DecGPU: distributed error correction on massively parallel graphics processing units using CUDA and MPI

Background  

Next-generation sequencing technologies have led to the high-throughput production of sequence data (reads) at low cost. However, these reads are significantly shorter and more error-prone than conventional Sanger shotgun reads. This poses a challenge for the de novo assembly in terms of assembly quality and scalability for large-scale short read datasets.     

Accelerating reaction-diffusion simulations with general-purpose graphics processing units

SUMMARY: We present a massively parallel stochastic simulation algorithm (SSA) for reaction-diffusion systems implemented on Graphics Processing Units (GPUs). These are designated chips optimized to process a high number of floating point operations in parallel, rendering them well-suited for a range of scientific high-performance computations. Newer GPU generations provide a high-level programming interface which turns them into General-Purpose Graphics Processing Units (GPGPUs). Our SSA exploits GPGPU architecture to achieve a performance gain of two orders of magnitude over the fastest existing implementations on conventional hardware. AVAILABILITY: The software is freely available at http://www.csse.monash.edu.au/~berndm/inchman/.     

Smoldyn on graphics processing units: massively parallel Brownian dynamics simulations

Space is a very important aspect in the simulation of biochemical systems; recently, the need for simulation algorithms able to cope with space is becoming more and more compelling. Complex and detailed models of biochemical systems need to deal with the movement of single molecules and particles, taking into consideration localized fluctuations, transportation phenomena, and diffusion. A common drawback of spatial models lies in their complexity: models can become very large, and their simulation could be time consuming, especially if we want to capture the systems behavior in a reliable way using stochastic methods in conjunction with a high spatial resolution. In order to deliver the promise done by systems biology to be able to understand a system as whole, we need to scale up the size of models we are able to simulate, moving from sequential to parallel simulation algorithms. In this paper, we analyze Smoldyn, a widely diffused algorithm for stochastic simulation of chemical reactions with spatial resolution and single molecule detail, and we propose an alternative, innovative implementation that exploits the parallelism of Graphics Processing Units (GPUs). The implementation executes the most computational demanding steps (computation of diffusion, unimolecular, and bimolecular reaction, as well as the most common cases of molecule-surface interaction) on the GPU, computing them in parallel on each molecule of the system. The implementation offers good speed-ups and real time, high quality graphics output     

Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs)

Iterative reconstruction algorithms are becoming increasingly important in electron tomography of biological samples. These algorithms, however, impose major computational demands. Parallelization must be employed to maintain acceptable running times. Graphics Processing Units (GPUs) have been demonstrated to be highly cost-effective for carrying out these computations with a high degree of parallelism. In a recent paper by Xu et al. (2010), a GPU implementation strategy was presented that obtains a speedup of an order of magnitude over a previously proposed GPU-based electron tomography implementation. In this technical note, we demonstrate that by making alternative design decisions in the GPU implementation, an additional speedup can be obtained, again of an order of magnitude. By carefully considering memory access locality when dividing the workload among blocks of threads, the GPU’s cache is used more efficiently, making more effective use of the available memory bandwidth.     

A microcomputer program for hydropathic analysis of proteins with I/O through word processing and graphics software

A BASIC program has been devised for the hydropathic analysisof protein sequences according to the method of Kyte and Doolittle(1982). The program uses sequence data from input files thatare created with a word processor and produces two types ofoutput file: one contains a bar graph of the hydropathic profilein a format that can be easily edited; the other is a tabulationof hydropathic indices along a protein's sequence that can beused as input by the program for the production of a bar graphor as input into other graphics and analysis software. An MS-DOSmicrocomputer, operating under IBM BASICA or GWBASIC and a dotmatrix printer with block graphics capabilities are the onlyhardware requirements for graphic display of hydropathy profiles.The program is capable of unattended analysis from a list ofup to 15 input files. ; accepted on March 10, 1986     

Developing a multiscale, multi-resolution agent-based brain tumor model by graphics processing units

Background

Arsenic in drinking water, a major health hazard to millions of people in South and East Asia and in other parts of the world, is ingested primarily as trivalent inorganic arsenic (iAs), which then undergoes hepatic methylation to methylarsonic acid (MMAs) and a second methylation to dimethylarsinic acid (DMAs). Although MMAs and DMAs are also known to be toxic, DMAs is more easily excreted in the urine and therefore methylation has generally been considered a detoxification pathway. A collaborative modeling project between epidemiologists, biologists, and mathematicians has the purpose of explaining existing data on methylation in human studies in Bangladesh and also testing, by mathematical modeling, effects of nutritional supplements that could increase As methylation.

