A computational approach to animal breeding

We propose a computational model of mating strategies for controlled animal breeding programs. A mating strategy in a controlled breeding program is a heuristic with some optimization criteria as a goal. Thus, it is appropriate to use the computational tools available for analysis of optimization heuristics. In this paper, we propose the first discrete model of the controlled animal breeding problem and analyse heuristics for two possible objectives: (1) breeding for maximum diversity and (2) breeding a target individual. These two goals are representative of conservation biology and agricultural livestock management, respectively. We evaluate several mating strategies and provide upper and lower bounds for the expected number of matings. While the population parameters may vary and can change the actual number of matings for a particular strategy, the order of magnitude of the number of expected matings and the relative competitiveness of the mating heuristics remains the same. Thus, our simple discrete model of the animal breeding problem provides a novel viable and robust approach to designing and comparing breeding strategies in captive populations.     

A computational approach to the polymerizabilities of diallylamines

Some selected diallylamine monomers have been studied with the semiempirical PM3 method as model compounds for N,N-dialkyl-N-2-(alkoxycarbonyl)allylammonium salts, in order to build up a quantitative and qualitative relationship between the experimental cyclopolymerizabilities of the monomers and calculated parameters such as charge, energy, geometrical features, bond orders, local softness values and HOMO-LUMO gaps. The charges on nitrogen, vinyl and allyl carbons, the activation barriers, the local softness values and the HOMO-LUMO gaps are found to represent the polymerizability trend of the monomers in general. Three-dimensional structures have been proposed for the reactants and their transition states by geometry optimizations with PM3.     

A computational approach to design energetic ionic liquids

The present work deals with the theoretical estimation of ion-pair binding energies and the energetic properties of four ion pairs formed by combining the 1-butyl-2,4-dinitro-3-methyl imidazolium ion with nitrate (I), perchlorate (II), dinitramide (III), or 3,5-dinitro-1,2,4-triazolate (IV) anions. The counterpoise-corrected ion-pair binding energies were calculated for each ion pair at the B3LYP/6-311+G(d,p) level of theory. Results show that the cation–anion interaction is strongest for ion pair I and weakest for IV, indicating that the nitrate (I) has a greater tendency to exist as a stable ionic salt whereas the 3,5-dinitro-1,2,4-triazolate (IV) may exist as an ionic liquid. Natural bond orbital (NBO) analysis and electrostatic potential (ESP) mapping revealed that charge transfer occurs in all of the ion pairs, but is greatest (0.25e) for ion pair I and smallest (0.03e) for IV, resulting in ion pair I being the least polarized. A nucleus-independent chemical shift (NICS) study revealed that the aromaticity of the 1-butyl-2,4-dinitro-3-methyl imidazolium ion significantly increases in ion pair IV, indicating that this has the greatest charge delocalization among all of the four ion pairs considered. Studies of thermodynamic and detonation properties showed that ion pair II is the most energetic ion pair in terms of its detonation velocity (D = 7.5 km s^?1) and detonation pressure (P = 23.1 GPa). It is also envisaged that ion pair IV would exist as an energetic azolium azolate type ionic liquid that could be conveniently used as a secondary explosive characterized by detonation parameters D and P of 6.9 km s^?1 and 19.3 GPa, respectively. These values are comparable to those of conventional explosives such as TNT.     

A computational approach to the synthesis of dirithromycin

Dirithromycin is a macrolide antibiotic derived from erythromycin A. Dirithromycin is synthesized by the condensation of 9(S)-erythromycylamine with 2-(2-methoxyethoxy)-acetaldehyde. To gain insight into the synthesis, the condensation mechanism has been analyzed computationally by the AM1 method in the gas phase. First, the formation of the Schiff bases of dirithromycin and epidirithromycin from 9(S)-erythromycylamine and 2-(2-methoxyethoxy)-acetaldehyde were modeled. Then, the tautomerization of the Schiff bases to dirithromycin and epidirithromycin were considered. Finally, the epimerization of the Schiff base of epidirithromycin to the Schiff base of dirithromycin was investigated. Our results show that, even though carbinolamine forms faster for epidirithromycin than the corresponding structure for dirithromycin, dirithromycin is the major product of the synthesis. Figure Synthesis of dirithromycin     

A multi-differential neuromorphic approach to motion detection

This paper presents a multi-differential neuromorphic approach to motion detection. The model is based evidence for a differential operators interpretation of the properties of the cortical motion pathway. We discuss how this strategy, which provides a robust measure of speed for a range of types of image motion using a single computational mechanism, forms a useful framework in which to develop future neuromorphic motion systems. We also discuss both our approaches to developing computational motion models, and constraints in the design strategy for transferring motion models to other domains of early visual processing.     

