Bicoordinate navigation based on non-orthogonal gradient fields

The mathematically exact solution for navigating with respect to two non-orthogonal gradient fields requires taking both fields into account conjointly. Such a complex solution may be beyond the brain capability of most animals. Animals may use an approximate, simpler solution by considering each field separately (i.e., the angle between the two gradient directions is ignored). This generates directional biases that may prove useful in determining the nature of the fields actually involved in bicoordinate navigation.     

Integrating individual search and navigation behaviors in mechanistic movement models

Understanding complex movement behaviors via mechanistic models is one key challenge in movement ecology. We built a theoretical simulation model using evolutionarily trained artificial neural networks (ANNs) wherein individuals evolve movement behaviors in response to resource landscapes on which they search and navigate. We distinguished among non-oriented movements in response to proximate stimuli, oriented movements utilizing perceptual cues from distant targets, and memory mechanisms that assume prior knowledge of a target??s location and then tested the relevance of these three movement behaviors in relation to size of resource patches, predictability of resource landscapes, and the occurrence of movement barriers. Individuals were more efficient in locating resources under larger patch sizes and predictable landscapes when memory was advantageous. However, memory was also frequently used in unpredictable landscapes with intermediate patch sizes to systematically search the entire spatial domain, and because of this, we suggest that memory may be important in explaining super-diffusion observed in many empirical studies. The sudden imposition of movement barriers had the greatest effect under predictable landscapes and temporarily eliminated the benefits of memory. Overall, we demonstrate how movement behaviors that are linked to certain cognitive abilities can be represented by state variables in ANNs and how, by altering these state variables, the relevance of different behaviors under different spatiotemporal resource dynamics can be tested. If adapted to fit empirical movement paths, methods described here could help reveal behavioral mechanisms of real animals and predict effects of anthropogenic landscape changes on animal movement.     

Locating rearrangement events in a phylogeny based on highly fragmented assemblies

Background

The inference of genome rearrangement operations requires complete genome assemblies as input data, since a rearrangement can involve an arbitrarily large proportion of one or more chromosomes. Most genome sequence projects, especially those on non-model organisms for which no physical map exists, produce very fragmented assembles, so that a rearranged fragment may be impossible to identify because its two endpoints are on different scaffolds. However, breakpoints are easily identified, as long as they do not coincide with scaffold ends. For the phylogenetic context, in comparing a fragmented assembly with a number of complete assemblies, certain combinatorial constraints on breakpoints can be derived. We ask to what extent we can use breakpoint data between a fragmented genome and a number of complete genomes to recover all the arrangements in a phylogeny.

Results

We simulate genomic evolution via chromosomal inversion, fragmenting one of the genomes into a large number of scaffolds to represent the incompleteness of assembly. We identify all the breakpoints between this genome and the remainder. We devise an algorithm which takes these breakpoints into account in trying to determine on which branch of the phylogeny a rearrangement event occurred. We present an analysis of the dependence of recovery rates on scaffold size and rearrangement rate, and show that the true tree, the one on which the rearrangement simulation was performed, tends to be most parsimonious in estimating the number of true events inferred.

Conclusions

It is somewhat surprising that the breakpoints identified just between the fragmented genome and each of the others suffice to recover most of the rearrangements produced by the simulations. This holds even in parts of the phylogeny disjoint from the lineage of the fragmented genome.

     

Principles of goal-directed spatial robot navigation in biomimetic models

Mobile robots and animals alike must effectively navigate their environments in order to achieve their goals. For animals goal-directed navigation facilitates finding food, seeking shelter or migration; similarly robots perform goal-directed navigation to find a charging station, get out of the rain or guide a person to a destination. This similarity in tasks extends to the environment as well; increasingly, mobile robots are operating in the same underwater, ground and aerial environments that animals do. Yet despite these similarities, goal-directed navigation research in robotics and biology has proceeded largely in parallel, linked only by a small amount of interdisciplinary research spanning both areas. Most state-of-the-art robotic navigation systems employ a range of sensors, world representations and navigation algorithms that seem far removed from what we know of how animals navigate; their navigation systems are shaped by key principles of navigation in ‘real-world’ environments including dealing with uncertainty in sensing, landmark observation and world modelling. By contrast, biomimetic animal navigation models produce plausible animal navigation behaviour in a range of laboratory experimental navigation paradigms, typically without addressing many of these robotic navigation principles. In this paper, we attempt to link robotics and biology by reviewing the current state of the art in conventional and biomimetic goal-directed navigation models, focusing on the key principles of goal-oriented robotic navigation and the extent to which these principles have been adapted by biomimetic navigation models and why.     

