Conditioning from an information processing perspective

The framework provided by Claude Shannon's [Bell Syst. Technol. J. 27 (1948) 623] theory of information leads to a quantitatively oriented reconceptualization of the processes that mediate conditioning. The focus shifts from processes set in motion by individual events to processes sensitive to the information carried by the flow of events. The conception of what properties of the conditioned and unconditioned stimuli are important shifts from the tangible properties to the intangible properties of number, duration, frequency and contingency. In this view, a stimulus becomes a CS if its onset substantially reduces the subject's uncertainty about the time of occurrence of the next US. One way to represent the subject's knowledge of that time of occurrence is by the cumulative probability function, which has two limiting forms: (1) The state of maximal uncertainty (minimal knowledge) is represented by the inverse exponential function for the random rate condition, in which the US is equally likely at any moment. (2) The limit to the subject's attainable certainty is represented by the cumulative normal function, whose momentary expectation is the CS-US latency minus the time elapsed since CS onset. Its standard deviation is the Weber fraction times the CS-US latency.     

Quantitative trait locus study design from an information perspective

We examine the efficiency of different genotyping and phenotyping strategies in inbred line crosses from an information perspective. This provides a mathematical framework for the statistical aspects of QTL experimental design, while guiding our intuition. Our central result is a simple formula that quantifies the fraction of missing information of any genotyping strategy in a backcross. It includes the special case of selectively genotyping only the phenotypic extreme individuals. The formula is a function of the square of the phenotype and the uncertainty in our knowledge of the genotypes at a locus. This result is used to answer a variety of questions. First, we examine the cost-information trade-off varying the density of markers and the proportion of extreme phenotypic individuals genotyped. Then we evaluate the information content of selective phenotyping designs and the impact of measurement error in phenotyping. A simple formula quantifies the information content of any combined phenotyping and genotyping design. We extend our results to cover multigenotype crosses, such as the F(2) intercross, and multiple QTL models. We find that when the QTL effect is small, any contrast in a multigenotype cross benefits from selective genotyping in the same manner as in a backcross. The benefit remains in the presence of a second unlinked QTL with small effect (explaining <20% of the variance), but diminishes if the second QTL has a large effect. Software for performing power calculations for backcross and F(2) intercross incorporating selective genotyping and marker spacing is available from http://www.biostat.ucsf.edu/sen.     

Autonomy: an information theoretic perspective

We present a tentative proposal for a quantitative measure of autonomy. This is something that, surprisingly, is rarely found in the literature, even though autonomy is considered to be a basic concept in many disciplines, including artificial life. We work in an information theoretic setting for which the distinction between system and environment is the starting point. As a first measure for autonomy, we propose the conditional mutual information between consecutive states of the system conditioned on the history of the environment. This works well when the system cannot influence the environment at all and the environment does not interact synergetically with the system. When, in contrast, the system has full control over its environment, we should instead neglect the environment history and simply take the mutual information between consecutive system states as a measure of autonomy. In the case of mutual interaction between system and environment there remains an ambiguity regarding whether system or environment has caused observed correlations. If the interaction structure of the system is known, we define a "causal" autonomy measure which allows this ambiguity to be resolved. Synergetic interactions still pose a problem since in this case causation cannot be attributed to the system or the environment alone. Moreover, our analysis reveals some subtle facets of the concept of autonomy, in particular with respect to the seemingly innocent system-environment distinction we took for granted, and raises the issue of the attribution of control, i.e. the responsibility for observed effects. To further explore these issues, we evaluate our autonomy measure for simple automata, an agent moving in space, gliders in the game of life, and the tessellation automaton for autopoiesis of Varela et al. [Varela, F.J., Maturana, H.R., Uribe, R., 1974. Autopoiesis: the organization of living systems, its characterization and a model. BioSystems 5, 187-196].     

Hitchhiking mapping--functional genomics from the population genetics perspective

Several statistical tests based on population genetic theory are used to identify genes that have recently acquired a beneficial mutation. Here, I describe the extension of these tests to a multilocus approach for a genome-wide survey for genes that have been under recent positive selection. As this strategy could potentially identify genes with weak phenotypic effects, it will be very useful in population genetic approaches aimed at understanding adaptation processes in natural populations. Furthermore, this 'hitchhiking mapping' could also help in the functional characterization of genomes.     

Biochemical genetics and fishery management: an historical perspective

This paper traces the development of applications of biochemical genetic methods to problems of fishery management over a period of four decades. In the 1950s, details of presumed genetic structuring offish species appeared destined for revelation through Mendelian characters identified by immunogenetic procedures. In the 1960s, immunogenetic methods were displaced by protein electrophoresis, with a proliferation of reports of genotypic and allelic data for protein-coding loci. In the 1970s, disagreement about the biological significance of protein polymorphisms delayed acceptance of management applications of this variation. In the 1980s, management applications included identification of relationships among populations, analyses of mixed stock fisheries, and uses in fish culture, conservation biology and forensics. The complementary relationship between protein electrophoresis and nucleic acid technologies is stressed, with a plea to recognize the unique attributes of properly applied protein electrophoresis in fishery management.     

