Life,information theory,and topology

The information content of an organism determines to a large extent its ability to perform the basic vital functions: selection of food, breaking up of the food molecules into appropriate parts, selection of those parts, and their assimilation. The information content needed is very large and requires a sufficiently large complexity of the organism. The information content of an organism is largely determined by the information content of the constituent organic molecules. The information content of the latter is in its turn determined by the number of physically distinguishable atoms or radicals of which the molecule is composed. The different arrangements of atoms in a molecule are represented by the structural formula, which is basically a graph. It is shown that the topology of this graph also determines to a large extent the information content. Different points of a graph may be physically indistinguishable; in general, however, they are different in regard to their topological properties. A study of the relations between the topological properties of graphs and their information content is suggested, and several theorems are demonstrated. A relation between topology and living processes is thus found also on the molecular level.     

Mapping of statistical physics to information theory with application to biological systems

The problem of achieving a mapping of formalisms in statistical physics and theoretical biology to information theory is discussed using an example for canonical ensembles. We extend the meaning of the Handscomb Monte-Carlo method to a general recipe for the transformation from a "configuration" space to a "sentence" space. The ensemble of "sentences" and its corresponding source uncertainty function are introduced. A possible mapping procedure based on a generalization of the Handscomb representation is described. For a biological illustration, we present a way to introduce a pathway representation to describe metabolic processes in living systems.     

A calculation of the probability of spontaneous biogenesis by information theory.

The Darwin-Oparin-Haldane “warm little pond” scenario for biogenesis is examined by using information theory to calculate the probability that an informational biomolecule of reasonable biochemical specificity, long enough to provide a genome for the “protobiont”, could have appeared in 10⁹ years in the primitive soup. Certain old untenable ideas have served only to confuse the solution of the problem. Negentropy is not a concept because entropy cannot be negative. The role that negentropy has played in previous discussions is replaced by “complexity” as defined in information theory. A satisfactory scenario for spontaneous biogenesis requires the generation of “complexity” not “order”. Previous calculations based on simple combinatorial analysis over estimate the number of sequences by a factor of 10⁵. The number of cytochrome c sequences is about 3·8 × 10⁶¹. The probability of selecting one such sequence at random is about 2·1 ×10^?65. The primitive milieu will contain a racemic mixture of the biological amino acids and also many analogues and non-biological amino acids. Taking into account only the effect of the racemic mixture the longest genome which could be expected with 95 % confidence in 10⁹ years corresponds to only 49 amino acid residues. This is much too short to code a living system so evolution to higher forms could not get started. Geological evidence for the “warm little pond” is missing. It is concluded that belief in currently accepted scenarios of spontaneous biogenesis is based on faith, contrary to conventional wisdom.     

Life, self-reproduction and information: beyond the machine metaphor

The problem of representing information in automation models of self-replication is considered. It is shown that, unlike in the natural reproduction process, in a computable model the reproduced entities do not contain all the information necessary for guiding the process. Current theoretical understanding of life and its replication, based on such models, is argued to be essentially inadequate. The solution to this problem is claimed to require recognition of the theoretical fact that information in living systems is different from that subsumed under the category of "knowledge", which is representable as computer programs or triggers of state transitions. A discussion of fundamentals of a new theory of information and its relationship to replication models is given and a new direction of further developments of biological theories is envisioned.     

Language evolution and information theory

This paper places models of language evolution within the framework of information theory. We study how signals become associated with meaning. If there is a probability of mistaking signals for each other, then evolution leads to an error limit: increasing the number of signals does not increase the fitness of a language beyond a certain limit. This error limit can be overcome by word formation: a linear increase of the word length leads to an exponential increase of the maximum fitness. We develop a general model of word formation and demonstrate the connection between the error limit and Shannon's noisy coding theorem.     