Locating a resistance mechanism to the cabbage aphid in two wild Brassicas

Feeding behaviour of the cabbage aphid,Brevicoryne brassicae, was monitored electronically on two resistantBrassica species,B. fruticulosa andB. spinescens, and compared with a susceptible controlB. oleracea var.capitata cv. Offenham Compacta. Aphids, monitored for 10 h on the under side of leaves, performed recognizable feeding behaviour on all species. Electrical Penetration Graphs (EPGs) of aphids on resistant and susceptible plants showed no difference in behaviour for aphids on resistantBrassica species compared to susceptible until stylets penetrated the phloem sieve elements when a large reduction in the duration of passive phloem uptake (E₂ pattern) onB. fruticulosa was indicated. Although feeding behaviour on 6 week-old plants ofB. spinescens was similar to the susceptible controls, behaviour on 10 week-old plants was similar to that recorded forB. fruticulosa. The mechanism of resistance is thought to be located in the sieve element as the normal sieve element salivation (E₁) signal was either quickly terminated by withdrawal of the stylets from the sieve element or continued as a disrupted E₂ pattern. Analysis of secondary plant compounds in the threeBrassica species only identified significant differences in the glucosinolate profile. No reproducible differences were detected in the concentration of phenolics or anthocyanins. The major glucosinolate component ofB. fruticulosa andB. spinescens was gluconapin rather than glucobrassicin and glucoiberin as found in the susceptible host plant. However, both pure glucosinolates and glucosinolate extracts from all three species did not reduce aphid survival on chemically-defined artificial diets. These results suggest that the mechanism of resistance may be a mechanical blocking of the sieve element or stylets rather than a difference in the secondary plant chemistry of glucosinolates and phenolics.     

Statistical alignment based on fragment insertion and deletion models

Motivation: The topic of this paper is the estimation of alignments and mutation rates based on stochastic sequence-evolution models that allow insertions and deletions of subsequences ('fragments') and not just single bases. The model we propose is a variant of a model introduced by Thorne et al., (J. Mol. Evol., 34, 3-16, 1992). The computational tractability of the model depends on certain restrictions in the insertion/deletion process; possible effects we discuss. Results: The process of fragment insertion and deletion in the sequence-evolution model induces a hidden Markov structure at the level of alignments and thus makes possible efficient statistical alignment algorithms. As an example we apply a sampling procedure to assess the variability in alignment and mutation parameter estimates for HVR1 sequences of human and orangutan, improving results of previous work. Simulation studies give evidence that estimation methods based on the proposed model also give satisfactory results when applied to data for which the restrictions in the insertion/deletion process do not hold. Availability: The source code of the software for sampling alignments and mutation rates for a pair of DNA sequences according to the fragment insertion and deletion model is freely available from http://www.math.uni-frankfurt.de/~stoch/software/mcmcsalut under the terms of the GNU public license (GPL, 2000).     

Molecular mixture models based on competitive and non-competitive agonism

Agonists in mixtures may bind to a common receptor or to independentreceptors. Signal generation may also depend on a transducer,such as a G protein. Interactions among agoinsts, receptorsand transducers lead to changes in the activity of effectors,such as adenylyl cyclase, resulting in signals which affectbehavior. In this paper, six molecular mixture models are presented,four of which are derived for the first time. These models distinguishbetween two important properties of chemicals as they interactwith receptor cells and transducers: their affinity in bindingto receptors and their efficacy in producing a particular effect,such as taste perception. Several generalizations can be drawnfrom these new models: (i) if a common receptor for two substancesexists and if simple binding to the receptor occurs, there willbe a linear relationship between the components of mixtureswhich have equal perceptual, or other, effects, even followingan additional transduction step prior to perception: (ii) ifco-operative binding to a common receptor occurs, the relationshipbetween mixture components will be non-linear, and (iii) ifsimple binding to independent receptors occurs, the relationshipbetween mixture components may be non-linear (for example, asynergistic effect), and similar to (ii). These models wereevaluated using the data of De Graaf and Frijter (1986) on theperceived sweetness of binary mixtures of glucose and fructose.These results of this analysis revealed that if a common receptorsoccurs for these two compounds, co-operative binding must alsoexist. If simple binding occurs, them independent receptorsand the participation of a third binding entity are requiredto model the data.     

A mathematical expectation model for bird navigation based on the clock-and-compass strategy

We present here a mathematical formula for the directional distribution of migratory birds if they use a vector navigation/clock-and-compass strategy to find their winter quarters. It is based on mathematical expectation theory and shows that a simple parabola can describe the expected geographical spread of clock-and-compass birds as a function of migratory distance. Predictions based on this model are then tested against all same autumn ringing recoveries of first-season Pied Flycatchers, Ficedula hypoleuca, ringed in Scandinavia and European Robins, Erithacus rubecula, ringed in Sweden and Finland and recovered north of the Sahara Desert. We find that the predictions of our analytical model fit the ringing recovery distribution of freely migrating conspecifics extremely well.     