Methods

We develop a whole body mathematical model of arsenic metabolism including arsenic absorption, storage, methylation, and excretion. The parameters for arsenic methylation in the liver were taken from the biochemical literature. The transport parameters between compartments are largely unknown, so we adjust them so that the model accurately predicts the urine excretion rates of time for the iAs, MMAs, and DMAs in single dose experiments on human subjects.

Results

We test the model by showing that, with no changes in parameters, it predicts accurately the time courses of urinary excretion in mutiple dose experiments conducted on human subjects. Our main purpose is to use the model to study and interpret the data on the effects of folate supplementation on arsenic methylation and excretion in clinical trials in Bangladesh. Folate supplementation of folate-deficient individuals resulted in a 14% decrease in arsenicals in the blood. This is confirmed by the model and the model predicts that arsenicals in the liver will decrease by 19% and arsenicals in other body stores by 26% in these same individuals. In addition, the model predicts that arsenic methyltransferase has been upregulated by a factor of two in this population. Finally, we also show that a modification of the model gives excellent fits to the data on arsenic metabolism in human cultured hepatocytes.

Conclusions

The analysis of the Bangladesh data using the model suggests that folate supplementation may be more effective at reducing whole body arsenic than previously expected. There is almost no data on the upregulation of arsenic methyltransferase in populations chronically exposed to arsenic. Our model predicts upregulation by a factor of two in the Bangladesh population studied. This prediction should be verified since it could have important public health consequences both for treatment strategies and for setting appropriate limits on arsenic in drinking water. Our model has compartments for the binding of arsenicals to proteins inside of cells and we show that these comparments are necessary to obtain good fits to data. Protein-binding of arsenicals should be explored in future biochemical studies.     

Scalable and highly parallel implementation of Smith-Waterman on graphics processing unit using CUDA

Program development environments have enabled graphics processing units (GPUs) to become an attractive high performance computing platform for the scientific community. A commonly posed problem in computational biology is protein database searching for functional similarities. The most accurate algorithm for sequence alignments is Smith-Waterman (SW). However, due to its computational complexity and rapidly increasing database sizes, the process becomes more and more time consuming making cluster based systems more desirable. Therefore, scalable and highly parallel methods are necessary to make SW a viable solution for life science researchers. In this paper we evaluate how SW fits onto the target GPU architecture by exploring ways to map the program architecture on the processor architecture. We develop new techniques to reduce the memory footprint of the application while exploiting the memory hierarchy of the GPU. With this implementation, GSW, we overcome the on chip memory size constraint, achieving 23× speedup compared to a serial implementation. Results show that as the query length increases our speedup almost stays stable indicating the solid scalability of our approach. Additionally this is a first of a kind implementation which purely runs on the GPU instead of a CPU-GPU integrated environment, making our design suitable for porting onto a cluster of GPUs.     

Indoor objects detection system implementation using multi-graphic processing units

Cluster Computing - Indoor objects detection and recognition plays an important role in computer science and artificial intelligence fields. This task plays also a crucial role especially for blind...     

Phylomat: an automated protein motif analysis tool for phylogenomics

Recent progress in genomics, proteomics, and bioinformatics enables unprecedented opportunities to examine the evolutionary history of molecular, cellular, and developmental pathways through phylogenomics. Accordingly, we have developed a motif analysis tool for phylogenomics (Phylomat, http://alg.ncsa.uiuc.edu/pmat) that scans predicted proteome sets for proteins containing highly conserved amino acid motifs or domains for in silico analysis of the evolutionary history of these motifs/domains. Phylomat enables the user to download results as full protein or extracted motif/domain sequences from each protein. Tables containing the percent distribution of a motif/domain in organisms normalized to proteome size are displayed. Phylomat can also align the set of full protein or extracted motif/domain sequences and predict a neighbor-joining tree from relative sequence similarity. Together, Phylomat serves as a user-friendly data-mining tool for the phylogenomic analysis of conserved sequence motifs/domains in annotated proteomes from the three domains of life.     

mmsearch: a motif arrangement language and search program.

