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检索条件"任意字段=IEEE Computational Systems Bioinformatics Conference"

共 879 条记录，以下是321-330 订阅

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A profile of today's SBML-compatible software

A profile of today's SBML-compatible software

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7th ieee International conference on e-Science Workshops, eScienceW 201

作者： Hucka, Michael Bergmann, Frank T. Keating, Sarah M. Smith, Lucian P. California Institute of Technology Pasadena CA United States EMBL European Bioinformatics Institute Wellcome Trust Genome Campus Hinxton Cambridge United Kingdom University of Washington Seattle WA United States

ISBN: (纸本)9780769545981

computational systems biologists today have a healthy selection of software resources to help them do research. Many software packages, especially those concerned with computational modeling, have adopted SBML (the systems Biology Markup Language) as a machine-readable format to permit users to exchange models. Our group has a keen interest in understanding the landscape of SBML support. To help us ascertain the state of modern SBML-compatible software, in mid-2011 we initiated a survey of software packages that support SBML. Here we report the preliminary survey results. Based on 81 packages for which we have data so far, we summarize the trends in six areas: (1) What are the major types of functionality offered by the software systems? (2) What mathematical frameworks do they support? (3) What are their SBML-specific capabilities? (4) What other standards do they support besides SBML? (5) What are their characteristics with respect to run-time environments? And finally, (6) what are the availability and licensing terms? © 2011 ieee.

关键词： Data handling

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HPC selection of models of DNA substitution 11

HPC selection of models of DNA substitution

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9th International conference on computational Methods in systems Biology, CMSB'11

作者： Darriba, Diego Taboada, Guillermo L. Doallo, Ramón Posada, David Computer Architecture Group University of A Coruña 15071 A Coruña Spain Bioinformatics and Molecular Evolution Group University of Vigo 36310 Vigo Spain

ISBN: (纸本)9781450308175

Statistical model selection has become an essential step for the estimation of phylogenies from DNA sequence alignments. The program jModelTest offers different strategies to identify best-fit models for the data at hand, but for large DNA alignments, this task can demand vast computational resources. This paper presents a High Performance Computing (HPC) adaptation of jModelTest for shared memory multi-core systems and distributed memory cluster platforms. The performance evaluation of this HPC version on a shared memory system and on a cluster shows significant performance advantages, with speedups up to 39. This could represent a reduction in the execution time of some analyses from almost one day to half an hour. © 2011 ACM.

关键词： Message passing

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The First ieee conference on Healthcare Informatics, Imaging, and systems Biology HISB'11 INTRODUCTION

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JOURNAL OF bioinformatics AND computational BIOLOGY 2011年第5期9卷 V-VI页

作者： Chen, Xue-Wen Miyano, Satoru

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Sequencing and disease variation detection tools and techniques

Sequencing and disease variation detection tools and techniq...

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9th ACS/ieee International conference on Computer systems and Applications, AICCSA 2011

作者： DeLuca, Adam P. Wagner, Alex H. Taylor, Kyle R. Faga, Ben Thole, David Sheffield, Val C. Stone, Edwin M. Casavant, Thomas L. Scheetz, Todd E. Braun, Terry A. Center for Bioinformatics and Computational Biology University of Iowa Iowa City IA United States Howard Hughes Medical Institute Iowa City IA United States

ISBN: (纸本)9781457704741

Next-generation sequencing technology provides greater sequencing capacity to identify disease-causing variations. Currently there are many alignment tools and variation detection techniques, multiple SNP data sets used to filter out benign polymorphisms with the intent of enriching for disease-causing variations, and many tools and websites for annotating variations and performing pathogenicity prediction of variations. There is no consensus or standard with regards to which tools and corresponding parameter settings for each tool is appropriate for the different application of next-generation sequencing technologies for disease-causing variation identification. We have implemented an annotation pipeline that can easily use the output from different alignment tools (BLAT, BWA, BFAST, Bowtie) typically used to align sequence from next-generation sequencing and Sanger sequencing experiments. The Automated Sequence Analysis Pipeline (ASAP) reports variations using the HGVS standardized nomenclature[1] to facilitate comparison across tools and publications. To date, we have annotated the sequence from 13 exomes in an effort to identify disease-causing mutations. © 2011 ieee.