Waypoint based path planner for socially aware robot navigation

Cluster Computing - Social navigation is beneficial for mobile robots in human inhabited areas. In this paper, we focus on smooth path tracking and handling disruptions during plan execution in...     

Codon substitution models based on residue similarity and their applications

Codon models are now widely used to draw evolutionary inferences from alignments of homologous sequence data. Incorporating physicochemical properties of amino acids into codon models, two novel codon substitution models describing the evolution of protein-coding DNA sequences are presented based on the similarity scores of amino acids. To describe substitutions between codons a continue-time Markov process is used. Transition/transversion rate bias and nonsynonymous codon usage bias are allowed in the models. In our implementation, the parameters are estimated by maximum-likelihood (ML) method as in previous studies. Furthermore, instantaneous mutations involving more than one nucleotide position of a codon are considered in the second model. Then the two suggested models are applied to five real data sets. The analytic results indicate that the new codon models considering physicochemical properties of amino acids can provide a better fit to the data comparing with existing codon models, and then produce more reliable estimates of certain biologically important measures than existing methods.     

Sensitivity to dimethyl sulphide suggests a mechanism for olfactory navigation by seabirds

Petrels, albatrosses and other procellariiform seabirds have an excellent sense of smell, and routinely navigate over the world's oceans by mechanisms that are not well understood. These birds travel thousands of kilometres to forage on ephemeral prey patches at variable locations, yet they can quickly and efficiently find their way back to their nests on remote islands to provision chicks, even with magnetic senses experimentally disrupted. Over the seemingly featureless ocean environment, local emissions of scents released by phytoplankton reflect bathymetric features such as shelf breaks and seamounts. These features suggest an odour landscape that may provide birds with orientation cues. We have previously shown that concentrated experimental deployments of one such compound, dimethyl sulphide (DMS), attracts procellariiforms at sea, suggesting that some species can use it as a foraging cue. Here we present the first physiological demonstration that an Antarctic seabird can detect DMS at biogenic levels. We further show that birds can use DMS as an orientation cue in a non-foraging context within a concentration range that they might naturally encounter over the ocean.     

Assembly models for Papovaviridae based on tiling theory

A vital constituent of a virus is its protein shell, called the viral capsid, that encapsulates and hence provides protection for the viral genome. Assembly models are developed for viral capsids built from protein building blocks that can assume different local bonding structures in the capsid. This situation occurs, for example, for viruses in the family of Papovaviridae, which are linked to cancer and are hence of particular interest for the health sector. More specifically, the viral capsids of the (pseudo-) T = 7 particles in this family consist of pentamers that exhibit two different types of bonding structures. While this scenario cannot be described mathematically in terms of Caspar-Klug theory (Caspar D L D and Klug A 1962 Cold Spring Harbor Symp. Quant. Biol. 27 1), it can be modelled via tiling theory (Twarock R 2004 J. Theor. Biol. 226 477). The latter is used to encode the local bonding environment of the building blocks in a combinatorial structure, called the assembly tree, which is a basic ingredient in the derivation of assembly models for Papovaviridae along the lines of the equilibrium approach of Zlotnick (Zlotnick A 1994 J. Mol. Biol. 241 59). A phase space formalism is introduced to characterize the changes in the assembly pathways and intermediates triggered by the variations in the association energies characterizing the bonds between the building blocks in the capsid. Furthermore, the assembly pathways and concentrations of the statistically dominant assembly intermediates are determined. The example of Simian virus 40 is discussed in detail.     

Acclimation in dynamic models based on structural relationships

1. A number of recent tree growth models have been based on the assumption that tree structure follows certain empirical rules and carbon allocation is performed so as to maintain these rules when growth and senescence occur simultaneously. This paper introduces a method of combining structural rules with adaptive regulation in a carbon balance model.
2. The method is based on regulating gross growth but situations are analysed where increased senescence of tissue functions as an alternative means of re-establishing the balance.
3. The model does not aim to be mechanistic but merely to describe the process of regulation, or acclimation to changing environments and situations, as constrained by the carbon balance. The method incorporates parameters that describe the rate of returning to the balance after disturbance or after a change in the goal, which can be determined empirically.
4. Two models are given as examples of the use of the method, and the requirements and limitations of control in a carbon balance framework are discussed.
5. The method is best applied as a technical tool to describe variations and disturbance in balanced growth models when the variations are present but not very large. In addition, it can be used as a theoretical framework for the analysis of regulation as constrained by the conservation of mass.     

Language models based on Hebbian cell assemblies.