This paper presents a language for describing arrangements of motifs in biological sequences, and a program that uses the language to find the arrangements in motif match databases. The program does not by itself search for the constituent motifs, and is thus independent of how they are detected, which allows it to use motif match data of various origins. AVAILABILITY: The program can be tested online at http://hits.isb-sib.ch and the distribution is available from ftp://ftp.isrec.isb-sib.ch/pub/software/unix/mmsearch-1.0.tar.gz CONTACT: Thomas.Junier@isrec.unil.ch SUPPLEMENTARY INFORMATION: The full documentation about mmsearchis available from http://hits.isb-sib.ch/~tjunier/mmsearch/doc.     

<Emphasis FontCategory="NonProportional">permGPU</Emphasis>: Using graphics processing units in RNA microarray association studies

Background  

Many analyses of microarray association studies involve permutation, bootstrap resampling and cross-validation, that are ideally formulated as embarrassingly parallel computing problems. Given that these analyses are computationally intensive, scalable approaches that can take advantage of multi-core processor systems need to be developed.     

重症监护病房脑膜脓毒金黄杆菌医院感染的调查分析

目的通过对重症监护病房（Intensive Care Unit,ICU）内脑膜脓毒金黄杆菌（Chryseobacterium meningosepticum）医院感染的临床特征和耐药性调查分析,为临床更好地预防和治疗该细菌所引起的感染提供参考。方法对我院2007年1月至2008年12月重症监护病房脑膜脓毒金黄杆菌医院感染的47例患者进行回顾性调查。结果45例（95．7％）患者均有严重的基础疾病,与感染相关的因素还包括侵入性操作、深静脉置管、环境污染及长期广谱抗菌药物的应用;47株脑膜脓毒金黄杆菌全部检测出金属β-内酰胺酶,具多重耐药性。体外抗菌活性较好的抗菌药物依次为万古霉素（100．0％）、头孢哌酮／舒巴坦（83．0％）、哌拉西林／他唑巴坦（57．1％）、替卡西林／克拉维酸（52．4％）和复方新诺明（45．2％）,其余所检测的抗菌药物体外抗菌活性均在6．4％-0。结论缩短住院时间、加强病区环境和空气监控、尽量减少侵入性操作和合理使用抗生素是减少脑膜脓毒金黄杆菌感染发生的重要措施。治疗脑膜脓毒金黄杆菌,可选用万古霉素、头孢哌酮／舒巴坦、哌拉西林／他唑巴坦、替卡西林／克拉维酸和复方新诺明。     

StatFingerprints: a friendly graphical interface program for processing and analysis of microbial fingerprint profiles

Molecular fingerprint methods are widely used to compare microbial communities in various habitats. The free program StatFingerprints can import, process, and display fingerprint profiles and perform numerous statistical analyses on them, and also estimate diversity indexes. StatFingerprints works with the free program R, providing an environment for statistical computing and graphics. No programming knowledge is required to use StatFingerprints, thanks to its friendly graphical user interface. StatFingerprints is useful for analysing the effect of a controlled factor on the microbial community and for establishing the relationships between the microbial community and the parameters of its environment. Multivariate analyses include ordination, clustering methods and hypothesis-driven tests like 50-50 multivariate analysis of variance, analysis of similarity or similarity percentage procedure and the program offers the possibility of plotting ordinations as a three-dimensional display.     

A program for reading DNA sequence gels using a small computer equipped with a graphics tablet.

A program has been written in BASIC that allows DNA sequence gels to be read by a Tektronix model 4052 computer equipped with a graphics tablet. Sequences from each gel are stored on tape for later transfer to a larger computer where they are melded into a complete overall sequence. The program should be adaptable to other small computers.     

Revealing signaling pathway deregulation by using gene expression signatures and regulatory motif analysis

Gene expression signatures consisting of tens to hundreds of genes have been found to be informative for different biological states. Recently, many computational methods have been proposed for biological interpretation of such signatures. However, there is a lack of methods for identifying cell signaling pathways whose deregulation results in an observed expression signature. We present a strategy for identifying such signaling pathways and evaluate the strategy using six human and mouse gene expression signatures.     

SCANGRAPH: a program for digitization of graphs using an image scanner

The program SCANGRAPH has been developed for vectorizing anydrawing or graph in the form of a single continuous line. Withthe use of the software, the raster image of a graph in theTIFF format as generated from an optical scanner or digitizingvideo system can be converted to the corresponding digitizedgraph with x and y coordinates given. The digitized data canbe output in the ASCII format for importing to other softwarepackages. Options for peak identification, data smoothing andcompression, and graph comparison are also provided for datamanipulation.