Population genetics of tunas

Population genetic studies on tunas are reviewed. These studies have focused on phylogenetic reconstructions, species identifications and stock delineation, and have used tools ranging from blood group and allozyme analysis to PCR-aided examination of mitochondrial DNA variation. Both allozyme and mtDNA approaches show tunas in the genus Thunnus to be very closely related to one another, but also indicate that the two presently recognized subspecies of northern bluefin tuna, Thunnus thynnus thynnus and T. t. orientalis , in fact may be worthy of species status. These techniques also permit the unequivocal recognition of specimens, which is not always possible on morphological grounds. However, it is arguable that, until recently, tunas have not received their due attention from geneticists given their commercial significance and the need for information on stock structure to ensure sustainable management. This may be because tunas are known to be highly vagile and therefore levels of population differentiation are expected to be low. None the less, population subdivision has been recorded in several species (skipjack, yellowfin, albacore), although this tends to be on a broad (intra- or inter-oceanic) rather than on a more local scale. New molecular tools, including the PCR-based analyses of nuclear genes and microsatellite loci, are yielding new, highly polymorphic markers, and will enable more powerful analyses of stock structure than have hitherto been possible.     

Deciphering next-generation pharmacogenomics: an information technology perspective

In the post-genomic era, the rapid evolution of high-throughput genotyping technologies and the increased pace of production of genetic research data are continually prompting the development of appropriate informatics tools, systems and databases as we attempt to cope with the flood of incoming genetic information. Alongside new technologies that serve to enhance data connectivity, emerging information systems should contribute to the creation of a powerful knowledge environment for genotype-to-phenotype information in the context of translational medicine. In the area of pharmacogenomics and personalized medicine, it has become evident that database applications providing important information on the occurrence and consequences of gene variants involved in pharmacokinetics, pharmacodynamics, drug efficacy and drug toxicity will become an integral tool for researchers and medical practitioners alike. At the same time, two fundamental issues are inextricably linked to current developments, namely data sharing and data protection. Here, we discuss high-throughput and next-generation sequencing technology and its impact on pharmacogenomics research. In addition, we present advances and challenges in the field of pharmacogenomics information systems which have in turn triggered the development of an integrated electronic ‘pharmacogenomics assistant’. The system is designed to provide personalized drug recommendations based on linked genotype-to-phenotype pharmacogenomics data, as well as to support biomedical researchers in the identification of pharmacogenomics-related gene variants. The provisioned services are tuned in the framework of a single-access pharmacogenomics portal.     

Population genetics of Dagestan highlanders

Subdivision of some isolates and heterogenic populations in Daghestan is analysed by human gene and phen frequencies. Comparative population study of phenotypic variability of quantitative characters (anthropometric, neurodynamic and psychodynamic) is carried out. Common hierarchy of variability for all populations as well as an effect of inbreeding and panmixis on variability of the above-mentioned quantitative characters in different populations is demonstrated.     

Population aspects of forensic genetics

The paper presents the methodology of forensic genetics as a synthesis of population genetics and forensic medicine. Main population genetic problems, appearing in calculation of probability statistics and interpretation of the results of forensic genetic investigations, are discussed in detail.     

植物病原物的群体遗传学

品种单一化、生产密集型和一年多茬的现代农业特点导致病原物呈现出进化速度加快、致病力增强及流行风险增大趋势。深入研究病原物群体遗传学对认识病害的流行、有效选育和使用抗性品种乃至控制病害具有重要意义。文章阐述了植物病原物群体遗传学的研究目标和内容、突变、基因迁移、基因重组、随机遗传漂变和自然选择5大遗传机制在植物病原物进化过程中的作用,以及目前植物病原物群体遗传学研究的现状。     

Population genetics of translational robustness

Recent work has shown that expression level is the main predictor of a gene's evolutionary rate and that more highly expressed genes evolve slower. A possible explanation for this observation is selection for proteins that fold properly despite mistranslation, in short selection for translational robustness. Translational robustness leads to the somewhat paradoxical prediction that highly expressed genes are extremely tolerant to missense substitutions but nevertheless evolve very slowly. Here, we study a simple theoretical model of translational robustness that allows us to gain analytic insight into how this paradoxical behavior arises.     

Population genetics of haplodiploid insects

Genic variation of seven species of Hymenoptera is described, using electrophoretic techniques. The heterozygosities range from 0.033 to 0.084. An average heterozygosity is calculated for 23 species of haplodiploid insects, and this value is significantly different from the same value for 18 Drosophila species or for 24 diploid insect species (including Drosophila). The niche width-genetic variation hypothesis is rejected as an explanation. A comparison of selection models and neutral models shows that both hypotheses are capable of explaining the data.