Complexity, Universality, Self-Similarity and Growth of Genomes

Our recent textual analysis of all extant complete genomes shows that in spite of the high complexity and divergence of genomes, the statistical property of the word frequencies in complete genomes exhibit an unequivocal universality. Moreover, each individual genome is highly complex and at the same time highly self-similar. These properties strongly constrain the way genomes grew and evolved. We show that a simple, biologically viable growth model with three universal parameters can account for all the genomic properties mentioned above. The main proportions of the model are that maximally stochastic segmental duplication was the main mechanism driving early genome growth, and that the duplication process most likely began when the genomes were smaller than 300 base pairs long. The model provides a natural explanation of many biological phenomena of genomes not related to word frequency. We discuss implications of our model in the context of genome evolution, the astonishing rapid accumulation of information by the genome, and the universal ancestor.

Order Through Disorder - The Unexpected Side of Entropy

The Second Law of Thermodynamics is often explained as: ìThe disorder of a closed system never decreasesî. However, in my lecture I will show examples of systems that order spontaneously in a closed system ñ yet obey the Second Law of Thermodynamics. I will also show other examples of unexpected entropic effects and I will explain that existence of liquids is an accident.

Open Problems in Evolutionary Biology

Modeling of Protein\'s Backbone

First, we discuss various models of protein backbone and then a new model is introduced by inclusion of all key atoms of the protein backbone in the Freely Rotating Chain model. This model has more details than Freely Rotating Chain (FRC), but less than Four bead model. The model is used to study the stretching of proteins in the entropic regime and we observed that the results of our Monte Carlo simulations fitted well the experiments which suggest that the force extension plot is universal and does not depend on the side chains or primary structure of proteins.

Coarse-Graining, Symbolic Description and Complexity

Coarse-grained description of Nature inevitably leads to the use of symbols and symbolic sequences. The latter open the possibility of invoking some well-established notions and methods from formal language theory to the study of complexity. We will show how this approach works on a few examples from dynamical systems and biological sequence analysis without using much mathematics.

Biology-Inspired Physics - Historical and Future Perspectives

Biology and Physics share common ancestors. The two sciences have drafted apart during the last century although they have often mutually fertilized each other. Often the discovery of a new physical method has triggered dramatic progresses in biology. However, there are also numerous examples of biology-inspired new physics. In my introductory lecture various facets and new developments of the interface between physics and biology are pointed out.

Einsteinís Greatest Achievement ñ Brownian Motion and Atomic Reality

Interesting Surprise: The Interesting Part of a Quantum System

Classical processes are often described in terms of the order and disorder they produce. Entropy is a typical measure of disorder. An information theoric perspective allows for additional characterization in terms of information storage and processing. Only surprise makes a system interesting. How about the quantum world? Are interesting surprises possible? I will give an introduction into the kind of order and disorder a quantum dynamical system can produce. An information theoretic perspective allows one to characterize a quantum dynamical system in terms of the information it can store and process. This is a measure of interesting surprise produced by a system. This conceptual frame work is taken to give an outlook on quantum systems of biological importance.

Genetic Algorithms and Hidden Order

The contemplation in natural science of a wider domain than the actual leads to a far better understanding of the actual. - A. S. Eddington

Complex adaptive systems (cas) consist of many components (agents) that interact in conditional (nonlinear) ways and adapt (learn) as they interact. Many of our most difficult problems center on cas: markets, biological cells, and ecosystems are familiar examples. Innovation and diversity are common, important features of these systems. Though networks are a natural representation of the interactions in cas, the nonlinearities are severe enough that most theorems of traditional mathematics are of limited help.

Despite the mathematical difficulties, there are regularities and a hidden order in cas that can be revealed by careful study. To acquire this insight, we must concentrate on the "building blocks" (standard components) from which the agents are constructed. It is a commonplace that we understand the world around us - be it proteins, spacecraft, or languages - by discovering the relevant building blocks. It is easily established that most innovation comes from combining well-known building blocks in new ways. To understand cas, then, we must understand the ways in which adaptation (learning) recombines building blocks.

Genetic Algorithms (GA\'s) produce adaptations through the simultaneous discovery and recombination of large numbers of building blocks. This lecture will outline the background and mathematics underpinning the construction of mathematical and computer-based models of cas, concentrating on GAís and associated analytic techniques.

[Background for these lectures can be found in the book HIDDEN ORDER, which is available in Chinese translation from the Shanghai Scientific and Technological Education Publishing House.]

One Thousand and One (1001) States of Matter: Smart Materials in the 21st Century

Contrary to the common belief, there are many strange and fascinating states of matter beside the gas, liquid and solid that we all know. In this lecture, after reviewing the properties of the three well-known phases, I will answer the following questions:

• What are these novel states of matter and their fascinating phases?
• In what they differ from the usual gas, liquid and solid?
• What is the new physics and basic science associated with these phases?
• Why isn\'t there here a contradiction to fundamental physical laws?
• Why are they useful and what are their applications?

The lectured will include a large number of demonstrations, and does not require any prior knowledge of physics above high school.

Final lecture "Soft Matter and Biophysics" and Roundtable discussion

An Integrative Model for the Scaling of Tumor Energetics and Growth

We derive a general model for vascular tumor growth, based on an analysis of resource use and distribution within a solid tumor. The model integrates diverse aspects of tumor pathology, from properties of the vascular system to cellular metabolic rate, and explains the origin of sigmoidal neoplastic growth. Our model allows for the quantitative comparison of the growth and metabolic characteristics of different tumors and normal tissue. Furthermore, we predict how the interaction of the tumor and host vascular system determines the scaling of growth rates and time scales with host size across species.

New Archaeological Research on the Rise of Civilizations

Between 6000 and 3000 years ago, human civilizations developed independently in at least six different areas of our planet: The Nile Valley, Mesopotamia, The Indus Valley, The central plain of China, Mexico, and Peru.

New research shows that these developments were polycentric, not monocentric; were eposidic and experimental, not gradual and determinate; and were products not a few key variable, but of many interacting variables. Research in Mesopotamia and China will be used as examples of recent breakthroughs.

From Simplicity to Complexity: Size, Scale, and Fractals from the Big Bang to Life

Considerations of size and scale play a central role across the entire spectrum of science and technology from practical problems of medicine and engineering to some of the most fundamental conceptual questions of physics and biology. Scaling laws typically reflect fundamental principles underlying the structure of a physical problem often revealing a hidden simplicity underlying the more visible complexity. This will be illustrated by considering the role of scaling in some fundamental problems in physics and biology that have their origins in hierarchical fractal-like structures. Is an elephant just a blown up mouse? What do we mean by scaling and what is a fractal? Examples discussed and questions addressed will include: Limits to Growth, the Speed of Dinosaurs, Drug Dosages, Cooking Turkeys, Metabolic Rate, Aging and Mortality, Cancer, Sleep, Universal Biological Time, Urban Growth, and the Unification of the Fundamental Forces of Nature and the Evolution of the Universe.