关键词： Pipelines

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Scaling HMMER performance on multicore architectures

Scaling HMMER performance on multicore architectures

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5th International conference on Complex, Intelligent and Software Intensive systems, CISIS 2011

作者： Isaza, Sebastian Houtgast, Ernst Sanchez, Friman Ramirez, Alex Gaydadjiev, Gergi Computer Engineering Laboratory Delft University of Technology Netherlands Computer Architecture Department Technical University of Catalonia Spain Barcelona Supercomputing Center Spain

ISBN: (纸本)9780769543734

In bioinformatics, protein sequence alignment is one of the fundamental tasks that scientists perform. Since the growth of biological data is exponential, there is an ever-increasing demand for computational power. While current processor technology is shifting towards the use of multicores, the mapping and parallelization of applications has become a critical issue. In order to keep up with the processing demands, applications' bottlenecks to performance need to be found and properly addressed. In this paper we study the parallelism and performance scalability of HMMER, a bioinformatics application to perform sequence alignment. After our study of the bottlenecks in a HMMER version ported to the Cell processor, we present two optimized versions to improve scalability in a larger multicore architecture. We use a simulator that allows us to model a system with up to 512 processors and study the performance of the three parallel versions of HMMER. Results show that removing the I/O bottleneck improves performance by 3X and 2.4X for a short and a long HMM query respectively. Additionally, by offloading the sequence pre-formatting to the worker cores, larger speedups of up to 27X and 7X are achieved. Compared to using a single worker processor, up to 156X speedup is obtained when using 256 cores. © 2011 ieee.

关键词： bioinformatics

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OntoHealth: A system to process ontologies applied to health pervasive environment

OntoHealth: A system to process ontologies applied to health...

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ieee International conference on Ubi-media Computing

作者： Librelotto, Giovani R. Freitas, Leandro O. Fiorin, André Mozzaquatro, Bruno A. Pasetto, Leandro Martini, Ricardo G. De Azevedo, Renato P. Pereira, Rafael T. PPGI/DELC - Technology Center Federal University of Santa Maria Santa Maria - RS Brazil Department of Bioinformatics University of Minho Braga Portugal

ISBN: (纸本)9780769544939

In the last years ontologies are being used in the development of pervasive computing applications. It is habitual their use for facilitating the interoperability among context-aware applications and the entities that may enter in the context at any time. This paper presents OntoHealth: a system to process ontologies applied to health pervasive environment. The main idea is that a hospital could be seen as this pervasive environment, where someone, through ubiquitous computing, engages a range of computational devices and systems simultaneously, in the course of ordinary activities, and may not necessarily even be aware that they are doing so. With the proposed ontology and the tool for its processing, the medical tasks can be shared by all components of this pervasive environment. © 2011 ieee.

关键词： Ontology

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Non linear modeling of cell survival/death using artificial neural network

Non linear modeling of cell survival/death using artificial ...

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2011 International conference on computational Intelligence and Communication systems, CICN 2011

作者： Jain, Shruti Naik, Pradeep K. Bhooshan, Sunil V. Department of Electronics and Communication Engineering Jaypee University of Information Technology Solan-173215 India Department of Biotechnology and Bioinformatics Jaypee University of Information Technology Solan-173215 India

ISBN: (纸本)9780769545875

Signal transduction pathways control cellular responses to stimuli, but it is unclear how molecular information is processed as a network. Large-scale collection and systematization of such data is likely to have a great impact on cell biology as complete genome sequencing has had on genetics. Cell signaling pathways interact with one another to form networks. Such networks are complex in their organization and exhibit emergent properties such as bistability and ultra sensitivity. Analysis of signaling networks requires a combination of experimental and theoretical approaches including the development and analysis of models. This work examines signaling networks that control the survival decision treated with combinations of the pro-death cytokine, tumor necrosis factor-α (TNF), and the pro-survival growth factors, epidermal growth factor (EGF) and insulin. A non linear model using Artificial Neural Network was proposed for cell survival/ death. With this we have made software which is used by doctors in doing chemotherapy without doing any experiments. © 2011 ieee.

