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检索条件"任意字段=Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004"

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The application of grid technology in systems biology: parameter estimation

The application of grid technology in systems biology: param...

引用

International conference on High Performance Computing in the Asia-Pacific Region

作者： P.K. Dhar Bioinformatics Institute Singapore Adjunct Faculty Department of Biochemistry National University of Singapore Singapore

The systems biology is a recent scientific discipline that arose from the need to combine biology with mathematics, physics, chemistry and computer science. Partly driven by the availability of a morass of data and partly driven by the availability of computational resources, the field of systems biology was reborn few years ago. Recently, a number of computational methods have been developed to model cellular pathways and networks. One of the major issues in building mathematical models of cellular processes is the difficulty of estimating parameters. Due to a wide numerical range within which parameters operate, it takes a large number of iterations to find the biologically relevant values. In This work the author describes how grid technology can be used to salvage this situation and help in building robust in-silico models.

关键词： systems biology Parameter estimation Availability Biology computing Biological system modeling Application software Chemical technology Cells (biology) Mathematics Physics

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Parallelization of Bayesian network based SNPs pattern analysis and performance characterization on SMP/HT

Parallelization of Bayesian network based SNPs pattern analy...

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International conference on Parallel and Distributed systems (ICPADS)

作者： J. Song E. Li Wei Hu S. Ge Chunrong Lai Yimin Zhang Xuegong Zhang Wenguang Chen Weimin Zheng Corporate Technology Group Intel Corporation USA MOE Key Laboratory of Bioinformatics / Department of Automation Tsinghua University Beijing China MOE Key Laboratory of Bioinformatics / Department of Computer Science and Technology Tsinghua University Beijing China

Single nucleotide polymorphisms (SNPs) is subtle variation in a genomic DNA sequence of individuals of the same species. It plays a key role in the pharmaceutical industry to understand variations in drug treatment responses between individuals at the molecular level. Discovering patterns around SNPs loci is very important for better understanding the possible origin of SNPs in evolution. Bayesian network has been applied to this problem and got promising results. Since Bayesian network based SNPs pattern analysis demonstrates high computational complexity, we parallelized this workload on Intel Xeon SMP systems. SNPs' task level parallelism is exploited. Experiment results show that memory is bottleneck: on 8-way Xeon SMP hyper-threading enabled system, system memory bandwidth is fully saturated and memory load access latency is roughly 50% longer than on single processor system. Another interesting result is that Intel's hyper-threading technology helps improve the multithreaded workload's performance by 1.6X speedup. Workload profiling shows that parallel SNPs' data sharing nature matches hyper-threading's cache sharing mechanism, and thus greatly reduces cache coherency protocol traffic on shared front side bus. Scalability analysis shows that imbalance and locks are two major factors that may limit the parallel workload speedup on more processor platforms.

关键词： Bayesian methods Pattern analysis Genomics bioinformatics DNA Sequences Pharmaceuticals Drugs computational complexity Parallel processing

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Domain specific languages for cellular interactions

Domain specific languages for cellular interactions

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Annual International conference of the ieee Engineering in Medicine and Biology Society (EMBC)

作者： W.L. Harrison R.W. Harrison Department of Computer Science University of Missouri Columbia Columbia MO USA Departments of Computer Science & Biology Georgia State University Atlanta GA USA

bioinformatics is the application of computer science techniques to problems in biology, and this paper explores one such application with great potential: the modeling of life cycles of autonomous, intercommunicating cellular systems using domain-specific programming languages (DSLs). We illustrate this approach for the simple photo-synthetic bacterium R. Sphaeroides with a DSL called CellSys embedded in the programming language Haskell.

关键词： Domain specific languages Application software Computer languages DSL bioinformatics Computer science Cells (biology) systems biology computational biology Biological system modeling

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Independent component analysis and scoring function based on protein interactions

Independent component analysis and scoring function based on...

引用

International ieee conference on Intelligent systems, IS

作者： K. Najarian A. Kedar R. Paleru A. Darvish R. Hakim Zadeh College of lnformation Technology University of North Carolina Charlotte USA Department of Physics and Optical Science University of North Carolina Charlotte Charlotte NC USA

We describe an approach for discovering biological gene clusters from gene expression data of DNA microarray and scoring the genes based on protein interaction data. Our approach is based on the assumption that many clusters exhibit two properties, i.e., their genes exhibit a similar gene expression profile and the protein products of the genes often interact. Our approach to clustering is based on the independent component analysis model, which uses the ICA algorithm and our approach to scoring is based on number of protein product interactions of the genes within a cluster. We present the results on Saccharomyces cerevisiae gene expression dataset combined with a binary protein interaction data set.

关键词： Independent component analysis Proteins Gene expression DNA Biological information theory Clustering algorithms Genomics bioinformatics Electronics packaging Data mining

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Feature selection for classifying high-dimensional numerical data

Feature selection for classifying high-dimensional numerical...

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conference on Computer Vision and Pattern Recognition (CVPR)

作者： Yimin Wu Aidong Zhang Department of Computer Science and Engineering Suny at Buffalo USA

Classifying high-dimensional numerical data is a very challenging problem. In high dimensional feature spaces, the performance of supervised learning methods suffers from the curse of dimensionality, which degrades both classification accuracy and efficiency. To address this issue, we present an efficient feature selection method to facilitate classifying high-dimensional numerical data. Our method employs balanced information gain to measure the contribution of each feature (for data classification); and it calculates feature correlation with a novel extension of balanced information gain. By integrating feature contribution and correlation, our feature selection approach uses a forward sequential selection algorithm to select uncorrelated features with large balanced information gain. Extensive experiments have been carried out on image and gene microarray datasets to demonstrate the effectiveness and robustness of the presented method.

