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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411-420 订阅

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A study of information diffusion over a realistic social network model

A study of information diffusion over a realistic social net...

引用

2009 ieee International conference on Social Computing, SocialCom 2009

作者： Apolloni, Andrea Channakeshava, Karthik Durbeck, Lisa Khan, Maleq Kuhlman, Chris Lewis, Bryan Swarup, Samarth Network Dynamics and Simulation Science Laboratory Virginia Bioinformatics Institute Virginia Tech Blacksburg United States

ISBN: (纸本)9780769538235

Sociological models of human behavior can explain population-level phenomena within social systems;computer modeling can simulate a wide variety of scenarios and allow one to pose and test hypotheses about the social system. In this paper, we model and examine the spread of information through personal conversations in a simulated socio-technical network that provides a high degree of realism and a great deal of captured detail. To our knowledge this is the first time information spread via conversation has been modeled against a statistically accurate simulation of people's daily interactions within a specific urban or rural environment, capturing the points in time and space at which two people could converse, and providing a realistic basis for modeling human behavior during face-to-face interaction. We use a probabilistic model to decide whether two people will converse about a particular topic based on their similarity and familiarity. Similarity is modeled by matching selected demographic characteristics, while familiarity is modeled by the amount of contact required to convey information. We report our findings on the effects of familiarity and similarity on the spread of information over the social network. We resolve the results by age group, daily activities, time, household income, household size and examine the relative effect of these factors. For informal topics where little familiarity is required, shopping and recreational activities predominate;otherwise, home, work, and school predominate. We find that youths play a significant role in spreading information through a community rapidly, mainly through interactions in schools and recreational activities. © 2009 ieee.

关键词： Behavioral research

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A GA-SVM feature selection model based on high performance computing techniques

A GA-SVM feature selection model based on high performance c...

引用

ieee International conference on systems, Man and Cybernetics

作者： Tianyou Zhang Xiuju Fu Rick Siow Mong Goh Chee Keong Kwoh Gary Kee Khoon Lee Institute of High Performance Computing Singapore Nanyang Technological University Singapore

Supervised learning is well-known and widely applied in many domains including bioinformatics, cheminformatics and financial forecasting. However, the interference from irrelevant features may lead to the poor accuracy of classifiers. As a popular feature selection model, GA-SVM is desirable in many of those cases to filter out irrelevant features and improve the learning performance subsequently. However, the high computational cost strongly discourages the application of GA-SVM in large-scale datasets. In this paper, an HPC-enabled GA-SVM (HGA-SVM) is proposed by integrating data parallelization, multithreading and heuristic techniques with the ultimate goal of robustness and low computational cost. Our proposed model is comprised of four improvement strategies: 1) GA parallelization, 2) SVM parallelization, 3) neighbor search and 4) evaluation caching. All the four strategies improve various aspects of the feature selection model and contribute collectively towards higher computational throughput.

关键词： Genetic algorithms Support vector machines High performance computing computational efficiency Supervised learning bioinformatics Interference Filters Large-scale systems Multithreading

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Exploratory Analysis of Protein Translation Regulatory Networks Using Hierarchical Random Graphs

Exploratory Analysis of Protein Translation Regulatory Netwo...

引用

ieee International conference on bioinformatics and Biomedicine (BIBM)

作者： Daniel Duanqing Wu Xiaohua Hu Tingting He College of Information Science and Technology Drexel University Philadelphia PA USA Department of Computer Science Central China Normal University Wuhan Hubei China

Protein translation is a vital cellular process for any living organism. The availability of interaction databases provides an opportunity for researchers to exploit the immense amount of data in silico such as studying biological networks. There has been an extensive effort using computational methods in deciphering the transcriptional regulatory networks. However, research on translation regulatory networks has caught little attention in the bioinformatics and computational biology community. In this paper, we present an exploratory analysis of yeast protein translation regulatory networks using hierarchical random graphs. We derive a protein translation regulatory network from a protein-protein interaction dataset. Using a hierarchical random graph model, we show that the network exhibits well organized hierarchical structure. In addition, we apply this technique to predict missing links in the network. The results have potential implications for better understanding mechanisms of translational control from a system's perspective.

