Information processing in social insect networks

Investigating local-scale interactions within a network makes it possible to test hypotheses about the mechanisms of global network connectivity and to ask whether there are general rules underlying network function across systems. Here we use motif analysis to determine whether the interactions within social insect colonies resemble the patterns exhibited by other animal associations or if they exhibit characteristics of biological regulatory systems. Colonies exhibit a predominance of feed-forward interaction motifs, in contrast to the densely interconnected clique patterns that characterize human interaction and animal social networks. The regulatory motif signature supports the hypothesis that social insect colonies are shaped by selection for network patterns that integrate colony functionality at the group rather than individual level, and demonstrates the utility of this approach for analysis of selection effects on complex systems across biological levels of organization.     

Role of Utility and Inference in the Evolution of Functional Information

Functional information means an encoded network of functions in living organisms from molecular signaling pathways to an organism’s behavior. It is represented by two components: code and an interpretation system, which together form a self-sustaining semantic closure. Semantic closure allows some freedom between components because small variations of the code are still interpretable. The interpretation system consists of inference rules that control the correspondence between the code and the function (phenotype) and determines the shape of the fitness landscape. The utility factor operates at multiple time scales: short-term selection drives evolution towards higher survival and reproduction rate within a given fitness landscape, and long-term selection favors those fitness landscapes that support adaptability and lead to evolutionary expansion of certain lineages. Inference rules make short-term selection possible by shaping the fitness landscape and defining possible directions of evolution, but they are under control of the long-term selection of lineages. Communication normally occurs within a set of agents with compatible interpretation systems, which I call communication system. Functional information cannot be directly transferred between communication systems with incompatible inference rules. Each biological species is a genetic communication system that carries unique functional information together with inference rules that determine evolutionary directions and constraints. This view of the relation between utility and inference can resolve the conflict between realism/positivism and pragmatism. Realism overemphasizes the role of inference in evolution of human knowledge because it assumes that logic is embedded in reality. Pragmatism substitutes usefulness for truth and therefore ignores the advantage of inference. The proposed concept of evolutionary pragmatism rejects the idea that logic is embedded in reality; instead, inference rules are constructed within each communication system to represent reality, and they evolve towards higher adaptability on a long time scale.     

Entropy and information in evolving biological systems

Integrating concepts of maintenance and of origins is essential to explaining biological diversity. The unified theory of evolution attempts to find a common theme linking production rules inherent in biological systems, explaining the origin of biological order as a manifestation of the flow of energy and the flow of information on various spatial and temporal scales, with the recognition that natural selection is an evolutionarily relevant process. Biological systems persist in space and time by transfor ming energy from one state to another in a manner that generates structures which allows the system to continue to persist. Two classes of energetic transformations allow this; heat-generating transformations, resulting in a net loss of energy from the system, and conservative transformations, changing unusable energy into states that can be stored and used subsequently. All conservative transformations in biological systems are coupled with heat-generating transformations; hence, inherent biological production, or genealogical proesses, is positively entropic. There is a self-organizing phenomenology common to genealogical phenomena, which imparts an arrow of time to biological systems. Natural selection, which by itself is time-reversible, contributes to the organization of the self-organized genealogical trajectories. The interplay of genealogical (diversity-promoting) and selective (diversity-limiting) processes produces biological order to which the primary contribution is genealogical history. Dynamic changes occuring on times scales shorter than speciation rates are microevolutionary; those occuring on time scales longer than speciation rates are macroevolutionary. Macroevolutionary processes are neither redicible to, nor autonomous from, microevolutionary processes.Authorship alphabetical     

Mining Rare Associations between Biological Ontologies

The constantly increasing volume and complexity of available biological data requires new methods for their management and analysis. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining cross and intra-ontology pairwise generalized association rules. Its advantage is sensitivity to rare associations, for these are important for biologists. We propose a new class of interestingness measures designed for hierarchically organized rules. These measures allow one to select the most important rules and to take into account rare cases. They favor rules with an actual interestingness value that exceeds the expected value. The latter is calculated taking into account the parent rule. We demonstrate this approach by applying it to the analysis of data from Gene Ontology and GPCR databases. Our objective is to discover interesting relations between two different ontologies or parts of a single ontology. The association rules that are thus discovered can provide the user with new knowledge about underlying biological processes or help improve annotation consistency. The obtained results show that produced rules represent meaningful and quite reliable associations.     