关键词： Feedback Supervised learning Training data Filters Information retrieval Gain measurement Pattern recognition Multimedia systems bioinformatics Uncertainty

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Asynchronous HMM with applications to speech recognition

Asynchronous HMM with applications to speech recognition

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International conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： A. Garg S. Balakrishnan S. Vaithyanathan IBM Almaden Research Center San Jose CA USA

We develop a novel formalism for modeling speech signals which are irregularly or incompletely sampled. This situation can arise in real world applications where the speech signal is being transmitted over an error prone channel where parts of the signal can be dropped. Typical speech systems based on hidden Markov models, cannot handle such data since HMMs rely on the assumption that observations are complete and made at regular intervals. We introduce the asynchronous HMM, a variant of the inhomogeneous HMM commonly used in bioinformatics, and show how it can be used to model irregularly or incompletely sampled data. A nested EM algorithm is presented in brief which can be used to learn the parameters of this asynchronous HMM. Evaluation on real world speech data, which has been modified to simulate channel errors, shows that this model and its variants significantly outperform the standard HMM and methods based on data interpolation.

关键词： Hidden Markov models Speech recognition Interpolation bioinformatics Random variables Speech analysis computational modeling Computer errors Computer vision Text analysis

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International conference on Application Specific systems (ASAP), Architectures and Processors

作者： P. Krishnamurthy J. Buhler R. Chamberlain M. Franklin M. Gyang J. Lancaster Department of Computer Science and Engineering Washington University Saint Louis USA

Biosequence similarity search is an important application in modern molecular biology. Search algorithms aim to identify sets of sequences whose extensional similarity suggests a common evolutionary origin or function. The most widely used similarity search tool for biosequences is BLAST, a program designed to compare query sequences to a database. Here, we present the design of BLASTN, the version of BLAST that searches DNA sequences, on the Mercury system, an architecture that supports high-volume, high-throughput data movement off a data store and into reconfigurable hardware. An important component of application deployment on the Mercury system is the functional decomposition of the application onto both the reconfigurable hardware and the traditional processor. Both the Mercury BLASTN application design and its performance analysis are described.

关键词： Sequences Hardware Databases Application software DNA Genomics bioinformatics Computer architecture Read-write memory Evolution (biology)

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Implementation of protein tertiary structure prediction system with NetSolve

Implementation of protein tertiary structure prediction syst...

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International conference on High Performance Computing in the Asia-Pacific Region

作者： Y. Tanimura K. Aoi T. Hiroyasu M. Miki Y. Okamoto J. Dongarra Graduate Student of Engineering Doshisha University Japan Department of Engineering Doshisha University Japan Department of Theoretical Studies Okazaki National Research Institute Japan Department of Computer Science University of Tennessee USA

In this study, the protein tertiary structure prediction systems on the grid are proposed for progress of the bioinformatics. The prediction is mainly performed by the protein energy minimization. However, this method has many iterated calculation of the protein energy in most cases. To use the grid as the large-scale computing environment would be valuable for this system. In the system, parallel simulated annealing using genetic crossover (PSA/GAc) is a minimization engine and NetSolve is a basic tool to use the grid. In this study, two types of implementations are prepared. The first naive implementation of the system has a critical overhead due to large communication delay over the Internet. The second system, asynchronous crossover model, improves the performance in the second implementation. The details of the system and the experimental results solving C-peptide are shown as an example of grid application.

关键词： Proteins bioinformatics Large-scale systems Grid computing computational modeling Simulated annealing Genetics Search engines Delay Internet

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Improvements in distance-based indexing

Improvements in distance-based indexing

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International Working conference on Scientific and Statistical Database Management

作者： M. Tasan Z.M. Ozsoyoglu Electrical Engineering and Computer Science Center for Computational Genomics Case Western Reserve University Cleveland OH USA

This work offers some improvements in the current distance-based indexing techniques. An optimal similarity search algorithm that is adopted from vector-based indexing is shown to be also optimal for distance-based indices. Farther similarity between the two types of indexing is revealed, leading to a general description of search structures. A probabilistic analysis of distance-based tree indices is also shown to be possible, allowing direct comparisons of structures without the need for extensive experimentation. This analysis will lend itself to future improved index construction algorithms.

关键词： Indexing Computer science Genomics bioinformatics Algorithm design and analysis Spatial databases Shape Multidimensional systems Image databases Clustering methods

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Families of FPGA-based algorithms for approximate string matching

Families of FPGA-based algorithms for approximate string mat...

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International conference on Application Specific systems (ASAP), Architectures and Processors

作者： T. Van Court M.C. Herbordt ECE Department Boston University USA

Dynamic programming for approximate string matching is a large family of different algorithms, which vary significantly in purpose, complexity, and hardware utilization. Many implementations have reported impressive speed-ups, but have typically been point solutions -highly specialized and addressing only one or a few of the many possible options. The problem to be solved is creating a hardware description that implements a broad range of behavioral options without losing efficiency due to feature bloat. We report a set of three component types that address different parts of the DP string matching problem. Multiple, interchangeable implementations are available for each component type. This allows each application to choose the feature set required, then make maximum use of the FPGA fabric according to that application's specific resource requirements. Synthesis estimates show a 4:1 improvement in time-space performance, depending on the options chosen for a specific matching task.

关键词： Hardware Dynamic programming bioinformatics Sequences Field programmable gate arrays Fabrics Databases DNA Proteins Amino acids

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