Life history theory and evolutionary anthropology

Life-history theory has been developed in biology to explain the variation in timing of fertility, growth, developmental rates, and death of living organisms, as well as events directly tied to these parameters. The theory is useful in explaining variations in age-specific human fertility and mortality patterns, as well as understanding how the human life course evolved to patterns so divergent from those that characterize our close primate relatives. Surprisingly, this same theory can also be used to explain why people often ignore the long-term consequences of behaviors that produce short-term gain.     

Life as physics and chemistry: A system view of biology

Cellular life can be viewed as one of many physical natural systems that extract free energy from their environments in the most efficient way, according to fundamental physical laws, and grow until limited by inherent physical constraints. Thus, it can be inferred that it is the efficiency of this process that natural selection acts upon. The consequent emphasis on metabolism, rather than replication, points to a metabolism-first origin of life with the adoption of DNA template replication as a second stage development. This order of events implies a cellular regulatory system that pre-dates the involvement of DNA and might, therefore, be based on the information acquired as peptides fold into proteins, rather than on genetic regulatory networks. Such an epigenetic cell regulatory model, the independent attractor model, has already been proposed to explain the phenomenon of radiation induced genomic instability. Here it is extended to provide an epigenetic basis for the morphological and functional diversity that evolution has yielded, based on natural selection of the most efficient free energy transduction. Empirical evidence which challenges the current genetic basis of cell and molecular biology and which supports the above proposal is discussed.     

Twin concordance: a set theoretic and probability theory approach

The concepts and assumptions used in twin concordance studies are made explicit with a mathematical treatment. The logic connecting those assumptions to the usual interpretations of twin studies is substantiated in a rigorous manner through the use of elementary set and probability theory.     

Determinism and probability in the development of the cell theory

A return to Claude Bernard's original use of the concept of 'determinism' displays the fact that natural laws were presumed to rule over all natural processes. In a more restricted sense, the term boiled down to a mere presupposition of constant determinant causes for those processes, leaving aside any particular ontological principle, even stochastic. The history of the cell theory until around 1900 was dominated by a twofold conception of determinant causes. Along a reductionist trend, cells' structures and processes were supposed to be accounted for through their analysis into detailed partial mechanisms. But a more holistic approach tended to subsume those analytic means and the mechanism involved under a program of global functional determinations. When mitotic and meiotic sequences in nuclear replication were being unveiled and that neo-Mendelian genetics was being grafted onto cytology and embryology, a conception of strict determinism at the nuclear level, principally represented by Wilhelm Roux and August Weismann, would seem to rule unilaterally over the mosaic interpretation of the cleavage of blastomeres. But, as shown by E.B. Wilson, in developmental processes there occur contingent outcomes of cell division which observations and experiments reveal. This induces the need to admit 'epigenetic' determinants and relativize the presumed 'preformation' of thedevelopmental phases by making room for an emergent order which the accidental circumstances of gene replication would trigger?on.     

Life history theory and human reproductive behavior

The purpose of this article is to develop a model of life history theory that incorporates environmental influences, contextual influences, and heritable variation. I argue that physically or psychologically stressful environments delay maturation and the onset of reproductive competence. The social context is also important, and here I concentrate on the opportunity for upward social mobility as a contextual influence that results in delaying reproduction and lowering fertility in the interest of increasing investment in children. I also review evidence that variation in life history strategies is influenced by genetic variation as well. Finally, I show that cultural shifts in the social control of sexual behavior have had differential effects on individuals predisposed to high- versus low-investment reproductive strategies.     

持变概率法与核酸序列中的信息提取

利用一种新的序列分析方法——持变概率法,对GenBank数据库中果蝇、小家鼠、人类的7310条核酸序列片断进行分析,得出：（1）核酸序列中的持变概率与持变数呈指数关系变化;（2）同一种生物同一染色体的持变指数很相近;（3）同一种生物不同染色体的持变指数有一定的差异;（4）不同种生物染色体的持变指数之间有显著差异。说明持变概率法能够提取核酸序列的特征,持变指数有助于基因的分类与识别,此方法可用于基因序列分析。