Variable selection and pattern recognition with gene expression data generated by the microarray technology

Lack of adequate statistical methods for the analysis of microarray data remains the most critical deterrent to uncovering the true potential of these promising techniques in basic and translational biological studies. The popular practice of drawing important biological conclusions from just one replicate (slide) should be discouraged. In this paper, we discuss some modern trends in statistical analysis of microarray data with a special focus on statistical classification (pattern recognition) and variable selection. In addressing these issues we consider the utility of some distances between random vectors and their nonparametric estimates obtained from gene expression data. Performance of the proposed distances is tested by computer simulations and analysis of gene expression data on two different types of human leukemia. In experimental settings, the error rate is estimated by cross-validation, while a control sample is generated in computer simulation experiments aimed at testing the proposed gene selection procedures and associated classification rules.     

Simulated evolution of selfish herd behavior

Single species aggregations are a commonly observed phenomenon. One potential explanation for these aggregations is provided by the selfish herd hypothesis, which states that aggregations result from individual efforts to reduce personnel predation risk at the expense of group-mates. Not all movement rules based on the selfish herd hypothesis are consistent with observed animal behavior. Previous work has shown that herd-like aggregations are not generated by movement rules limited to local interactions between nearest neighbors. Instead, rules generating realistic herds appear to require delocalized interactions. To date, it has been an open question whether or not the necessary delocalization can emerge from local interactions under natural selection. To address this question, we study an individual-based model with a single quantitative genetic trait that controls the influence of neighbors as a function of distance. The results indicate that predation-based selection can increase the influence of distant neighbors relative to near neighbors. Our results lend support for the idea that selfish herd behavior can arise from localized movement rules under natural selection.     

Principles of a new biological theory: A summary

This is a review of the present state of the author's efforts, extending over many years, to construct a formal biological theory that is entirely compatible with quantum mechanics. We point out that the correspondence between detailed realizations on the molecular level and the characteristics of a class or organisms is exceedingly multivalued with respect to the former. Biological theory deals with the process of selection of actual biological states among the very large manifold of possible ones. This may also be expressed by saying that biological theory deals with (biologically) necessary conditions but not with sufficient ones. Conditions that are both necessary and sufficient pertain to physical science (molecular biology). In conformity with a well-known theorem of von Neumann, the selective process (being partly non-mechanistic) is not assumed controlled by simple mathematical rules. The selection from a very large reservoir of possible states is here described as creativity of the organism. The ordinary process of hereditary reproduction may then be represented as creativity with constraints, where the constraints (partly non-mechanistic but compatible with quantum mechanics) are such that the progeny tends to resemble the progenitors. This scheme differs from the usual view of heredity as purely mechanistic molecular replication with possible small errors. In the new scheme a gene appears as an operative symbol which functions as the releaser of a creative process.     

On a Mixed-Type Randomized Rule for Selecting Superior Binomial Models

We propose a new class of selection rules for selecting superior models from finite Binomial models. This new class of rules extends the classes of classical rules and shows its superiority to the classical selection rules by some Monte Carlo results. This new class of rules is easier and more flexible to apply than these known classical rules.     