This paper demonstrates how associative neural networks as standard models for Hebbian cell assemblies can be extended to implement language processes in large-scale brain simulations. To this end the classical auto- and hetero-associative paradigms of attractor nets and synfire chains (SFCs) are combined and complemented by conditioned associations as a third principle which allows for the implementation of complex graph-like transition structures between assemblies. We show example simulations of a multiple area network for object-naming, which categorises objects in a visual hierarchy and generates different specific syntactic motor sequences ("words") in response. The formation of cell assemblies due to ongoing plasticity in a multiple area network for word learning is studied afterwards. Simulations show how assemblies can form by means of percolating activity across auditory and motor-related language areas, a process supported by rhythmic, synchronized propagating waves through the network. Simulations further reproduce differences in own EEG&MEG experiments between responses to word- versus non-word stimuli in human subjects.     

Mathematical models and simulations of cellular processes based on actin filaments

Actin filaments help to maintain the physical integrity of cells and participate in many processes that produce cellular movements. Studies of the processes that depend on actin filaments have progressed to the point where mathematical models and computer simulations are an essential part of the experimental toolkit. These quantitative models integrate knowledge about the structures of the key proteins and the rate and equilibrium constants for the reactions for comparison with a growing body of quantitative measurements of dynamic processes in live cells. Models and simulations are essential because it is impossible to appreciate by intuition alone the properties that emerge from a network of coupled reactions, particularly when the system contains many components, and force is one of the parameters.     

Designing hybrid life cycle assessment models based on uncertainty and complexity

Purpose

Despite the wide use of LCA for environmental profiling, the approach for determining the system boundary within LCA models continues to be subjective and lacking in mathematical rigor. As a result, life cycle models are often developed in an ad hoc manner, and are difficult to compare. Significant environmental impacts may be inadvertently left out. Overcoming this shortcoming can help elicit greater confidence in life cycle models and their use for decision making.

Methods

This paper describes a framework for hybrid life cycle model generation by selecting activities based on their importance, parametric uncertainty, and contribution to network complexity. The importance of activities is determined by structural path analysis—which then guides the construction of life cycle models based on uncertainty and complexity indicators. Information about uncertainty is from the available life cycle inventory; complexity is quantified by cost or granularity. The life cycle model is developed in a hierarchical manner by adding the most important activities until error requirements are satisfied or network complexity exceeds user-specified constraints.

Results and Discussion

The framework is applied to an illustrative example for building a hybrid LCA model. Since this is a constructed example, the results can be compared with the actual impact, to validate the approach. This application demonstrates how the algorithm sequentially develops a life cycle model of acceptable uncertainty and network complexity. Challenges in applying this framework to practical problems are discussed.

Conclusion

The presented algorithm designs system boundaries between scales of hybrid LCA models, includes or omits activities from the system based on path analysis of environmental impact contribution at upstream network nodes, and provides model quality indicators that permit comparison between different LCA models.

     

Structural models of the MscL gating mechanism.

Three-dimensional structural models of the mechanosensitive channel of large conductance, MscL, from the bacteria Mycobacterium tuberculosis and Escherichia coli were developed for closed, intermediate, and open conformations. The modeling began with the crystal structure of M. tuberculosis MscL, a homopentamer with two transmembrane alpha-helices, M1 and M2, per subunit. The first 12 N-terminal residues, not resolved in the crystal structure, were modeled as an amphipathic alpha-helix, called S1. A bundle of five parallel S1 helices are postulated to form a cytoplasmic gate. As membrane tension induces expansion, the tilts of M1 and M2 are postulated to increase as they move away from the axis of the pore. Substantial expansion is postulated to occur before the increased stress in the S1 to M1 linkers pulls the S1 bundle apart. During the opening transition, the S1 helices and C-terminus amphipathic alpha-helices, S3, are postulated to dock parallel to the membrane surface on the perimeter of the complex. The proposed gating mechanism reveals critical spatial relationships between the expandable transmembrane barrel formed by M1 and M2, the gate formed by S1 helices, and "strings" that link S1s to M1s. These models are consistent with numerous experimental results and modeling criteria.     

Predicting future responses based on possibly mis-specified working models

Under a general regression setting, we propose an optimal unconditionalprediction procedure for future responses. The resulting predictionintervals or regions have a desirable average coverage levelover a set of covariate vectors of interest. When the workingmodel is not correctly specified, the traditional conditionalprediction method is generally invalid. On the other hand, onecan empirically calibrate the above unconditional procedureand also obtain its crossvalidated counterpart. Various largeand small sample properties of these unconditional methods areexamined analytically and numerically. We find that the -foldcrossvalidated procedure performs exceptionally well even forcases with rather small sample sizes. The new proposals areillustrated with two real examples, one with a continuous responseand the other with a binary outcome.