Stephen Wolfram, Universality and Complexity in Cellular Automata, Physica D, 10 (January 1984) 1-35
D. Farmer, T. Toffoli, S. Wolfram (editors): Preface to Cellular Automata. Cellular Automata: Proceedings of an Interdisciplinary Workshop, (North-Holland Physics Publishing, 1984), vii--xii.
S. Wolfram, Computation Theory of Cellular Automata, Communications in Mathematical Physics, 96 (November 1984) 15-57
S. Wolfram, Cellular Automaton Supercomputing, High-Speed Computing: Scientific Applications and Algorithm Design, ed. Robert B. Wilhelmson (University of Illinois Press, 1988)
Stephen Wolfram, Cellular Automata and Complexity: Collected Papers Publisher: Addison-Wesley Copyright year: 1994 ISBN: 0201627167, Paperback: ISBN 0201626640 URL: http://www.stephenwolfram.com/
Before creating Mathematica, Stephen Wolfram was well known in the scientific community for his groundbreaking work in the study of complexity and cellular automata. His work in the early 1980s has been the basis for thousands of papers in the scientific literature as well as for several popular books. This book is a collection of his original papers on cellular automata and complexity, many of which have never been published before.
All Mathematica Notebooks and Cellular Automata from A New Kind of Science
Ivars Peterson. MathTrek: Numbers of No Escape. Science News. Week of Oct. 1, 2005; Vol. 168, No. 14. Web-only. http://www.sciencenews.org/articles/20051001/mathtrek.asp Playful iterative processes can get you stuck in mathemagical black holes. Certain number games lead to stable attractors like class 2 cellular automata.
John L. Casti. Confronting Science's Logical Limits. Scientific American October 1996, 102-105.
Erica Klarreich. Navigating Celestial Currents: Math leads spacecraft on joy rides through the solar system. Science News, Vol. 167, No. 16, April 16, 2005, p. 250-252. Mathematicians are creating an atlas of solar system highways along which spacecraft can coast using no fuel. Chaotic math reveals 5 Lagrange points, L1-L3 are unstable, L4 and L5 are stable.
Sid Perkins. Global Vineyard: Can technology take on a warming climate? Science News, Vol. 165, No. 22, May 29, 2004, p. 347. Modeling global warming and modeling soil effect on grapes improves the quality of wine.
Erica Klarreich. Generous Players: Game theory explores the Golden Rule's place in biology. Science News, Vol. 166, No. 4, July 24, 2004, p. 58.
Christen Brownlee. Unhealthy Change: Diversity in a bacterial colony can prolong infections. Science News, Vol. 166, No. 21, Nov. 20, 2004, p. 324.
Bruce Bower. One-Celled Socialites: Bacteria mix and mingle with microscopic fervor. Science News, Vol. 166, No. 21, Nov. 20, 2004, p. 330.
Nathan Seppa. Staph receptor as drug target. Science News, Vol. 166, No. 21, Nov. 20, 2004, p. 332.
Cooperation in Active SETI (for Active SETI Working Group)
Robert Axelrod The Evolution of Cooperation booklet
RICK L. RIOLO, MICHAEL D. COHEN & ROBERT AXELROD. Evolution of cooperation without reciprocity. Nature 414, 441 - 443 (22 November 2001); doi:10.1038/35106555.
A long-standing problem in biological and social sciences is to understand the conditions required for the emergence and maintenance of cooperation in evolving populations. For many situations, kin selection1 is an adequate explanation, although kin-recognition may still be a problem. Explanations of cooperation between non-kin include continuing interactions that provide a shadow of the future (that is, the expectation of an ongoing relationship) that can sustain reciprocity2-4, possibly supported by mechanisms to bias interactions such as embedding the agents in a two-dimensional space4-6 or other context-preserving networks7. Another explanation, indirect reciprocity8, applies when benevolence to one agent increases the chance of receiving help from others. Here we use computer simulations to show that cooperation can arise when agents donate to others who are sufficiently similar to themselves in some arbitrary characteristic. Such a characteristic, or 'tag', can be a marking, display, or other observable trait. Tag-based donation can leadto the emergence of cooperation among agents who have only rudimentary ability to detect environmental signals and, unlike models of direct3, 4 or indirect reciprocity9, 10, no memory of past encounters is required.
Axelrod, Robert; Dion, Douglas. The Further Evolution of Cooperation, Science, Volume 242, Issue 4884, pp. 1385-1390
Axelrod's model of the evolution of cooperation was based on the iterated Prisoner's Dilemma. Empirical work following this approach has helped establish the prevalence of cooperation based on reciprocity. Theoretical work has led to a deeper understanding of the role of other factors in the evolution of cooperation: the number of players, the range of possible choices, variation in the payoff structure, noise, the shadow of the future, population dynamics, and population structure.
Erica Klarreich. Generous Players: Game theory explores the Golden Rule's place in biology. Science News, Vol. 166, No. 4, July 24, 2004, p. 58.
Peter D. Taylor and Troy Day. Cooperate with thy neighbour? NATURE, VOL 428, 8 APRIL 2004,611-612.
What gives cooperation an evolutionary edge? Two features of a population - spatial structure and finite size - are factors in the success of any strategy, although more subtle than we thought.
