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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281-290 订阅

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An Efficient Comparative Machine Learning-based Metagenomics Binning Technique Via Using Random Forest

An Efficient Comparative Machine Learning-based Metagenomics...

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ieee International conference on computational lntelligence and Virtual Environments for Measurement systems and Applications

作者： Helal Saghir Dalila B. Megherbi Center for Human/Machine Intelligence Networking and Distributed Systems Department of Electrical and Computer Engineering University of Massachusetts

ISBN: (纸本)9781467347020

Metagenomics is the study of microorganisms collected directly from natural environments. Metagenomics studies use DNA fragments obtained directly from a natural environment using whole genome shotgun (WGS) sequencing. Sequencing random fragments obtained from whole genome shotgun into taxa-based groups is known as binning. Currently, there are two different methods of binning: sequence similarity methods and sequence composition methods. Sequence similarity methods are usually based on sequence alignment to known genome like BLAST, or MEGAN. As only a very small fraction of species is available in the current databases, similarity methods do not yield good results. As a given database of organisms grows, the complexity of the search will also grow. Sequence composition methods are based on compositional features of a given DNA sequence like K-mers, or other genomic signature(s). Most of these current methods for binning have two major issues: they do not work well with short sequences and closely related genomes. In this paper we propose new machine learning related predictive DNA sequence feature selection algorithms to solve binning problems in more accurate and efficient ways. In this work we use Oligonucleotide frequencies from 2-mers to 4-mers as features to differentiate between sequences. 2-mers produces 16 features, 3-mers produces 64 features and 4-mers produces 256 features. We did not use feature higher than 4-mers as the number of feature increases exponentially and for 5-mers the number of feature would be 1024 features. We found out that the 4-mers produces better results than 2-mers and 3-mers. The data used in this work has an average length of 250, 500, 1000, and 2000 base pairs. Experimental results of the proposed algorithms are presented to show the potential value of the proposed methods. The proposed algorithm accuracy is tested on a variety of data sets and the classification/prediction accuracy achieved is between 78% - 99% for various simul

关键词： bioinformatics Metagenomics Binning Next generation Sequencing Pattern Classification Machine learning Random forest Bagged decision tree computational intelligence Reduction methods Forwaord sequential feature selection Ttest Metagenomics Artificial Intelligence computational intelligence Pattern recognition Dataset bioinformatics REDUCTION METHODS Machine Learning

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Golden-run Alignment for Analysis of Robustness Testing Results: Dealing with Diagnostics Issues

Golden-run Alignment for Analysis of Robustness Testing Resu...

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Annual ieee/IFIP International conference on Dependable systems and Networks Workshops

作者： Gizelle Sandrini Lemos Eliane Martins Institute of Computing University of Campinas

ISBN: (纸本)9781479901807

For the analysis of robustness testing results, comparison with a golden run is commonly used to determine whether robustness failures occurred or not. One limitation of this approach is that traditional comparison techniques require the system to have a repeatable behavior under the same workload, whether or not in presence of faults. This limits the applicability of this technique, since most systems have indeterminist behavior due to concurrency, for example. Moreover, tools that use golden-run comparisons hardly ever give information about what are the common patterns of behavior between the golden-run and a faulty trace and where there are deviations due to action of fault-tolerance mechanisms, for example. In this paper, we show how the use of sequence alignment algorithms, from computational biology, can be of help. Besides allowing the determination of regions of similarities between two sequences that are not exactly equal, these algorithms present results in a visual form, highlighting the different zones where there are common patterns between the two sequences. We also point out other ways in which alignment algorithms can be useful as well.

