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Wetware: A Computer in Every Living Cell Paperback – March 1, 2011
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"Whilst Bray doesn''t shy away from using unfamiliar terms they are always explained in context. For a book delving into systems biology and comparing specific examples of biological processes to computational systems that''s quite a welcome surprise. . . . [The] style is elegant and very readable."--Celia Gitterman, "Chemistry World"--Celia Gitterman"Chemistry World" (12/01/2009)
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Most of the book is very readable and gives the non-expert an insight into how through diffusion cells react and signals are processed. Cases are studied and the strategies of such single celled organisms such as the ameoba are discussed in strong detail. Examples of environmental sensitivity are discussed and "intelligence" to the extent that even single cells have architecture that allow them to dynamically adapt are explored. The exploration of the single cell is the most interesting, likely because it can be studied in isolation and thus its easier to discuss a single cells properties than a multi-celled organism. The book goes through a lot of interesting material, it discusses RNA, protein structures and dynamics and neural networks. The Neural networks portion is a good overview of how they work and how they can be used in a machine setting to obtain interesting results. As the book gets into the multicelled aspect, the quality doesnt go down so much as the material can be slightly overwhelming. Despite that, the themes of the book can still be gleaned despite some of the specifics being a bit hard to follow.
One reads this book and really mavels at the complexity of the single cell. The author gives a good example at the end - the fruitfly is able to, with negligble energy, navigate efficiently, the computing power required for humans to replicate that is of a very different order of magnitute. The cell is of microscopic size but astronomical complexity and that is where one must stop in awe and appreciate the amazing depth of life. This book takes the reader on that journey. The author tries to only take what can be observed and doesnt try to fill the gaps with intelligent design. He shows how genetic programming results show that solutions to complicated problems show up unexpectedly in evolutionary settings and that is no evidence of design. I found this book to really revitalize the idea that life is truly astonishing. It is not only astonishing from the perspective of muticelled organisms and our own self awareness, but more foundationally, from the single cell and up. I highly recommend this, it should be read by all.
Another thing I liked about this book is Bray's curiosity. He takes Barbara McClintock's 1983 suggestion "To determine the extent of knowledge the cell has of itself" as a point of departure in explaining how the cell works and as a goal and goad for future scientists. How does a cell know what to do, which decision to make at any given time? As Bray shows, each cell has a lot of possible choices; there's a lot going on in the primordial soup of a cell's world. And as we come to understand how to answer those questions and others like them, what implications do the answers have, if any, on human psychology and the way we consciously and unconsciously make decisions? Bray is clear that he doesn't know, but also clear and prescient in asking the questions and encouraging others to ask. We know a great deal about cell biology but there is still much, much more to learn.
Near the end of the book, Bray quotes French writer Andre Gide: "One doesn't discover new lands without consenting to lose sight of the shore for a very long time." So true and so inspiring!
I very highly recommend this book: 5 stars.
He begins with “clever” cellular animal behavior, such as pseudopodia movement in amoebas and the feeding and hazard avoidance behaviors of protozoa. He then explains the chemical mechanisms, including “digital” protein switches that cells use to maintain state information, giving as an example the manner in which the hormone glucagon interacts with liver cells to cause them to catalyze the glucose stored in glycogen. He compares this type of signaling behavior to the logic circuitry used in semiconductors.
Indeed, Bray ranges across a wide range of AI topics, attempting to equate research in both AI and robotics, for example, to biological processes. While this is certainly appropriate, I found these discussions and digressions less convincing than the presentation of the actual results of the biological research. Eventually, Bray works his way up to the electrical signals that nerve cells in the brain process, where we see “computing” structures far more complex than anything we can currently represent in a digital computer network – although maybe Google, for one, is within hailing distance.
The book also contains a discussion of gene regulatory networks, which is an area of computational biology where microbiologists are just beginning to understand the role of “junk” DNA in gene expression. That the 98% of the human genome that was not explicitly used to encode for protein synthesis was mere “junk” accumulated in the chromosomes for no good purpose always bordered on the preposterous. It is reassuring to read about new developments in this field. As we see scientists starting to unravel these gene regulatory networks, genetic circuitry also turns out to be quite complex. In this context, Bray cites favorably some of the visionary work of Stuart Kauffman, who originally suggested there were physical mechanisms that could explain how biologically-ordered structures could emerge spontaneously from a chaotic chemical soup.
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