Bergmann’s Rule,Adaptation, and Thermoregulation in Arctic Animals: Conflicting Perspectives from Physiology,Evolutionary Biology,and Physical Anthropology After World War II

Bergmann’s rule and Allen’s rule played important roles in mid-twentieth century discussions of adaptation, variation, and geographical distribution. Although inherited from the nineteenth-century natural history tradition these rules gained significance during the consolidation of the modern synthesis as evolutionary theorists focused attention on populations as units of evolution. For systematists, the rules provided a compelling rationale for identifying geographical races or subspecies, a function that was also picked up by some physical anthropologists. More generally, the rules provided strong evidence for adaptation by natural selection. Supporters of the rules tacitly, or often explicitly, assumed that the clines described by the rules reflected adaptations for thermoregulation. This assumption was challenged by the physiologists Laurence Irving and Per Scholander based on their arctic research conducted after World War II. Their critique spurred a controversy played out in a series of articles in Evolution, in Ernst Mayr’s Animal Species and Evolution, and in the writings of other prominent evolutionary biologists and physical anthropologists. Considering this episode highlights the complexity and ambiguity of important biological concepts such as adaptation, homeostasis, and self-regulation. It also demonstrates how different disciplinary orientations and styles of scientific research influenced evolutionary explanations, and the consequent difficulties of constructing a truly synthetic evolutionary biology in the decades immediately following World War II.     

Dissimilarity Maximization Method for Real-time Routing of Parts in Random Flexible Manufacturing Systems

This paper presents a dissimilarity maximization method (DMM) for real-time routing selection and compares it via simulation with typical priority rules commonly used in scheduling and control of flexible manufacturing systems (FMSs). DMM aims to reduce the congestion in the system by selecting a routing for each part among its alternative routings such that the overall dissimilarity among the selected routings is maximized. In order to evaluate the performance of DMM, a random FMS, where the product mix is not known prior to production and off-line scheduling is not possible, is selected for the simulation study. A software environment that consists of a computer simulation model, which mimics a physical system, a C++ module, and a linear program solver is used to implement the DMM concept. In addition to DMM, the simulation study uses two priority rules for routing (i.e., machine) selection and seven priority rules for selecting parts awaiting service at machine buffers. The results show (1) DMM outperforms the other two routing selection rules on production rate regardless of the part selection rule used, and (2) its performance is highly dependent on the part selection rules it is combined with.     

Data-oriented analyses of ciliate foraging behaviors

Optimal foraging theory states that natural selection makes foragers efficient food harvesters and maximizing a colony’s energy intake. This study presumed that the ciliates foraging trajectories follow optimal foraging theory, verified the presumption and discover specific rules and patterns hidden in the ciliate’s trajectories data using methodologies of statistical, cluster analyses, and decision tree analysis. This study examined the foraging behaviors of ciliates by video recordings and quantitative analyses of movement trajectories under four nourishment conditions (low, medium, high, and highest concentrations). Similar biological studies adopt statistical analyses to certain locomotion indices to determine the responses of plankton to various aquatic environments. In addition to statistical analyses, cluster analysis was used in this study to confirm the observations of the statistical analyses. The statistical analysis and cluster analysis results in this study revealed two distinct groups of trajectories or behaviors, which matched the optimal foraging theory. Decision tree analysis was then applied to acquire objective information regarding foraging behaviors, and further detailed the foraging behaviors with explicit classification rules using locomotion indices. The production rules can play an alternative role to assess the sustainability of an aquatic environment in terms of algae concentration.     

On the Emergence of Biological Complexity: Life as a Kinetic State of Matter

A kinetic model that attempts to further clarify the nature of biological complexification is presented. Its essence: reactions of replicating systems and those of regular chemical systems follow different selection rules leading to different patterns of chemical behavior. For regular chemical systems selection is fundamentally thermodynamic, whereas for replicating chemical systems selection is effectively kinetic. Building on an extension of the kinetic stability concept it is shown that complex replicators tend to be kinetically more stable than simple ones, leading to an on-going process of kinetically-directed complexification. The high kinetic stability of simple replicating assemblies such as phages, compared to the low kinetic stability of the assembly components, illustrates the complexification principle. The analysis suggests that living systems constitute a kinetic state of matter, as opposed to the traditional thermodynamic states that dominate the inanimate world, and reaffirms our view that life is a particular manifestation of replicative chemistry.     