A biological approach to computational models of proteomic networks

Computational modeling is useful as a means to assemble and test what we know about proteins and networks. Models can help address key questions about the measurement, definition and function of proteomic networks. Here, we place these biological questions at the forefront in reviewing the computational strategies that are available to analyze proteomic networks. Recent examples illustrate how models can extract more information from proteomic data, test possible interactions between network proteins and link networks to cellular behavior. No single model can achieve all these goals, however, which is why it is critical to prioritize biological questions before specifying a particular modeling approach.     

A matrix computational approach to kinesin neck linker extension

Kinesin stepping requires both tethered diffusion of the free head and conformational changes driven by the chemical state of the motor. We present a numerical method using matrix representations of approximating Markov chains and renewal theory to compute important experimental quantities for models that include both tethered diffusion and chemical transitions. Explicitly modeling the tethered diffusion allows for exploration of the model under perturbation of the neck linker; comparisons are made between the computed models and in vitro assays.     

A computational approach to the functional screening of genomes

Comparative genomics usually involves managing the functional aspects of genomes, by simply comparing gene-by-gene functions. Following this approach, Mushegian and Koonin proposed a hypothetical minimal genome, Minimal Gene Set (MGS), aiming for a possible oldest ancestor genome. They obtained MGS by comparing the genomes of two simple bacteria and eliminating duplicated or functionally identical genes. The authors raised the fundamental question of whether a hypothetical organism possessing MGS is able to live or not. We attacked this viability problem specifying in silico the metabolic pathways of the MGS-based prokaryote. We then performed a dynamic simulation of cellular metabolic activities in order to check whether the MGS-prokaryote reaches some equilibrium state and produces the necessary biomass. We assumed these two conditions to be necessary for a living organism. Our simulations clearly show that the MGS does not express an organism that is able to live. We then iteratively proceeded with functional replacements in order to obtain a genome composition that gives rise to equilibrium. We ruled out 76 of the original 254 genes in the MGS, because they resulted in duplication from a functional point of view. We also added seven genes not present in the MGS. These genes encode for enzymes involved in critical nodes of the metabolic network. These modifications led to a genome composed of 187 elements expressing a virtually living organism, Virtual Cell (ViCe), that exhibits homeostatic capabilities and produces biomass. Moreover, the steady-state distribution of the concentrations of virtual metabolites that resulted was similar to that experimentally measured in bacteria. We conclude then that ViCe is able to “live in silico.”     

A comparative psychophysical approach to visual perception in primates

Studies on the visual processing of primates, which have well developed visual systems, provide essential information about the perceptual bases of their higher-order cognitive abilities. Although the mechanisms underlying visual processing are largely shared between human and nonhuman primates, differences have also been reported. In this article, we review psychophysical investigations comparing the basic visual processing that operates in human and nonhuman species, and discuss the future contributions potentially deriving from such comparative psychophysical approaches to primate minds.     

The computational measurement of apparent motion: A recurrent pattern recognition strategy as an approach to solve the correspondence problem

In short, the model consists of a two-dimensional set of edge detecting units, modelled according to the zero-crossing detectors introduced first by Marr and Ullman (1981). These detectors are located peripherally in our synthetic vision system and are the input elements for an intelligent recurrent network. The purpose of that network is to recognize and categorize the previously detected contrast changes in a multi-resolution representation of the original image in such a manner that the original information will be decomposed into a relatively small numberN of well-defined edge primitives. The advantage of such a construction is that time-consuming pattern recognition has no longer to be done on the originally complex motion-blurred images of moving objects, but on a limited number of categorized forms. Based on a numberM of elementary feature attributes for each individual edge primitive, the model is then able to decompose each edge pattern into certain features. In this way anM-dimensional vector can be constructed for each edge. For each sequence of two successive frames a tensor can be calculated containing the distances (measured inM-dimensional feature space) between all features in both images. This procedure yields a set ofK—1 tensors for a sequence ofK images. After cross-correlation of allN ×M feature attributes from image (i) with those from image (i+1), wherei = 1, ...,K - 1, probability distributions can be computed. The final step is to search for maxima in these probability functions and then to construct from these extremes an optimal motion field. A number of simulation examples will be presented.     

A computational approach to simplifying the protein folding alphabet.

What is the minimal number of residue types required to form a structured protein? This question is important for understanding protein modeling and design. Recently, an experimental finding by Baker and coworkers suggested a five-residue solution to this problem. We were motivated by their results and by the arguments of Wolynes to study reductions of protein representation based on the concept of mismatch between a reduced interaction matrix and the Miyazawa and Jernigan (MJ) matrix. We find several possible simplified schemes from the relationship of minimized mismatch versus the number of residue types (N = approximately 2-20). As a specific case, an optimal reduction with five types of residues has the same form as the simplified palette of Baker and coworkers. Statistical and kinetic features of a number of sequences are tested. Comparison of results from sequences with 20 residue types and their reduced representations indicates that the reduction by mismatch minimization is successful. For example, sequences with five types of residues have good folding ability and kinetic accessibility in model studies.     

