankly the very term information is a misnomer, mainly since we do not know what we mean by information from an epistemological basis so by applying this terms to data bits was cute and catchy but does it a disservice because people who fail to have any understanding of it will err in its application. Shannon was interested in signals sent over a noisy channel where there were limits in transmission capacity, say bandwidth.

He has two main theorems. The Channel Coding Theorem which says how fast or at what rate you cane transmits a signal over a channel at a rate where the channel has a capacity in say bandwidth and an interference in terms of noise. There frankly is no real "information" here. Secondly is the Source Coding Theorem which says how much you can compress some signal with excess stuff, called information. For example, we can compress voice to a few hundreds of bits, 0 and 1, per second or we can likewise do the same with video at so many thousand bits per second. The Source and Channel Coding Theorems of Shannon describe dealing with redundancy and dealing with limited capacity and noise respectively. That's it folks! It does not tell you about "information", whatever that means to someone. To Shannon it was changing a sine wave to a bunch of on and off signals. That's all folks.

So when one sees articles, letters, books like this one shudders and understands why we have so many poorly educated students. It’s the teachers stupid!

Now; do biologists use any of these approaches? Think Eric Lander and the human genome. How do you think he got to match all the broken pieces of DNA into a genome; mathematics? After all he was a trained engineer in coding, that Shannon stuff. So he may not have used the two Theorems but he did employ the ideas resulting therefrom.

Pity we have people who make these statements. But alas this is all too common.