Life by the numbers

I last formally studied biology in high school.  (No clues will be given how long ago that was.) Lots of memorization. Little in the way of organizing principles. At the time, I didn't find it very interesting.

In recent years, though, I've been revisiting biology. It probably didn't hurt that two of my college physics buddies eventually got their PhDs in biophysics. And in the course of reintroducing myself to elements of modern biology, I recently read a book that reexamines cellular and molecular biology with tools very familiar to me as a a physicist and computer guy.  

The book is An Introduction to Systems Biology: Design Principles of Biological Circuits, by Uri Alon (of the Weitzman Institute).

Circuits, you ask?

Circuits, indeed. Take the process of gene transcription: which genes in which cells are activated to express which proteins.  And which cells lock into particular tissue types, and why, despite all cells in an organism having identical genetic makeup.  It all happens amid lots and lots of feedback loops, because proteins (some acting as proxies for environmental factors) influence gene expression influence proteins influence ...

The fascinating theme of this textbook is: straightforward underlying principles drive this complexity. 

Alon's book presents what any computer person will recognize as logic circuits. He shows, for example, how chemical activators and repressors and (conceptually) simple chemical "connections" drive the functioning of a cell.

Had this book only put gene transcription into this new (to me, anyway) framework, it would have been money well spent. That's only one of the book's topics. It looks at several core functions of cells, and their underlying mechanisms, and uses fundamental systems-engineering techniques to get at a very basic question -- why (for a particular function) is THIS the mechanism. 

The analysis generally finds logical reasons why a genome would have evolved in a particular way -- and discusses how and why, at a molecular level, a cellular mechanism might change as environmental conditions change. It cites experiments with bacteria environmentally influenced to test theories of if/how a certain cellular mechanism would logically evolve.

Computational biology ... neat stuff.