Bifurcations of nonlinear reaction-diffusion systems in prolate spheroids

Spontaneous pattern formation may arise in biological systems as primary and secondary bifurcations to nonlinear parabolic partial differential equations describing chemical reaction-diffusion systems subject to zero flux boundary conditions. Prepatterns are investigated, which arise in the three dimensional region of a prolate spheroid (elongated sphere). Pattern sequences and selection rules are established numerically. The results confirm previously recorded results of the spherical region upon which a prepattern theory of mitosis and cytokinesis is based. New results described here establish the emerging patterns as reliable prepatterns ensuring bipolarity during elongation of biological cells, as seen in anaphase of the process of mitosis.     

The Recognition Signal Hypothesis for the Adaptive Evolution of Religion

Recent research on the evolution of religion has focused on whether religion is an unselected by-product of evolutionary processes or if it is instead an adaptation by natural selection. Adaptive hypotheses for religion include direct fitness benefits from improved health and indirect fitness benefits mediated by costly signals and/or cultural group selection. Herein, I propose that religious denominations achieve indirect fitness gains for members through the use of ecologically arbitrary beliefs, rituals, and moral rules that function as recognition markers of cultural inheritance analogous to kin and species recognition of genetic inheritance in biology. This recognition signal hypotheses could act in concert with either costly signaling or cultural group selection to produce evolutionarily altruistic behaviors within denominations. Using a cultural phylogenetic analysis, I show that a large set of religious behaviors among extant Christian denominations supports the prediction of the recognition signal hypothesis that characters change more frequently near historical schisms. By incorporating demographic data into the model, I show that more-distinctive denominations, as measured through dissimilar characteristics, appear to be protected from intrusion by nonmembers in mixed-denomination households, and that they may be experiencing greater biological growth of their populations even in the present day.     

Evolution as resistance to entropy. I. Mechanisms of species homeostasis

The idea is discussed that the common output of any evolution is creation of the entities that are increasingly resistant to further evolution. The moving force of evolution is entropy, the tendency to disorder. This general aspiration for chaos is a cause of the mortality of organisms and species, however, being prerequisite for any movement, it creates (by chance) novelties, which may occur (by chance) more resistant to further decay and thus survive. The surviving of those who survive is the most general principle of evolution discovered by Darwin for particular case of biological evolution. The second law of thermodynamics states that our Universe is perishing but its ontology is such that it creates resistance to destruction. The evolution is a history of this resistance. Not only those who die do not survive but also those who evolve. The entities that change (evolve) rapidly disappear rapidly and by this reason they are not observed among both the fossils and now-living organisms. We know only about long-living species. All the existing organisms are endowed with an ability to resist other changing. The following main achievements of the species homeostasis are discussed: high fidelity of DNA replication and effective mechanisms of DNA repair; diploidy; normalizing selection; truncated selection; heterozygote superiority; ability to change phenotype adaptively without changing genotype; parental care and the K-strategy of reproduction; behavior that provides independence of the environment. The global resistance of the living systems to entropy is provided the state that all the essential in biology is determined not by physical-chemical interactions but could semantic rules. A conception of "potential zygotic information" that determines the rules of ontogenesis is proposed. A zygote does not contain this information in explicit form. It is created de novo step by step during ontogenesis and it could not be decoded beforehand. The experimental data on the adaptive mutagenesis and the relevant hypothesis are discussed. It is concluded that the special mechanisms for speeding-up of evolution as created by evolution are impossible conceptually.     