A computational approach to characterization of bovine sperm chromatin alterations

We describe here a computational morphology-based approach to the investigation of possible causes of chromatin alterations in sperm. A comprehensive set of state-of-the-art and geometric measures are computationally extracted from toluidine blue stained images and analyzed to infer the possible processes leading to normal and abnormal chromatin formation while seeking a possible taxonomy of chromatin alterations and their influence on sperm head morphology. Using this methodology, we have identified higher chromatin fragility at some specific points of the sperm head. Despite the lack of correlation between morphologies of sperm head and chromatin structure, four main morphological types of chromatin alterations in bull spermatozoa have been identified and their possible causes discussed.     

A computational approach to studying ageing at the individual level

The ageing process is actively regulated throughout an organism''s life, but studying the rate of ageing in individuals is difficult with conventional methods. Consequently, ageing studies typically make biological inference based on population mortality rates, which often do not accurately reflect the probabilities of death at the individual level. To study the relationship between individual and population mortality rates, we integrated in vivo switch experiments with in silico stochastic simulations to elucidate how carefully designed experiments allow key aspects of individual ageing to be deduced from group mortality measurements. As our case study, we used the recent report demonstrating that pheromones of the opposite sex decrease lifespan in Drosophila melanogaster by reversibly increasing population mortality rates. We showed that the population mortality reversal following pheromone removal was almost surely occurring in individuals, albeit more slowly than suggested by population measures. Furthermore, heterogeneity among individuals due to the inherent stochasticity of behavioural interactions skewed population mortality rates in middle-age away from the individual-level trajectories of which they are comprised. This article exemplifies how computational models function as important predictive tools for designing wet-laboratory experiments to use population mortality rates to understand how genetic and environmental manipulations affect ageing in the individual.     

A computational approach to finding novel targets for existing drugs

Repositioning existing drugs for new therapeutic uses is an efficient approach to drug discovery. We have developed a computational drug repositioning pipeline to perform large-scale molecular docking of small molecule drugs against protein drug targets, in order to map the drug-target interaction space and find novel interactions. Our method emphasizes removing false positive interaction predictions using criteria from known interaction docking, consensus scoring, and specificity. In all, our database contains 252 human protein drug targets that we classify as reliable-for-docking as well as 4621 approved and experimental small molecule drugs from DrugBank. These were cross-docked, then filtered through stringent scoring criteria to select top drug-target interactions. In particular, we used MAPK14 and the kinase inhibitor BIM-8 as examples where our stringent thresholds enriched the predicted drug-target interactions with known interactions up to 20 times compared to standard score thresholds. We validated nilotinib as a potent MAPK14 inhibitor in vitro (IC50 40 nM), suggesting a potential use for this drug in treating inflammatory diseases. The published literature indicated experimental evidence for 31 of the top predicted interactions, highlighting the promising nature of our approach. Novel interactions discovered may lead to the drug being repositioned as a therapeutic treatment for its off-target's associated disease, added insight into the drug's mechanism of action, and added insight into the drug's side effects.     

Auditory motion information drives visual motion perception

Background

Vision provides the most salient information with regard to the stimulus motion. However, it has recently been demonstrated that static visual stimuli are perceived as moving laterally by alternating left-right sound sources. The underlying mechanism of this phenomenon remains unclear; it has not yet been determined whether auditory motion signals, rather than auditory positional signals, can directly contribute to visual motion perception.

Methodology/Principal Findings

Static visual flashes were presented at retinal locations outside the fovea together with a lateral auditory motion provided by a virtual stereo noise source smoothly shifting in the horizontal plane. The flash appeared to move by means of the auditory motion when the spatiotemporal position of the flashes was in the middle of the auditory motion trajectory. Furthermore, the lateral auditory motion altered visual motion perception in a global motion display where different localized motion signals of multiple visual stimuli were combined to produce a coherent visual motion perception.

Conclusions/Significance

These findings suggest there exist direct interactions between auditory and visual motion signals, and that there might be common neural substrates for auditory and visual motion processing.     

A new approach to the job scheduling problem in computational grids

Job scheduling is one of the most challenging issues in Grid resource management that strongly affects the performance of the whole Grid environment. The major drawback of the existing Grid scheduling algorithms is that they are unable to adapt with the dynamicity of the resources and the network conditions. Furthermore, the network model that is used for resource information aggregation in most scheduling methods is centralized or semi-centralized. Therefore, these methods do not scale well as Grid size grows and do not perform well as the environmental conditions change with time. This paper proposes a learning automata-based job scheduling algorithm for Grids. In this method, the workload that is placed on each Grid node is proportional to its computational capacity and varies with time according to the Grid constraints. The performance of the proposed algorithm is evaluated through conducting several simulation experiments under different Grid scenarios. The obtained results are compared with those of several existing methods. Numerical results confirm the superiority of the proposed algorithm over the others in terms of makespan, flowtime, and load balancing.