关键词： Neural networks

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Biclustering and classification analysis in gene expression using nonnegative matrix factorization on multi-GPU systems

Biclustering and classification analysis in gene expression ...

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2011 11th International conference on Intelligent systems Design and Applications, ISDA'11

作者： Mejía-Roa, E. García, C. Gómez, J.I. Prieto, M. Tirado, F. Nogales, R. Pascual-Montano, A. Madrid 28040 Spain Functional Bioinformatics Group Biocomputing Unit National Center for Biotechnology-CSIC Madrid 28049 Spain

ISBN: (纸本)9781457716751

A great interest has been given to the Nonnegative Matrix Factorization (NMF) technique due to its ability of extracting highly-interpretable parts from data sets. Gene expression analysis is one of the most popular applications of NMF in bioinformatics. Nonetheless, its usage is hindered by the computational complexity when processing large data sets. In this paper, we present two parallel implementations of NMF. The first version uses CUDA on a Graphics Processing Unit (GPU). Large input matrices are iteratively blockwise transferred and processed. The second implementation distributes data among multiple GPUs synchronized through MPI (Message Passing Interface). When analyzing large data sets with two and four GPUs, it performs respectively, 2.3 and 4.13 times faster than the single-GPU version. This represents about 120 times faster than a conventional CPU. These super linear speedups are achieved when data portions assigned to each GPU are small enough to be transferred only once. © 2011 ieee.

关键词： Graphics processing unit

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Towards a pervasive computing enabled modeling environment for integrated coevolving energy systems

Towards a pervasive computing enabled modeling environment f...

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2011 EPU-CRIS International conference on Science and Technology, EPU-CRIS 2011

作者： Marathe, Achla Marathe, Madhav V. Kumar, V. S. Anil Network Dynamics and Simulation Science Laboratory Virginia Bioinformatics Institute Virginia Tech. Blacksburg VA 24061 United States

ISBN: (纸本)9783940961693

We present elements of a pervasive computing enabled modeling environment for integrated national energy systems (CI-MINES) to support policy and decision making as it pertains to co-evolving socio-energy systems. Decision support systems built using CI-MINES will provide public policy makers as well as private stakeholders entirely new ways to design and architect next-generation energy systems. When complete, CI-MINES can be used to evaluate the relative merits of competing conceptual architectures for interactive energy grids and markets before substantial investment is made in realizing them. It will also help evaluate new ways to invest in renewable energy sources and assess the reliability and security of the emerging grid architectures. CI-MINES is based on recent computational advances for modeling extremely large, complex, multi-scale socio-technical systems. © 2011 CRIS.

关键词： Decision support systems

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Discriminative random field approach to prediction of protein residue contacts

Discriminative random field approach to prediction of protei...

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5th ieee International conference on systems Biology, ISB 2011

作者： Kamada, Mayumi Hayashida, Morihiro Song, Jiangning Akutsu, Tatsuya Bioinformatics Center Institute for Chemical Research Kyoto University Gokasho Uji 611-0011 Japan Department of Biochemistry and Molecular Biology Monash University Clayton VIC 3800 Australia Tianjin Institute of Industrial Biotechnology Chinese Academy of Sciences Tianjin 300308 China

ISBN: (纸本)9781457716669

Understanding of interactions of proteins is important to reveal networks and functions of molecules. Many investigations have been conducted to analyze interactions and contacts between residues. It is supported that residues at interacting sites have co-evolved with those at the corresponding residues in the partner protein to keep the interactions between the proteins. Therefore, mutual information (MI) between residues calculated from multiple sequence alignments of homologous proteins is considered to be useful for identifying contact residues in interacting proteins. In our previous work, we proposed a prediction method for protein-protein interactions using mutual information and conditional random fields (CRFs), and confirmed its usefulness. The discriminative random field (DRF) is a special type of CRFs, and can recognize some specific characteristic regions in an image. Since the matrix consisted of mutual information between residues in two interacting proteins can be regarded as an image, we propose a prediction method for protein residue contacts using DRF models with mutual information. To validate our method, we perform computational experiments for several interactions between Pfam domains. The results suggest that the proposed DRF-based method with MI is useful for predicting protein residue contacts compared with that using the corresponding Markov random field (MRF) model. © 2011 ieee.

关键词： Proteins

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