Computational analysis of epigenetic information in human DNA sequences

Over the last few years, investigations of human epigenetic profiles have identified key elements of change to be Histone Modifications, stable and heritable DNA methylation and Chromatin remodeling. These factors determine gene expression levels and characterise conditions leading to disease. In order to extract information embedded in long DNA sequences, data mining and pattern recognition tools are widely used, but efforts have been limited to date with respect to analyzing epigenetic changes, and their role as catalysts in disease onset. Useful insight, however, can be gained by investigation of associated dinucleotide distributions. The focus of this paper is to explore specific dinucleotides frequencies across defined regions within the human genome, and to identify new patterns between epigenetic mechanisms and DNA content. Signal processing methods, including Fourier and Wavelet Transformations, are employed and principal results are reported.

Whole-brain imaging with single-cell resolution using chemical cocktails and computational analysis

Systems-level identification and analysis of cellular circuits in the brain will require the development of whole-brain imaging with single-cell resolution. To this end, we performed comprehensive chemical screening to develop a whole-brain clearing and imaging method, termed CUBIC (clear, unobstructed brain imaging cocktails and computational analysis). CUBIC is a simple and efficient method involving the immersion of brain samples in chemical mixtures containing aminoalcohols, which enables rapid whole-brain imaging with single-photon excitation microscopy. CUBIC is applicable to multicolor imaging of fluorescent proteins or immunostained samples in adult brains and is scalable from a primate brain to subcellular structures. We also developed a whole-brain cell-nuclear counterstaining protocol and a computational image analysis pipeline that, together with CUBIC reagents, enable the visualization and quantification of neural activities induced by environmental stimulation. CUBIC enables time-course expression profiling of whole adult brains with single-cell resolution.

An improved computational method in structural dynamics

Purpose – In structural, earthquake and aeronautical engineering and mechanical vibration, the solution of dynamic equations for a structure subjected to dynamic loading leads to a high order system of differential equations. The numerical methods are usually used for integration when either there is dealing with discrete data or there is no analytical solution for the equations. Since the numerical methods with more accuracy and stability give more accurate results in structural responses, there is a need to improve the existing methods or develop new ones. The paper aims to discuss these issues. Design/methodology/approach – In this paper, a new time integration method is proposed mathematically and numerically, which is accordingly applied to single-degree-of-freedom (SDOF) and multi-degree-of-freedom (MDOF) systems. Finally, the results are compared to the existing methods such as Newmark’s method and closed form solution. Findings – It is concluded that, in the proposed method, the data variance of each set of structural responses such as displacement, velocity, or acceleration in different time steps is less than those in Newmark’s method, and the proposed method is more accurate and stable than Newmark’s method and is capable of analyzing the structure at fewer numbers of iteration or computation cycles, hence less time-consuming. Originality/value – A new mathematical and numerical time integration method is proposed for the computation of structural responses with higher accuracy and stability, lower data variance, and fewer numbers of iterations for computational cycles.

Biophysical correlates of intrinsic and stress-induced morphological variability in lateral amygdaloid neurons: A computational study

Morphological and physiological characteristics of neurons located in the dorsolateral and two ventral subdivisions of the lateral amygdala (LA) have been compared in order to differentiate their roles in the formation and storage of fear memories (Alphs et al, SfN abs 623.1, 2003). Briefly, in these populations, significant differences are observed in input resistance, membrane time constant, firing frequency, dendritic tortuosity, numbers of primary dendrites, dendritic segments and dendritic nodes...

Bayesian computational methods for spatial analysis of images

This thesis introduces a new way of using prior information in a spatial model and develops scalable algorithms for fitting this model to large imaging datasets. These methods are employed for image-guided radiation therapy and satellite based classification of land use and water quality. This study has utilized a pre-computation step to achieve a hundredfold improvement in the elapsed runtime for model fitting. This makes it much more feasible to apply these models to real-world problems, and enables full Bayesian inference for images with a million or more pixels.

Understanding the relationship between interfragmentary movement and callus growth in fracture healing: A novel computational approach

