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

共 881 条记录，以下是461-470 订阅

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Database interoperability through Web Services and ontologies

Database interoperability through Web Services and ontologie...

引用

ieee Symposium on bioinformatics and Bioengineering (BIBE)

作者： Timos Sellis Dimitrios Skoutas Konstantinos Staikos Institute for the Management of Information Systems National and Technical University of Athens Athens Greece National and Technical University of Athens Athens Greece European Dynamics SA Athens Greece

This paper reports on efforts towards database integration and interoperability, based on Web services and ontologies. The development of Web services software for three biological institutes is discussed. The software was created considering three major biological institutes which possess databases with heterogeneous information. The goal was to make this information available over the Internet, in the form of Web services so that they can be used from other applications over the Web. Moreover, we discuss how to extend this functionality through the use of ontologies so as to allow for more effective and automatic data integration.

关键词： Databases Web services Ontologies bioinformatics Application software Web and internet services XML Access protocols computational biology Communication standards

来源：评论

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High-performance computing for drug design

High-performance computing for drug design

引用

ieee International conference on bioinformatics and Biomedicine Workshops (BIBMW)

作者： Mary Qu Yang Jack Y. Yang National Institutes of Health Bethesda MD US Harvard Medical School Harvard University Cambridge MA USA

High performance computing has become a major focus of attention by government, industry, medical centers and academic institutions. The U.S. government has made this a ldquotop national priorityrdquo, linking the development of a ldquodata superhighway systemrdquo to national competitiveness and national research interest. High performance supercomputing approaches have been used for sequence analysis, gene finding, protein structural prediction, all-atom simulation such as molecular dynamics and quantum calculations, modeling biological networks such as systems biology and more recently drug design and drug discovery. All these approaches are highly computationally demanding, in terms of compute load, communication speed, and memory load. Supercomputing based drug design and drug discovery use high-performance super-computers and bioinformatics approaches to discover, enhance, and study drugs and related biologically active molecules as well as the sites of protein interactions. Methods include molecular modeling using biophysical approaches such as molecular dynamics, semi-empirical quantum mechanics methods, ab initio quantum chemistry methods, density functional theory, receptor-ligand interactions and protein docking and so on. The success of the high-throughput drug design and drug discovery now directly relies on the high-performance computing capabilities. Many research and computational products that were used to be considered impossible now proved to be feasible and effective with the help of todaypsilas supercomputing techniques. In particular, the identification of diseases relating to protein structural changes challenges biomedicine as the result of the sophisticated protein interaction networks that demand effective drug design using supercomputing based on mathematical, computational and biophysical models and algorithms for solving the model equations, and the bioinformatics techniques to analyze and validate the results. Those will need our deeper

关键词： Drugs Proteins Biology computing Biological system modeling bioinformatics Biomedical computing Government computational modeling Predictive models Quantum mechanics

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Cancer classification by minimizing fuzzy scattering effect

Cancer classification by minimizing fuzzy scattering effect

引用

ieee International conference on Fuzzy systems (FUZZ-ieee)

作者： Tuan D. Pham Bioinformatics Applications Research Centre and the School of Mathematics Physics and Information Technology James Cook University QLD Australia

Proteomic technology has been found promising for classifying complex diseases that leads to early prediction. However, for effective classification, the extraction of good features that can represent the identities of different classes plays the frontal critical factor for any classification problems. In addition, another major problem associated with pattern recognition is how to effectively handle a large feature space. This paper addresses these two frontal issues for mass spectrometry (MS) classification. We apply the theory of linear predictive coding to extract features and fuzzy vector quantization to reduce the large feature space of MS data. The minimization of the fuzzy scattering matrix in the setting of the fuzzy c-means algorithm provides better grouping for feature classification. The proposed methodology was tested using two MS-based cancer datasets and the results are promising.

关键词： Cancer Classification algorithms Feature extraction Distortion measurement Spectroscopy Proteomics Signal processing algorithms

来源：评论

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A multiagent multicellular systems biology model of Trichoplax adhaerens

A multiagent multicellular systems biology model of Trichopl...

引用

ieee International conference on Electro-Information Technology

作者： Karl Altenburg Karthik Namasivayam Department of Accounting and Information Systems North Dakota State University Fargo ND USA Department of Computer Science and Operations Research North Dakota State University Fargo ND USA

We present an agent-based simulation model of the animal Trichoplax adhaerens (phylum: Placozoa). The model attempts to simulate the whole organism based on a cellular-level description. The question we wish to address is: How does whole organism morphology and behavior emerge from cellular activity? A prototype animal model was specified, designed and implemented. Cellular-level as was as animal-level behavior and morphology was demonstrated.

