498: Statistical Physics, Biological Information and Complexity

Author: Anoush Aghajani-Talesh
Title: Dynamics of Urban Sprawl (121 kb)

Abstract:

In this essay a model for the spatial development of a contemporary city and its implementation on a computer as a cellular automat is presented.

Abstract:

Linguistics is an interesting field, in that it makes connections to a broad range of sciences, such as mathematics and the study of artificial intelligence, the social sciences (of course), and the study of complex systems in physics.  I present work suggesting that a common view of language learning is flawed.  The solution to this problem, according to many, is universal grammar.  I introduce universal grammar in basic terms, and present work that studies universal grammar as a complex system in a formal and mathematically rigorous way.

Abstract:

Biological complexity is intimately related to the amount of information in a given system. The way in which information arises and consequently how
complexity increases in biological systems is discussed. Both are consequences of the principle of natural selection introduced by Darwin.

Abstract:

It is the purpose of this review, to explore some existing models that introduce the concept of 'cooperative behavior' and 'measures' that extracts the information of the market.

Abstract:

Author:  Swarbhanu Chatterjee
Title:  Complexity and attempts to quantify it. (69 kb)

Abstract:

In this paper, I have discussed the various kinds of complexity and have described the different attempts made by scientists all over the world to
quantify it. It would be very nice if we could quantify complexity because then we would be able to compare between the levels of complexity of different
systems and study how organisms become more and more complex in the natural world due to evolution.

Abstract:

In this essay, I present a very simple numerical model for species evolution developed by Sneppen et. al. The model assumes random interactions between neighboring species. It is observed that the model quickly self-organizes into a critical state characterized by extinction events at all scales (that follow power law distributions).  The model successfully predicts the "punctuated equilibrium" observed in the history of the major mass extinctions. An interesting conclusion to the model is that catastrophic events are intrinsic to it and major external sources of mayhem (such as a meteorite) are not needed to explain major extinctions.

Author: Parag Ghosh
Title: Degeneracy in Biological Systems (76 kb)

Abstract:

Degeneracy is an ubiquitous property of biological systems where nonisomorphic elements can perform the same function. Degeneracy is distinguished from Redundancy which is the case where similar elements perform the same function. The former is particularly favored by natural selection because it contributes to robustness and the ability of the organism to adapt to its surroundings.

Abstract:

Several examples of scaling are known in biology; for example, the species-area and mass-metabolism relationships.  A new scaling law can now be added to these: a power-law relationship between the number of cells in an organ and its variance.  This power law holds over nearly twelve orders of magnitude, and has been partially explained by a simple theoretical model.

Abstract:

In this paper, I would like to provide a review on how energy is transported and converted into the universal energy currency "ATP" by five
enzyme complexes which function together in Oxidative Phosphorylation. The focus will be on the last 3 enzymes complexes (Complex III, IV and V) as
recently their structures have been solved.

Abstract:

This paper gives a simple introduction to the Conway's cellular automata referred to as the "game of life."  Since much work has been done to
discover complex patterns in the game of life, but little has been done to discover fault-tolerant ones, this paper proposes to look for more robust
patterns.

Abstract:

This essay introduces the basic properties of scale-free networks  and plausible models to explain the power-law connectivity distribution. Two
examples in biological complexity are analyzed in detail and suggestions  are made to further explore the network behavior in bilogical systems.

Abstract:

This essay reviews studies of biologically complex and chaotic behaviour in insect colonies.  It is found that although the behaviour of individuals in
the colony is simple, it leads to complex behaviour of the colony when viewed as a single entity.   Comparisons are made to human organizations and an
example from IBM is used to illustrate similarities between large corporations and insect colonies.

Abstract

Many natural systems are found to have complex behaviors that obey power laws. This is the case of the dynamics of heartbeat. In this paper, I review the
research on the fractal behavior of heartbeats and its applications to diagnosis for heart disease patients.

Abstract:

Author:    Martin Ph. Stehno
Title:  Simulations of recovery after mass extinctions (252 kb)

Abstract:

Mass extinctions played a crucial role in the evolution of species. They  disrupted some evolutionary lines and started or altered others. After a short
discussion of the impact of mass extinctions on the evolution of species, a simple model of evolution with three trophic levels will be discussed. This
model was used by Sole and Montoya (2001)  to measure the fragility of ecological networks, and to simulate the recovery of ecosystems after mass
extinction events.

Abstract

This essay discusses Ben-Jacob's work on cooperative bacterial networks. An alternative approach to Darwinian evolution is suggested, relying on
the idea of the genome as a self-aware and adaptive cybernetic unit. The concept of complexity and importance of individual genomes and
networks is presented in relation to Godel's theorem.

Abstract:

The finding that the number of genes in humans is only about 31,000 compared to that of 19000 of worms is challenging the assuption of
linearity of gene assignment and functioning and suggests a picture of genome as a complex interacting network. In this paper some approaches to
the study of such networks is presented.

Abstract:

Author: Qing-jun Wang
Title: Degeneracy, Redundancy & Complexity in Biological Systems & Their Measures (250 kb)

Abstract:

This essay introduces two distinct yet easily confused concepts in describing the complexity of biological system Ä degeneracy and redundancy. The generality of degeneracy in biological systems is explored. The measures for degeneracy and redundancy, together with the measures for integrity and complexity, are defined to quantitatively describe biological complexity. Computer simulation results are given to show the close relationship between redundancy and degeneracy, and their contributions to biological complexity.

Abstract:

This paper purpose an adjustable fitness model in phylogenetic analysis.  The model accounts for site heterogeneity among substitution rates and among
evolutionary constraints, and does not make any assumptions about which sites or characteristics of proteins are important to molecular evolution. The model
was tested and gave better result than traditional mtREV method.

Abstract:

This essay introduces a recent research, by information-theoretic definition identifing genomic complexity as the amount of information a sequence stores
about its environmentthrough and by digital evolution, suggesting that the natural selection forces genomes to behave as a natural Maxwell Demon and
within a fixed environment the genomic complexity is forced to increase.

Abstract:

The World Wide web is a ever-growing random network with some special characters. Recently research on it reveals that there are self-organization phenomenon and scale-free power law in it.  Furthermore,  it has been pointed out clusters are formed in it. All of these cannot be well explained by the original theory of random graph. A new model are proposed and proved to be correct in some cases. And a search strategy in WWW based on it has been tested.

Return to homepage