关键词： Robustness testing result analysis Golden run comparison Sequence alignment Sequence Alignment computational Biology bioinformatics Fault tolerance Analysis

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Forests of Latent Tree Models to Decipher Genotype-Phenotype Associations

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5th International Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2012

作者： Sinoquet, Christine Mourad, Raphaël Leray, Philippe LINA UMR CNRS 6241 Université de Nantes 2 rue de la Houssinière BP 92208 44322 Nantes Cedex France Center for Computational Biology and Bioinformatics Department of Molecular and Medical Genetics Indiana University Indianapolis IN 46002 United States UMR CNRS 6241 Ecole Polytechnique de l'Université de Nantes rue Christian Pauc BP 50609 44306 Nantes Cedex 3 France

ISBN: (纸本)9783642382550

Genome-wide association studies have revolutionized the search for genetic influences on common genetic diseases such as diabetes, obesity, asthma, cardio-vascular diseases and some cancers. In particular, together with the population aging concern, increasing health care costs require that further investigations are pursued to design scalable and efficient tools. The high dimensionality and complexity of genetic data hinder the detection of genetic associations. To decrease the risks of missing the causal factor and discovering spurious associations, machine learning offers an attractive framework alternative to classical statistical approaches. A novel class of probabilistic graphical models (PGMs) has recently been proposed - the forest of latent tree models (FLTMs) -, to reach a trade-off between faithful modeling of data dependences and tractability. In this chapter, we assess the great potentiality of this model to detect genotype-phenotype associations. The FLTM-based contribution is first put into the perspective of PGM-based works meant to model the dependences in genetic data;then the contribution is considered from the technical viewpoint of LTM learning, with the vital objective of scalability in mind. We then present the systematic and comprehensive evaluation conducted to assess the ability of the FLTM model to detect genetic associations through latent variables. Realistic simulations were performed under various controlled conditions. In this context, we present a procedure tailored to correct for multiple testing. We also show and discuss results obtained on real data. Beside guaranteeing data dimension reduction through latent variables, the FLTM model is empirically proven able to capture indirect genetic associations with the disease: strong associations are evidenced between the disease and the ancestor nodes of the causal genetic marker node, in the forest;in contrast, very weak associations are obtained for other latent variables. Finally, we

关键词： Scalability

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On the Application of Supervised Machine Learning to Trustworthiness Assessment

On the Application of Supervised Machine Learning to Trustwo...

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ieee International conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Sascha Hauke Sebastian Biedermann Max Mühlhäuser Dominik Heider Department of Computer Science Technische Universität Darmstadt Germany Deptartment of Bioinformatics University of Duisburg-Essen Germany

State-of-the art trust and reputation systems seek to apply machine learning methods to overcome generalizability issues of experience-based Bayesian trust assessment. These approaches are, however, often model-centric instead of focussing on data and the complex adaptive system that is driven by reputation-based service selection. This entails the risk of unrealistic model assumptions. We outline the requirements for robust probabilistic trust assessment using supervised learning and apply a selection of estimators to a real-world dataset, in order to show the effectiveness of supervised methods. Furthermore, we provide a representational mapping of estimator output to a belief logic representation for the modular integration of supervised methods with other trust assessment methodologies.

关键词： Predictive models computational modeling Data models Estimation Bayes methods Vegetation Aggregates

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A Distributed CPU-GPU Framework for Pairwise Alignments on Large-Scale Sequence Datasets

A Distributed CPU-GPU Framework for Pairwise Alignments on L...

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ieee International conference on Application-specific systems, Architectures and Processors

作者： Da Li Kittisak Sajjapongse Huan Truong Gavin Conant Michela Becchi Dept. of Electrical and Computer Engineering MU Informatics Institute

ISBN: (纸本)9781479904945

Several problems in computational biology require the all-against-all pairwise comparisons of tens of thousands of individual biological sequences. Each such comparison can be performed with the well-known Needleman-Wunsch alignment algorithm. However, with the rapid growth of biological databases, performing all possible comparisons with this algorithm in serial becomes extremely time-consuming. The massive computational power of graphics processing units (GPUs) makes them an appealing choice for accelerating these computations. As such, CPU-GPU clusters can enable all-against-all comparisons on large datasets. In this paper, we present a hybrid MPI-CUDA framework for computing multiple pairwise sequence alignments on CPU-GPU clusters. Our design targets both homogeneous and heterogeneous clusters with nodes characterized by different hardware and computing capabilities. Our framework consists of the following components: a cluster-level dispatcher, a set of node-level dispatchers, and a set of CPU- and GPU-workers. The cluster-level dispatcher progressively distributes work to the compute nodes and aggregates the results. The node-level dispatchers distribute alignment tasks to available CPUs and GPUs and perform dual-buffering to hide data transfers between CPU and GPU. CPU- and GPU-workers perform pairwise sequence alignments using the Needleman-Wunsch algorithm. We propose and evaluate three designs for these GPU workers, all of them outperforming the existing open-source implementation from the Rodinia Benchmark Suite.

