Genome-wide computational identification of microRNAs and their targets in the deep-branching eukaryote Giardia lamblia

Using a combined computational program. we identified 50 potential microRNAs (miRNAs) in Giardia lamblia. one of the most primitive unicellular eukaryotes. These miRNAs are unique to G. lamblia and no homologues have been found in other organisms; miRNAs.

Computational mechanisms of sensorimotor control.

In order to generate skilled and efficient actions, the motor system must find solutions to several problems inherent in sensorimotor control, including nonlinearity, nonstationarity, delays, redundancy, uncertainty, and noise. We review these problems and five computational mechanisms that the brain may use to limit their deleterious effects: optimal feedback control, impedance control, predictive control, Bayesian decision theory, and sensorimotor learning. Together, these computational mechanisms allow skilled and fluent sensorimotor behavior.

Computational fluid-structure interaction of DGB parachutes in compressible fluid flow

This paper describes large-scale simulations of compressible flows over a supersonic disk-gap-band parachute system. An adaptive mesh refinement method is used to resolve the coupled fluid-structure model. The fluid model employs large-eddy simulation to describe the turbulent wakes appearing upstream and downstream of the parachute canopy and the structural model employed a thin-shell finite element solver that allows large canopy deformations by using subdivision finite elements. The fluid-structure interaction is described by a variant of the Ghost-Fluid method. The simulation was carried out at Mach number 1.96 where strong nonlinear coupling between the system of bow shocks, turbulent wake and canopy is observed. It was found that the canopy oscillations were characterized by a breathing type motion due to the strong interaction of the turbulent wake and bow shock upstream of the flexible canopy. Copyright © 2010 by ASME.

The assembly of computational models for the collaborative development of virtual prototypes

In the context of collaborative product development, new requirements need to be accommodated for Virtual Prototyping Simulation (VPS), such as distributed processing and the integration of models created using different tools or languages. Existing solutions focus mainly on the implementation of distributed processing, but this paper explores the issues of combining different models (some of which may be proprietary) developed in different software environments. In this paper, we discuss several approaches for developing VPS, and suggest how it can best be integrated into the design process. An approach is developed to improve collaborative work in a VPS development by combining disparate computational models. Specifically, a system framework is proposed to separate the system-level modeling from the computational infrastructure. The implementation of a simple prototype demonstrates that such a paradigm is viable and thus provides a new means for distributed VPS development. © 2009 by ASME.

BarraCUDA - a fast short read sequence aligner using graphics processing units.

BACKGROUND: With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence. FINDINGS: Using the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput. CONCLUSIONS: BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology.BarraCUDA is currently available from http://seqbarracuda.sf.net.

Comparative studies on parallel and antiparallel duplex and triplex DNA

Parallel strand models for base sequences d(A)(10). d(T)(10), d(AT)(5) . d(TA)(5), d(G(5)C(5)). d(C(5)G(5)), d(GC)(5) . d(CG)(5) and d(CTATAGGGAT). d(GATATCCCTA), where reverse Watson-Crick A-T pairing with two H-bonds and reverse Watson-Crick G-C pairing with one H-bond or with two H-bonds were adopted, and three models of d(T)(14). d(A)(14). d(T)(14) triple helix with different strand orientations were built up by molecular architecture and energy minimization. Comparisons of parallel duplex models with their corresponding B-DNA models and comparisons among the three triple helices showed: (i) conformational energies of parallel AT duplex models were a little lower, while for GC duplex models they were about 8% higher than that of their corresponding B-DNA models; (ii) the energy differences between parallel and B-type duplex models and among the three triple helices arose mainly from base stacking energies, especially for GC base pairing; (iii) the parallel duplexes with one H-bond G-C pairs were less stable than those with two H-bonds G-C pairs. The present paper includes a brief discussion about the effect of base stacking and base sequences on DNA conformations. (C) 1997 Academic Press Limited.