Human evolution: humanistic selection and looking to the future

Cultural evolution has predominated over biological evolution in modern man (Homo sapiens sapiens). Cultural evolution differs from biological evolution not only by inheritance of acquired characteristics but also, as is proposed in the present essay, by another kind of selection mechanism. Whereas selection in biological evolution is executed according to a criterion of reproductive success (the natural selection), selection in cultural evolution appears to be carried out according to human and humanistic criteria (success or fitness in meeting human needs, interests and humanistic values--"humanistic selection"). Many humanistic needs or values do not seem to be prerequisite for reproductive success, yet some of them (e.g. a need for freedom) seem to be inborn. Innateness, humanistic selection (decisive at a community level) and hierarchy of some human needs, interests and values appear to give cultural evolution a generally upward trend although long periods of stagnation or even regression may occur. Modern humans appear to be still at the early stage of their cultural evolution. A further cultural evolution of man appears to be, in contrast to biological evolution, predictable (with an optimistic outlook) and testable. The problem is that the hopeful result of this test will probably be known only in the fairly remote future provided that this species will not become extinct before that.     

Darwinian aesthetics: sexual selection and the biology of beauty

Current theoretical and empirical findings suggest that mate preferences are mainly cued on visual, vocal and chemical cues that reveal health including developmental health. Beautiful and irresistible features have evolved numerous times in plants and animals due to sexual selection, and such preferences and beauty standards provide evidence for the claim that human beauty and obsession with bodily beauty are mirrored in analogous traits and tendencies throughout the plant and animal kingdoms. Human beauty standards reflect our evolutionary distant and recent past and emphasize the role of health assessment in mate choice as reflected by analyses of the attractiveness of visual characters of the face and the body, but also of vocal and olfactory signals. Although beauty standards may vary between cultures and between times, we show in this review that the underlying selection pressures, which shaped the standards, are the same. Moreover we show that it is not the content of the standards that show evidence of convergence--it is the rules or how we construct beauty ideals that have universalities across cultures. These findings have implications for medical, social and biological sciences.     

Non-natural nucleotides as probes for the mechanism and fidelity of DNA polymerases

DNA is a remarkable macromolecule that functions primarily as the carrier of the genetic information of organisms ranging from viruses to bacteria to eukaryotes. The ability of DNA polymerases to efficiently and accurately replicate genetic material represents one of the most fundamental yet complex biological processes found in nature. The central dogma of DNA polymerization is that the efficiency and fidelity of this biological process is dependent upon proper hydrogen-bonding interactions between an incoming nucleotide and its templating partner. However, the foundation of this dogma has been recently challenged by the demonstration that DNA polymerases can effectively and, in some cases, selectively incorporate non-natural nucleotides lacking classic hydrogen-bonding capabilities into DNA. In this review, we describe the results of several laboratories that have employed a variety of non-natural nucleotide analogs to decipher the molecular mechanism of DNA polymerization. The use of various non-natural nucleotides has lead to the development of several different models that can explain how efficient DNA synthesis can occur in the absence of hydrogen-bonding interactions. These models include the influence of steric fit and shape complementarity, hydrophobicity and solvation energies, base-stacking capabilities, and negative selection as alternatives to rules invoking simple recognition of hydrogen-bonding patterns. Discussions are also provided regarding how the kinetics of primer extension and exonuclease proofreading activities associated with high-fidelity DNA polymerases are influenced by the absence of hydrogen-bonding functional groups exhibited by non-natural nucleotides.     

General Rules for Optimal Codon Choice

Different synonymous codons are favored by natural selection for translation efficiency and accuracy in different organisms. The rules governing the identities of favored codons in different organisms remain obscure. In fact, it is not known whether such rules exist or whether favored codons are chosen randomly in evolution in a process akin to a series of frozen accidents. Here, we study this question by identifying for the first time the favored codons in 675 bacteria, 52 archea, and 10 fungi. We use a number of tests to show that the identified codons are indeed likely to be favored and find that across all studied organisms the identity of favored codons tracks the GC content of the genomes. Once the effect of the genomic GC content on selectively favored codon choice is taken into account, additional universal amino acid specific rules governing the identity of favored codons become apparent. Our results provide for the first time a clear set of rules governing the evolution of selectively favored codon usage. Based on these results, we describe a putative scenario for how evolutionary shifts in the identity of selectively favored codons can occur without even temporary weakening of natural selection for codon bias.