Martin A. Nowak, Akira Sasaki, Christine Taylor and Drew Fudenberg. Emergence of cooperation and evolutionary stability in finite populations. NATURE, VOL 428, 8 APRIL 2004, 646-650.
To explain the evolution of cooperation by natural selection has been a major goal of biologists since Darwin. Cooperators help others at a cost to themselves, while defectors receive the benefits of altruism without providing any help in return. The standard game dynamical formulation is the 'Prisoner's Dilemma', in which two players have a choice between cooperation and defection. In the repeated game, cooperators using direct reciprocity cannot be exploited by defectors, but it is unclear how such cooperators can arise in the first place. In general, defectors are stable against invasion by cooperators. This understanding is based on traditional concepts of evolutionary stability and dynamics in infinite populations. Here we study evolutionary game dynamics in finite populations. We show that a single cooperator using a strategy like ‘tit-for-tat’ can invade a population of defectors with a probability that corresponds to a net selective advantage. We specify the conditions required for natural selection to favour the emergence of cooperation and define evolutionary stability in finite populations.
Hauert, C., and M. Doebeli. 2004. Spatial structure often inhibits the evolution of cooperation in the snowdrift game. Nature 428(April 8):643-646.
Understanding the emergence of cooperation is a fundamental problem in evolutionary biology. Evolutionary game theory has become a powerful framework with which to investigate this problem. Two simple games have attracted most attention in theoretical and experimental studies: the Prisoner's Dilemma and the snowdrift game (also known as the hawk-dove or chicken game). In the Prisoner's Dilemma, the non-cooperative state is evolutionarily stable, which has inspired numerous investigations of suitable extensions that enable cooperative behaviour to persist. In particular, on the basis of spatial extensions of the Prisoner's Dilemma, it is widely accepted that spatial structure promotes the evolution of cooperation. Here we show that no such general predictions can be made for the effects of spatial structure in the snowdrift game. In unstructured snowdrift games, intermediate levels of cooperation persist. Unexpectedly, spatial structure reduces the proportion of cooperators for a wide range of parameters. In particular,spatial structure eliminates cooperation if the cost-to-benefit ratio of cooperation is high. Our results caution against the common belief that spatial structure is necessarily beneficial for cooperative behaviour.
Doebeli, M., C. Hauert, and T. Killingback. 2004. The evolutionary origin of cooperators and defectors. Science 306(Oct. 29):859-862.
Erica Klarreich. When Laziness Pays: Math explains how cooperation and cheating evolve. Science News, Vol. 167, No. 3, Jan. 15, 2005, p. 35.
Anenomes learn to recognize competitors and attack them. Part of evolving cooperation rests on improving recognition abilities.
Christen Brownlee. The Sum of the Parts: Synthetic biologists string genes into living machines. Science News, Vol. 168, No. 24, Dec. 10, 2005, p. 378. http://www.sciencenews.org/articles/20051210/bob9.asp Some researchers are breaking genomes into a collection of parts and precisely reassembling them to do a scientist's bidding.
How long does a Virtual Mouse have to live? Erica Klarreich. Life on the Scales: Simple mathematical relationships underpin much of biology and ecology. Science News, Vol. 167, No. 7, Feb. 12, 2005, p. 106.
A mathematical equation helps explain life processes
on all biological scales, from molecules to ecosystems.
Brown, J.H., J.F. Gillooly, A.P. Allen, V.M. Savage, and G.B. West. T. Toward a metabolic theory of ecology. Ecology, 85(7), 2004, pp. 1771-1789
Lauretta M.S. Chan, Simon Lowes, Barry H. Hirst, The ABCs of drug transport in intestine and liver: efflux proteins limiting drug absorption and bioavailability, European Journal of Pharmaceutical Sciences 21 (2004) 25-51.
Many orally administered drugs must overcome several barriers before reaching their target site. The first major obstacle to cross is the intestinal epithelium. Although lipophilic compounds may readily diffuse across the apical plasma membrane, their subsequent passage across the basolateral membrane and into blood is by no means guaranteed. Efflux proteins located at the apical membrane, which include P-glycoprotein (Pgp; MDR1) and MRP2, may drive compounds from inside the cell back into the intestinal lumen, preventing their absorption into blood. Drugs may also be modified by intracellular phase I and phase II metabolising enzymes. This process may not only render the drug ineffective, but it may also produce metabolites that are themselves substrates for Pgp and/or MRP2. Drugs that reach the blood are then passed to the liver, where they are subject to further metabolism and biliary excretion, often by a similar system of ATP-binding cassette (ABC) transporters and enzymes to that present in the intestine. Thus a synergistic relationship exists between intestinal drug metabolising enzymes and apical efflux transporters, a partnership that proves to be a critical determinant of oral bioavailability. The effectiveness of this system is optimised through dynamic regulation of transporter and enzyme expression; tissues have a remarkable capacity to regulate the amounts of protein both at transcriptional and post-transcriptional levels in order to maintain homeostasis. This review addresses the progress to date on what is known about the role and regulation of drug efflux mechanisms in the intestine and liver.
Henry Gee. A journey into the genome: what's there. Nature. Published online: 12 February 2001; | doi:10.1038/news010215-3. http://news.nature.com//news/2001/010215/010215-3.html