关键词： Proteins Organisms Databases Biology computing Computer networks bioinformatics computational biology Fungi Biological system modeling Control systems

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computational testing of protein-protein interactions

Computational testing of protein-protein interactions

引用

ieee International conference on bioinformatics and Biomedicine Workshops (BIBMW)

作者： Ataur R. Katebi Andrzej Kloczkowski Robert L. Jeringan L.H. Baker Center for Bioinformatics and Biological Statistics Iowa State University Ames Iowa USA Iowa State University Ames IA US

Abundant protein interaction data are currently available. These interaction networks are important sources of information about how biological systems function. In the present work the yeast protein interaction network is clustered and the individual clusters are investigated for functional relationships among the member proteins. 3D structural models of the proteins in a cluster have been built. We investigate the docking of proteins within the cluster, verifying reported and predicting some unreported interactions.

关键词： Testing Proteins Fungi Matrix decomposition Information resources Data mining Clustering methods Biology computing bioinformatics Statistics

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Integration of parallel EPSO and variable TS for unit commitment with nonsmooth fuel cost functions

Integration of parallel EPSO and variable TS for unit commit...

引用

2009 15th International conference on Intelligent System Applications to Power systems, ISAP '09

作者： Mori, Hiroyuki Okawa, Kenta Department of Electronics and Bioinformatics Meiji University Kawasaki 214-857 Japan

ISBN: (纸本)9781424450985

In this paper, a new hybrid meta-heuristic method is proposed to solve a unit commitment (UC) problem with nonsmooth fuel cost functions effectively. The proposed method focuses on global optimization in a sense that a generation company need carry out the cost reduction under competitive environment. The proposed method integrates parallel Evolutionary Particle Swarm Optimization (PEPSO) with variable neighborhood tabu search (VTS). The objective of UC is to minimize operation-cost while satisfying the constraints. The unit commitment problem is hard to solve due to the complexity in determining on-off conditions and output of generators. The problem formulation may be written as a nonlinear mixedinteger problem. In addition, large steam turbine generators with nonsmooth fuel cost functions are considered from a realistic standpoint. This paper proposes a new hybrid meta-heuristic method that combines VTS with PEPSO and evaluates solutions with two layers. Layer 1 determines the on-off conditions of generators with VTS while Layer 2 evaluates output of generators with PEPSO. TS is very effective for solving a combinatorial optimization problem efficiently. EPSO has better performance in dealing with an optimization problem of continuous variables. However, both methods still have room to improve solution quality and reduce computational time. Therefore, TS is improved to include the technique of the priority list limit and variable neighborhood search and EPSO is enhanced by the parallel scheme with the island model. The effectiveness of the proposed method is successfully applied to sample systems. © 2009 ieee.

关键词： Global optimization

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Towards a Better Ranking for Biomedical Information Retrieval Using Context

Towards a Better Ranking for Biomedical Information Retrieva...

引用

ieee International conference on bioinformatics and Biomedicine (BIBM)

作者： Xiaoshi Yin Xiangji Huang Zhoujun Li College of Computer Science and Engineering Beihang University Beijing China School of Information Technology York University Toronto Canada

In this paper, we present a context-sensitive approach for re-ranking retrieved documents for further improving the effectiveness of high-performance biomedical literature retrieval systems. For each topic, a two-dimensional context is learnt from the top N and the last N' documents in initial retrieval ranked list, which contains lexical context and conceptual context. The probabilities that retrieved documents are generated within the contextual space are then computed for document re-ranking. Empirical evaluation on the TREC Genomics full-text collection and two strong biomedical literature retrieval runs demonstrates that the context-sensitive re-ranking approach yields better retrieval performance.

