Future readings?

Vin Gulisano had the following suggestion (on Nov. 21, 2006)

"Here's a book that would fit in with the theme of the new information theory:

"Decoding the Universe: How the New Science of Information Is Explaining Everything In The Cosmos, From Our Brains To Black Holes. -- by Charles Seife, Author of "Zero"

Form the inside jacket: " ... information is everywhere -- and it's not just an abstract concept. Information is a concrete property of matter and energy that's every bit as real as the weight of a chunk of lead, something that sits inside very living cell and is inscribed upon every cosmic phenomenon. The red hot science of information theory is today the place where biologists, physicists, and chemists are converging to break the last remaining codes of the universe."

The book has some of the most clear explanations of physical concepts, including entanglement, non-localities, and the holographic universe. And, every topic is related to information with an attempt to convince us that information can be considered another crucial dimension required to understand the universe. It has what the Vilenkin book was missing: information theory in the description of cosmology.

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A suggestion from Mark Tiede (July 20, 2007):

"When you have a chance take a look at this book, and see whether you agree it might make for a good topic:

An Introduction to Systems Biology: Design Principles of Biological Circuits by Uri Alon (2007) Chapman & Hall

From a Physics Today review by Nigel Goldenfeld: "[The book] assumes no prior knowledge of or even interest in biology. Yet right from chapter 1 the author succeeds in explaining in an intellectually exciting way what the cell does and what degrees of freedom enable it to function. [It] proceeds with detailed discussions of some of the key network motifs, circuit-element designs that are believed to be repeated over and over again in biological systems. Those motifs include autoregulation, feed-forward loops, and kinetic proofreading. The discussions in all cases introduce the particular motif, use simple differential equations in most cases as a way to model it, and offer plenty of comparisons with experimental data."