关键词： systems biology Biological system modeling Animals Object oriented modeling Cells (biology) Morphology bioinformatics computational biology Immune system Feeds

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In silico prediction of target SNPs affecting miR-mRNA interaction

In silico prediction of target SNPs affecting miR-mRNA inter...

引用

ieee International conference on bioinformatics and Biomedicine Workshops (BIBMW)

作者： Hao Sun Milena S. Nicoloso Anirban Bhattacharyya George A. Calin Ramana V. Davuluri Center for Systems and Computational Biology Cancer Center Bioinformatics Facility The Wistar Institute Philadelphia PA USA Department of Experimental Therapeutics University of Texas M.D. Anderson Cancer Center Houston TX USA

MicroRNAs (miRs) are a large family of short 20 - 25-nt single-stranded noncoding RNAs, recently identified in many eukaryotes from nematode to human, which play an important role in gene regulation. Single nucleotide polymorphisms (SNPs) are the most common genetic variants in the human genome, and an immense source of information for localizing and identifying disease susceptible genes. Here, we investigate how the SNPs located in transcribed regions of protein coding genes will affect the miR-mRNA interaction by altering the Minimum Free Energy (MFE) of the miR-mRNA duplex, thus destroying the existing miR target sites or creating the new target sites. We propose that a combination of multiple allelic variants in miR target regions can alter the gene regulation and contribute to the likelihood of disease development. We developed a bioinformatics pipeline to predict the target SNPs, which can potentially influence the miR-mRNA interaction, based on the SNPspsila ability to alter the MFE of the miR-mRNA duplex. We annotated and integrated such target SNPs, miRs, and the target gene annotation information into an integrated database, called miR-SNPDB.

关键词： Humans bioinformatics Diseases RNA Genetics Genomics Information resources Proteins Pipelines Databases

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Modeling gene regulation and spatial organization of sequence based motifs

Modeling gene regulation and spatial organization of sequenc...

引用

ieee Symposium on bioinformatics and Bioengineering (BIBE)

作者： Jochen Supper Claas aufm Kampe Dierk Wanke Kenneth W. Berendzen Klaus Harter Richard Bonneau Andreas Zell Center for Bioinfonnatics Tiibingen (ZBIT) University of Tubingen Germany Center for Plant Molecular Biology (ZMBP) University of Tubingen Germany New York University New York NY US

Reconstructing and modeling regulatory networks is an active area of research in bioinformatics and systems biology. Hence, various computational methods have been published, often successfully modeling one aspect of regulatory control. Gene regulation, however, is a process that depends on many different components such as transcription factors (TFs), cis-regulatory motifs and their temporal and spatial coordination. Accordingly, a promising new direction for computational analysis is the incorporation of multiple data types to discover, for instance, cluster membership, the spatial organization of cis-regulatory motifs and TFs that bind to these motifs. Here, we present such a data-driven framework, comprising four stages, to infer gene regulatory networks (GRNs) by modeling: 1. Motif presence in the promoter; 2. Spatial motif arrangement in co-regulated genes; 3. TFs that bind the respective motifs, and: 4. Dynamic properties of the GRN. A novel method is presented in stage 2, where we optimize for the spatial motif properties: orientation, occurrence of multiple motifs, relative distance between two motifs and distance to the transcription start site (TSS). To find optimal distance based properties in efficient time we describe a dynamic programming approach. To combine multiple motif properties that are shared by genes with similar expression profiles a Hill-climber is employed. Subsequently, in stage 3 and 4, we infer GRNs by assigning TFs to the derived motifs and model time-dependent regulatory relationships between them with the inferelator approach. None of the stages require the user to manually adjust any parameter, and thus derived properties can be analyzed without the bias introduced by parametrization. We applied this approach to S. cerevisiae data and obtained insight into individual and general properties of the spatial assembly of regulatory elements and inferred the corresponding GRN.

关键词： bioinformatics systems biology Proteins Sequences Genomics Biological system modeling Biology computing DNA RNA Data analysis

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Uncertainty propagation for quality assurance in Reinforcement Learning

Uncertainty propagation for quality assurance in Reinforceme...