关键词： heterogeneous system sequence alignment GPU cluster Sequence Alignment Dispatchers Graphics Processing Unit central processing units GRAPPER PICK UP Pairwise HETEROGENEOUS SYSTEM Frameworks bioinformatics computational Biology Clusters Dataset

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An Optimized and Low-cost FPGA-based DNA Sequence Alignment - A Step towards Personal Genomics

An Optimized and Low-cost FPGA-based DNA Sequence Alignment ...

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

作者： Hunnat Ali Shah Laiq Hasan Nasir Ahmad Department of Computer Systems Engineering UET Peshawar

ISBN: (纸本)9781457702150

DNA sequence alignment is a cardinal process in computational biology but also is much expensive computationally when performing through traditional computational platforms like CPU. Of many off the shelf platforms explored for speeding up the computation process, FPGA stands as the best candidate due to its performance per dollar spent and performance per watt. These two advantages make FPGA as the most appropriate choice for realizing the aim of personal genomics. The previous implementation of DNA sequence alignment did not take into consideration the price of the device on which optimization was performed. This paper presents optimization over previous FPGA implementation that increases the overall speed-up achieved as well as the price incurred by the platform that was optimized. The optimizations are (1) The array of processing elements is made to run on change in input value and not on clock, so eliminating the need for tight clock synchronization, (2) the implementation is unrestrained by the size of the sequences to be aligned, (3) the waiting time required for the sequences to load to FPGA is reduced to the minimum possible and (4) an efficient method is devised to store the output matrix that make possible to save the diagonal elements to be used in next pass, in parallel with the computation of output matrix. Implemented on Spartan3 FPGA, this implementation achieved 20 times performance improvement in terms of CUPS over GPP implementation.

关键词： output matrix performance boost DNA Sequence Alignment Speeding input value Sequence Alignment clock recovery Genomics bioinformatics computational Biology Platform

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Analysis on critical nodes in controlling complex networks using dominating sets

Analysis on critical nodes in controlling complex networks u...

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International ieee conference on Signal-Image Technologies and Internet-Based System

作者： Jose C. Nacher Tatsuya Akutsu Department of Information Science Toho University Funabashi Japan Bioinformatics Center Kyoto University Uji Japan

ISBN: (纸本)9781479932122

We investigate the role of nodes when a minimum dominating set (MDS) approach is considered in controlling a network. We present an algorithmic procedure to compute the critical and redundant nodes using the MDS. The theoretical analysis for scale-free networks shows that (1) high-degree nodes tend to be critical nodes and (2) for scaling exponent gamma>2, such probability increases when gamma grows. These relationships are confirmed by computer simulations. Furthermore, our computational experiments also show that the MDS is unimodal when the average degree left grows. It means that most nodes are redundant for high-degree, therefore one can achieve control through a small set of nodes, highlighting a centralized control feature. The analysis of a set of real-world networks confirms the findings observed in simulation experiments. In particular, the U.S. airport network shows a more centralized control, whereas the Italy's nationwide power grid network exhibits a more distributed control. The human protein-protein interaction network exerts control with a configuration between both man-made networks.

关键词： Airports Computer simulation Educational institutions Centralized control Proteins Power system dynamics Complex networks

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Analyzing T cell repertoire diversity by high-throughput sequencing

Analyzing T cell repertoire diversity by high-throughput seq...