Introduction & Aims Optimising fracture treatments requires a sound understanding of relationships between stability, callus development and healing outcomes. This has been the goal of computational modelling, but discrepancies remain between simulations and experimental results. We compared healing patterns vs fixation stiffness between a novel computational callus growth model and corresponding experimental data. Hypothesis We hypothesised that callus growth is stimulated by diffusible signals, whose production is in turn regulated by mechanical conditions at the fracture site. We proposed that introducing this scheme into computational models would better replicate the observed tissue patterns and the inverse relationship between callus size and fixation stiffness. Method Finite element models of bone healing under stiff and flexible fixation were constructed, based on the parameters of a parallel rat femoral osteotomy study. An iterative procedure was implemented, to simulate the development of callus and its mechanical regulation. Tissue changes were regulated according to published mechano-biological criteria. Predictions of healing patterns were compared between standard models, with a pre-defined domain for callus development, and a novel approach, in which periosteal callus growth is driven by a diffusible signal. Production of this signal was driven by local mechanical conditions. Finally, each model’s predictions were compared to the corresponding histological data. Results Models in which healing progressed within a prescribed callus domain predicted that greater interfragmentary movements would displace early periosteal bone formation further from the fracture. This results from artificially large distortional strains predicted near the fracture edge. While experiments showed increased hard callus size under flexible fixation, this was not reflected in the standard models. Allowing the callus to grow from a thin soft tissue layer, in response to a mechanically stimulated diffusible signal, results in a callus shape and tissue distribution closer to those observed histologically. Importantly, the callus volume increased with increasing interfragmentary movement. Conclusions A novel method to incorporate callus growth into computational models of fracture healing allowed us to successfully capture the relationship between callus size and fixation stability observed in our rat experiments. This approach expands our toolkit for understanding the influence of different fixation strategies on healing outcomes.

A service-oriented architecture for text analytics enabled business applications

Experiences showed that developing business applications that base on text analysis normally requires a lot of time and expertise in the field of computer linguistics. Several approaches of integrating text analysis systems with business applications have been proposed, but so far there has been no coordinated approach which would enable building scalable and flexible applications of text analysis in enterprise scenarios. In this paper, a service-oriented architecture for text processing applications in the business domain is introduced. It comprises various groups of processing components and knowledge resources. The architecture, created as a result of our experiences with building natural language processing applications in business scenarios, allows for the reuse of text analysis and other components, and facilitates the development of business applications. We verify our approach by showing how the proposed architecture can be applied to create a text analytics enabled business application that addresses a concrete business scenario. © 2010 IEEE.

Designs and architectures for the next generation of organic solar cells

Organic solar cells show great promise as an economically and environmentally friendly technology to utilize solar energy because of their simple fabrication processes and minimal material usage. However, new innovations and breakthroughs are needed for organic solar cell technology to become competitive in the future. This article reviews research efforts and accomplishments focusing on three issues: power conversion efficiency, device stability and processability for mass production, followed by an outlook for optimizing OSC performance through device engineering and new architecture designs to realize next generation organic solar cells.

Single layer lead iodide: Computational exploration of structural, electronic and optical properties, strain induced band modulation and the role of spin-orbital-coupling

Graphitic like layered materials exhibit intriguing electronic structures and thus the search for new types of two-dimensional (2D) monolayer materials is of great interest for developing novel nano-devices. By using density functional theory (DFT) method, here we for the first time investigate the structure, stability, electronic and optical properties of monolayer lead iodide (PbI2). The stability of PbI2 monolayer is first confirmed by phonon dispersion calculation. Compared to the calculation using generalized gradient approximation, screened hybrid functional and spin–orbit coupling effects can not only predicts an accurate bandgap (2.63 eV), but also the correct position of valence and conduction band edges. The biaxial strain can tune its bandgap size in a wide range from 1 eV to 3 eV, which can be understood by the strain induced uniformly change of electric field between Pb and I atomic layer. The calculated imaginary part of the dielectric function of 2D graphene/PbI2 van der Waals type hetero-structure shows significant red shift of absorption edge compared to that of a pure monolayer PbI2. Our findings highlight a new interesting 2D material with potential applications in nanoelectronics and optoelectronics.

Population of computational rabbit-specific ventricular action potential models for investigating sources of variability in cellular repolarisation

Variability is observed at all levels of cardiac electrophysiology. Yet, the underlying causes and importance of this variability are generally unknown, and difficult to investigate with current experimental techniques. The aim of the present study was to generate populations of computational ventricular action potential models that reproduce experimentally observed intercellular variability of repolarisation (represented by action potential duration) and to identify its potential causes. A systematic exploration of the effects of simultaneously varying the magnitude of six transmembrane current conductances (transient outward, rapid and slow delayed rectifier K(+), inward rectifying K(+), L-type Ca(2+), and Na(+)/K(+) pump currents) in two rabbit-specific ventricular action potential models (Shannon et al. and Mahajan et al.) at multiple cycle lengths (400, 600, 1,000 ms) was performed. This was accomplished with distributed computing software specialised for multi-dimensional parameter sweeps and grid execution. An initial population of 15,625 parameter sets was generated for both models at each cycle length. Action potential durations of these populations were compared to experimentally derived ranges for rabbit ventricular myocytes. 1,352 parameter sets for the Shannon model and 779 parameter sets for the Mahajan model yielded action potential duration within the experimental range, demonstrating that a wide array of ionic conductance values can be used to simulate a physiological rabbit ventricular action potential. Furthermore, by using clutter-based dimension reordering, a technique that allows visualisation of multi-dimensional spaces in two dimensions, the interaction of current conductances and their relative importance to the ventricular action potential at different cycle lengths were revealed. Overall, this work represents an important step towards a better understanding of the role that variability in current conductances may play in experimentally observed intercellular variability of rabbit ventricular action potential repolarisation.