关键词： Information retrieval Feedback bioinformatics Genomics Unified modeling language Databases Computer science Biomedical engineering Information technology computational geometry

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Prediction of non-classical secreted proteins using informative physicochemical properties

Prediction of non-classical secreted proteins using informat...

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The International conference on computational and System Biology 2009(ieee计算生物与系统生物国际会议)(iCCSB2009)

作者： Chiung-Hui Hung Kai-Ti Hsu Hui-Ling Huang Shinn-Ying Ho The Institute of Bioinformatics and Systems Biology the National Chiao Tung UniversityHsinchuTaiwan The Institute of Bioinformatics and Systems BiologyDepartment of Biological Science and Technologythe National Chiao Tung UniversityHsinchuTaiwan

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An improving gene selection for microarray data

An improving gene selection for microarray data

引用

ieee International conference on Fuzzy systems (FUZZ-ieee)

作者： Chou-Yuan Lee Zne-Jung Lee Yu-Lin Weng Department of Information Management Lan Yang Institute of Technology Taiwan Department of Information Management Huafan University Taiwan Department of Information Management Nursing and Management College Taiwan

The microarray data consists of tens of thousands of genes on a genomic scale. To avoid higher computational complexity, it needs gene selection to find the gene subsets that are able to explain the disease. In this paper, an improving gene selection for microarray data is proposed. In the proposed algorithm, scatter search is used to obtain suitable parameter settings for support vector machine and then a subset of beneficial genes is selected. These selected genes can increase the accuracy of classification for microarray data. From experimental results, it shows that the proposed algorithm can obtain a better parameter setting and reduce unnecessary genes.

关键词： Support vector machines Support vector machine classification Scattering parameters Lagrangian functions Polynomials Equations Genomics bioinformatics computational complexity Diseases

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Using clouds for metagenomics: A case study

Using clouds for metagenomics: A case study

引用

ieee International conference on Cluster Computing

作者： Jared Wilkening Andreas Wilke Narayan Desai Folker Meyer Mathematics and Computer Science Division Argonne National Laboratory Argonne IL USA

Cutting-edge sequencing systems produce data at a prodigious rate; and the analysis of these datasets requires significant computing resources. Cloud computing provides a tantalizing possibility for on-demand access to computing resources. However, many open questions remain. We present here a performance assessment of BLAST on real metagenomics data in a cloud setting in order to determine the viability of this approach. BLAST is one of the premier applications in bioinformatics and computational biology and is assumed to consume the vast majority of resources in that area.

关键词： Cloud computing DNA bioinformatics Genomics Biology computing Sequences Organisms Data analysis Costs Laboratories

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Assessment of Gene Annotation Accuracy by Inferring Transcripts from RNA-Seq

Assessment of Gene Annotation Accuracy by Inferring Transcri...

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ieee International conference on bioinformatics and Biomedicine (BIBM)

作者： Jeffrey Martin Wenhan Zhu Nicholas Bergman Mark Borodovsky School of Biology Georgia Institute of Technology Atlanta GA USA Wallace H. Coulter Department of Biomedical Engineering Computational Science and Engineering Division College of Computing Georgia Institute of Technology Atlanta GA USA

Next generation sequencing is quickly changing long standing paradigms of genomics in terms of what is feasible to accomplish within a ldquoresearch life timerdquo and what is supposed to remain beyond limits of reliable experimental analysis. Sequencing and mapping of a prokaryote transcriptome can provide experimental validation for computationally predicted genes annotated in a prokaryotic genome. In this study we use the transcriptome sequencing to assess the accuracy of the public annotation of genes in a genome of important pathogen Bacillus anthracis. We show that the transcriptome data confirm existence of a number of genes missing in the annotation. Also, the transcriptome data indicate that pseudogenes, genes with frameshifts and in frame stop codons, do keep the transcriptional activity (while possessing a coding potential as well) and continue to present a challenge for accurate annotation.

关键词： bioinformatics Genomics Hidden Markov models Solids Biology computing Biomedical engineering RNA Gene expression systems biology Laboratories

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