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ieee Global conference on Signal and Information Processing (GlobalSIP)

作者： Boris Grinshpun Jennifer Sims Peter Canoll Jeffrey N. Bruce Peter Sims Yufeng Shen Department of Systems Biology Department of Neurological Surgery Department of Pathology and Cell Biology Department of Biochemistry & Molecular Biophysics Department of Biomedical Informatics

Diversity on a large scale is one of the most striking and powerful features utilized by the mammalian immune system to fight off a vast universe of pathogens. The T-cell driven immune response is characterized by a multitude of distinct receptors capable of antigen recognition with high specificity. Using high-throughput sequencing we are able to investigate the T cell receptor (TCR) repertoire as the collection of its individual receptors, aiming to profile the global properties of the complementarily determining region 3 (CDR3) of the TCR in human immunity. However, analysis of the data is highly sensitive to single nucleotide polymoprhisms, read length and error rate, accuracy in mapping to a genomic reference, and our ability to translate the sequence, in silico, in the appropriate reading frame. We have developed a computational pipeline that performs error correction on overlapping paired-end long (250 nt) reads, and maps the reads unambiguously to V and J cassettes corresponding to TCR-α and -β chains. Our methods were applied to functional T cell receptors from healthy blood tissue and to several patients with low grade glioma (LGG) and glioblastoma multiforme (GBM). We used Shannon entropy to measure levels of diversity in the productive T cell repertoire and observed that greater than 50% of the TCR diversity can be explained by V, J cassette usage.

关键词： Entropy Immune system Error correction bioinformatics Blood Sequential analysis Genomics

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The illusion box of Syndactyly: Setup and ad hoc algorithm to induce virtual fingers webbing

The illusion box of Syndactyly: Setup and ad hoc algorithm t...

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International ieee/EMBS conference on Neural Engineering, CNE

作者： M. Merone P. Soda G. Di Pino D. Formica G. Pellegrino S. Micera V. Di Lazzaro G. Iannello E. Guglielmelli Laboratory of Biomedical Robotics and Biomicrosystem Universitá Campus Bio-Medico di Roma Rome Italy Computer Science and Bioinformatics Laboratory Universitá Campus Bio-Medico di Roma Rome Italy Institute of Neurology Universitá Campus Bio-Medico di Roma Rome Italy Epfi Translational Neural Engineering Laboratory Swiss

Inclusion of the prosthesis in the body schema lets the device felt by the user as an extension of the self and consequently improves its performance and acceptability. Two paradigmatic models that faced the issue of the illusory embodiment, the rubber hand illusion and the mirror box, revealed that such process goes in parallel with changes in the activity of cortical sensorimotor areas devoted to the limb and that a key factor is represented by the visual inflow that overrides the mismatching kinesthesia. In spite of that, vision alone is not able to trigger prosthesis embodiment in amputees everyday-life. In order to disentangle the contributes of visual and proprioceptive feedback in the induction of sensorimotor plasticity we develop the Illusion Box of Syndactyly that, through an ad hoc algorithm, produces an index-middle finger illusory fingers webbing. The algorithm works in realtime and, trough background difference, it segments the hands, recognizes the fingers and produces the virtual syndactyly. We perform preliminary tests on a healthy subject, suggesting that the setup is robust and efficient to induce the illusion.

关键词： Visualization Indexes Robot sensing systems computational modeling Mirrors Monitoring Prosthetics

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Workshop: Opportunities and challenges of non-model ecoinformatics

Workshop: Opportunities and challenges of non-model ecoinfor...

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2012 ieee 2nd International conference on computational Advances in Bio and Medical Sciences, ICCABS 2012

作者： Emrich, Scott Department of Computer Science and Engineering University of Notre Dame Notre Dame IN United States

ISBN: (纸本)9781467313216

Ongoing improvements in sequencing technology allow even greater analysis of questions related to genome biology. We will overview several of the opportunities and challenges of newer generation sequencing applied to ecological questions. We also discuss arthropod-focused applications and resulting distributed systems resources available for decentralized bioinformatics analysis. © 2012 ieee.

关键词： bioinformatics

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