引用

International Joint conference on Neural Networks (IJCNN)

作者： Daniel Schneegass Steffen Udluft Thomas Martinetz Learning Systems Department of the Information & Communications Corporate Technology Siemens AG Institute for Neuro-and Bioinformatics University of Luebeck Germany

In this paper we address the reliability of policies derived by Reinforcement Learning on a limited amount of observations. This can be done in a principled manner by taking into account the derived Q-functionpsilas uncertainty, which stems from the uncertainty of the estimators used for the MDPpsilas transition probabilities and the reward function. We apply uncertainty propagation parallelly to the Bellman iteration and achieve confidence intervals for the Q-function. In a second step we change the Bellman operator as to achieve a policy guaranteeing the highest minimum performance with a given probability. We demonstrate the functionality of our method on artificial examples and show that, for an important problem class even an enhancement of the expected performance can be obtained. Finally we verify this observation on an application to gas turbine control.

关键词： Uncertainty Covariance matrix Bayesian methods Learning Measurement uncertainty Gaussian processes Joints

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A new cluster validity measure for bioinformatics relational datasets

A new cluster validity measure for bioinformatics relational...

引用

ieee International conference on Fuzzy systems (FUZZ-ieee)

作者： Mihail Popescu James C. Bezdek James M. Keller Timothy C. Havens Jacalyn M. Huband Electrical and computer Engineering Department University of Missouri Columbia MO USA Health Management and Medical Informatics Department University of Missouri Columbia MO USA Cs. Department University of West Florida Pensacola FL USA

Many important applications in biology have underlying datasets that are relational, that is, only the (dis)similarity between biological objects (amino acid sequences, gene expression profiles, etc.) is known and not their feature values in some feature space. Examples of such relational datasets are the gene similarity matrices obtained from BLAST, gene expression data, or gene ontology (GO) similarity measures. Once a relational dataset is obtained, a common question asked is how many groups of objects are represented in the original dataset. The answer to this question is usually obtained by employing a clustering algorithm and a cluster validity measure. In this article we describe a cluster validity measure for non-Euclidean relational fuzzy c-means that is based on the correlation between a relation induced on the data by the cluster memberships and the original relational data. This validity measure can be applied to partitions made by any fuzzy relational clustering algorithm. We illustrate our measure by validating clusters in several dissimilarity matrices for a set of 194 gene products obtained using BLAST and GO similarities.

关键词： conferences Correlation Fuzzy systems Partitioning algorithms Biology Gene expression Clustering algorithms

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DNA-sequence analysis using Markov chain models

DNA-sequence analysis using Markov chain models

引用

ieee (first ITW conference of the year) Information Theory Workshop (ITW)

作者： Boris Ryabko Natalie Usotskaya Institute of Computational Technologies Siberian Branch of RAS Siberian State University of Telecommunications and Informatics Novosibirsk Russia Novosibirsk State University Novosibirsk Russia

The statistical structure of DNA-sequences is of a great interest to molecular biology, genetics and the theory of evolution (see Chen and others, GIW-99, 1999, Aktulga and others, EURASIP J. of bioinformatics and systems Biology, 2007, Li, Computers and Chemistry , 1997). One of the approaches is a sequence modeling using Markov processes of different orders, and further statistical estimation of their parameters (see Simons and others, JSPI , 2005). In this paper we use firstly the test for the serial independence from Ryabko, Astola (Stat. Methodology, 2006) to estimate the ldquomemoryrdquo (or connectivity) of genetic texts and secondly we apply the homogeneity test for solving the DNA-based problem connected to the phylogenetic system of various organisms.

关键词： Biological system modeling systems biology Evolution (biology) Genetics bioinformatics Biology computing DNA computing Chemistry Sequences Markov processes

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Advances in the ProGenGrid Workflow Management System

Advances in the ProGenGrid Workflow Management System

引用

ieee International conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)

作者： Maria Mirto Massimo Cafaro Italo Epicoco Giovanni Aloisio NNL of CNR-INFM Lecce Italy University of Salerno Lecce Italy NNL/CNR-INFM University of Salerno Lecce Italy

A large-scale simulation in e-science experiments can be modeled by using a workflow. The ProGenGrid workflow management system is being developed at the University of Salento in Lecce since 2004 and consists of an editor for designing the experiment and an engine for scheduling the jobs in a computational grid. The initial version was based on wrapping the bioinformatics tools as Web services and scheduling job execution on the grid by using an opportune engine. Then the engine was optimized to support batch, parameter and MPI jobs by using the Globus Toolkit. This component was developed as part of the grid resource broker project. In this paper, we present the latest advances regarding the editorpsilas new features such as on line monitoring, and the enginepsilas support for scheduling jobs on other grid middleware such as gLite and Unicore.

关键词： Workflow management software Engines Processor scheduling Large-scale systems computational modeling Job design Grid computing Wrapping bioinformatics Web services

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