Flow evaluation and hemolysis analysis of BVAD centrifugal blood pump by computational fluids dynamics

Computational fluid dynamics (CFD) and particle image velocimetry (PIV) are commonly used techniques to evaluate the flow characteristics in the development stage of blood pumps. CFD technique allows rapid change to pump parameters to optimize the pump performance without having to construct a costly prototype model. These techniques are used in the construction of a bi-ventricular assist device (BVAD) which combines the functions of LVAD and RVAD in a compact unit. The BVAD construction consists of two separate chambers with similar impellers, volutes, inlet and output sections. To achieve the required flow characteristics of an average flow rate of 5 l/min and different pressure heads (left – 100mmHg and right – 20mmHg), the impellers were set at different rotating speeds. From the CFD results, a six-blade impeller design was adopted for the development of the BVAD. It was also observed that the fluid can flow smoothly through the pump with minimum shear stress and area of stagnation which are related to haemolysis and thrombosis. Based on the compatible Reynolds number the flow through the model was calculated for the left and the right pumps. As it was not possible to have both the left and right chambers in the experimental model, the left and right pumps were tested separately.

Dissociable forms of repetition priming: A computational model

Nondeclarative memory and novelty processing in the brain is an actively studied field of neuroscience, and reducing neural activity with repetition of a stimulus (repetition suppression) is a commonly observed phenomenon. Recent findings of an opposite trend specifically, rising activity for unfamiliar stimuli—question the generality of repetition suppression and stir debate over the underlying neural mechanisms. This letter introduces a theory and computational model that extend existing theories and suggests that both trends are, in principle, the rising and falling parts of an inverted U-shaped dependence of activity with respect to stimulus novelty that may naturally emerge in a neural network with Hebbian learning and lateral inhibition. We further demonstrate that the proposed model is sufficient for the simulation of dissociable forms of repetition priming using real-world stimuli. The results of our simulation also suggest that the novelty of stimuli used in neuroscientific research must be assessed in a particularly cautious way. The potential importance of the inverted-U in stimulus processing and its relationship to the acquisition of knowledge and competencies in humans is also discussed

Two-scale computational modelling of water flow in unsaturated soils containing irregular-shaped inclusions

The focus of this paper is two-dimensional computational modelling of water flow in unsaturated soils consisting of weakly conductive disconnected inclusions embedded in a highly conductive connected matrix. When the inclusions are small, a two-scale Richards’ equation-based model has been proposed in the literature taking the form of an equation with effective parameters governing the macroscopic flow coupled with a microscopic equation, defined at each point in the macroscopic domain, governing the flow in the inclusions. This paper is devoted to a number of advances in the numerical implementation of this model. Namely, by treating the micro-scale as a two-dimensional problem, our solution approach based on a control volume finite element method can be applied to irregular inclusion geometries, and, if necessary, modified to account for additional phenomena (e.g. imposing the macroscopic gradient on the micro-scale via a linear approximation of the macroscopic variable along the microscopic boundary). This is achieved with the help of an exponential integrator for advancing the solution in time. This time integration method completely avoids generation of the Jacobian matrix of the system and hence eases the computation when solving the two-scale model in a completely coupled manner. Numerical simulations are presented for a two-dimensional infiltration problem.

Dynamics of ribonuclease A and ribonuclease S: Computational and experimental studies

RNase S is a complex consisting of two proteolytic fragments of RNase A: the S peptide (residues 1-20) and S protein (residues 21-124). RNase S and RNase A have very similar X-ray structures and enzymatic activities. previous experiments have shown increased rates of hydrogen exchange and greater sensitivity to tryptic cleavage for RNase S relative to RNase A. It has therefore been asserted that the RNase S complex is considerably more dynamically flexible than RNase A. In the present study we examine the differences in the dynamics of RNaseS and RNase A computationally, by MD simulations, and experimentally, using trypsin cleavage as a probe of dynamics. The fluctuations around the average solution structure during the simulation were analyzed by measuring the RMS deviation in coordinates. No significant differences between RNase S and RNase A dynamics were observed in the simulations. We were able to account for the apparent discrepancy between simulation and experiment by a simple model, According to this model, the experimentally observed differences in dynamics can be quantitatively explained by the small amounts of free S peptide and S protein that are present in equilibrium with the RNase S complex. Thus, folded RNase A and the RNase S complex have identical dynamic behavior, despite the presence of a break in polypeptide chain between residues 20 and 21 in the latter molecule. This is in contrast to what has been widely believed for over 30 years about this important fragment complementation system.