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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81-90 订阅

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K-Means Clustering for Features Arrangement in Metagenomic Data Visualization 12th

K-Means Clustering for Features Arrangement in Metagenomic D...

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12th International conference on computational Collective Intelligence (ICCCI)

作者： Hai Thanh Nguyen Toan Bao Tran Huong Hoang Luong Trung Phuoc Le Tran, Nghi C. Quoc-Dinh Truong Can Tho Univ Coll Informat & Commun Technol Can Tho 900000 Vietnam Duy Tan Univ Ctr Software Engn Da Nang 550000 Vietnam Duy Tan Univ Inst Res & Dev Da Nang 550000 Vietnam FPT Univ Dept Informat Technol Can Tho 900000 Vietnam Natl Cent Univ Taoyuan Taiwan

ISBN: (纸本)9783030631185;9783030631192

Personalized medicine is one of the most concern of the scientists to propose successful treatments for diseases. This approach considers patients' genetic make-up and attention to their preferences, beliefs, attitudes, knowledge and social context. Deep learning techniques hold important roles and obtain achievements in bioinformatics tasks. Metagenomic data analysis is very important to develop and evaluate methods and tools applying to Personalized medicine. Metagenomic data is usually characterized by high-dimensional spaces where humans meet difficulties to interpret data. Visualizing metagenomic data is crucial to provide insights in data which can help researchers to explore patterns in data. Moreover, these visualizations can be fetched into deep learning such as Convolutional Neural Networks to do prediction tasks. In this study, we propose a visualization method for metagenomic data where features are arranged in the visualization based on K-means clustering algorithms. We show by experiments on metagenomic datasets of three diseases (Colorectal Cancer, Obesity and Type 2 Diabetes) that the proposed approach not only provides a robust method for visualization where we can observe clusters in the images but also enables us to improve the performance in disease prediction with deep learning algorithms.

关键词： Personalized medicine bioinformatics Visualization Convolutional neural networks K-means Clustering Disease prediction

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2017 ieee conference on computational Intelligence in bioinformatics and computational Biology, CIBCB 2017

2017 IEEE Conference on Computational Intelligence in Bioinf...

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2017 ieee conference on computational Intelligence in bioinformatics and computational Biology, CIBCB 2017

ISBN: (纸本)9781467389884

The proceedings contain 48 papers. The topics discussed include: leveraging data mining techniques to understand drivers of obesity;applying brain emotional learning based fuzzy inference system for EEG signal classification between schizophrenics and control participant;inference of genetic networks from time-series of gene expression levels using random forests;biclustering of gene expression microarray data using dynamic deme parallelized genetic algorithm(DdPGA);a multivariate feature selection framework for high dimensional biomedical data classification;a novel representation for Boolean networks designed to enhance heritability and scalability;inferring bistable LAC operon Boolean regulatory networks using evolutionary computation;hybridization and ring optimization for larger sets of embeddable biomarkers;modeling protein structural transitions as a multi-objective optimization problem;binning metagenomic reads with probabilistic sequence signatures based on spaced seeds;topological, functional, and structural analyses of protein-protein interaction networks of breast cancer lung and brain metastases;a novel hybrid differential evolution strategy applied to classifier design for mortality prediction in adult critical care admissions;evaluation of support vector machines and random forest classifiers in a real-time fetal monitoring system based on cardiotocography data;and reboot strategies in particle swarm optimization and their impact on parameter estimation of biochemical systems.

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Towards Reproducible bioinformatics: The OpenBio-C Scientific Workflow Environment 19

Towards Reproducible Bioinformatics: The OpenBio-C Scientifi...

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19th Annual ieee International conference on bioinformatics and Bioengineering (BIBE)

作者： Kanterakis, Alexandros Iatraki, Galateia Pityanou, Konstantina Koumakis, Lefteris Kanakaris, Nikos Karacapilidis, Nikos Potamias, George FORTH Inst Comp Sci Iraklion Greece Hellen Mediterranean Univ Heraklion Dept Elect & Comp Engn Iraklion Greece Univ Patras MEAD Ind Management & Informat Syst Lab Patras Greece

ISBN: (纸本)9781728146171

The highly competitive environment of post-genomics biomedical research is pushing towards the production of highly qualified results and their utilization in clinical practice. Due to this pressure, an important factor of scientific progress has been underestimated namely, the reproducibility of the results. To this end, it is critical to design and implement computational platforms that enable seamless and unhindered access to distributed bio-data, software and computational infrastructures. Furthermore, the need to support collaboration and form synergistic activities between the engaged researchers is also raised, as the mean to achieve consensus on respective scientific discoveries. The aforementioned needs and requirements underlie the motivations for the development of OpenBio-C workflow environment, and determine its fundamental objectives. The insufficiencies of current workflow editing and execution environments are explored, and the key-directions to advance over an environment that supports reproducibility are stated. The basic components and functionality of the OpenBio-C initial implementation (beta version) are detailed.

关键词： bioinformatics scientific workflows collaborative systems open science

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computational identification of metabolites for pathways related to Huntington's disease 19

Computational identification of metabolites for pathways rel...

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19th Annual ieee International conference on bioinformatics and Bioengineering (BIBE)

作者： Christodoulou, Christiana C. Minadakis, George Demetriou, Christiana A. Zamba-Papanicolaou, Eleni Spyrou, George M. Cyprus Inst Neurol & Genet Neurol Clin & Bioinformat Grp Engomi Cyprus Cyprus Sch Mol Med Engomi Cyprus Cyprus Inst Neurol & Genet Bioinformat Grp Engomi Cyprus Univ Nicosia Sch Med Dept Primary Care & Populat Engomi Cyprus

ISBN: (纸本)9781728146171

Huntington's disease (HD), a rare autosomal dominant disease, affecting the medium spiny neurons of the CNS. Although HD is caused by a trinucleotide repeat in the HTT gene, it is a complex disease. systems bioinformatics which combines systems biology and bioinformatics, has the ability to reveal synergistic relationships between multiple entities. This approach is vital as it can shed light on the biological behavior and mechanisms of the cell rather than only trying to study and understand a part of the system. Metabolomics is the systematic study and measurement of metabolites within a biological sample. In this work, we employ two approaches to identify metabolites for HD-related pathways, which were previously identified from our previous work on multi-source data integration These include: i) creation of pathway-to-pathway networks based on the reference network of PathwayConnector where pathways are mapped based on connectivity on KEGG, and (ii) creation of pathway-to-pathway networks using a pairwise approach, where a connection between two pathways exists only if they share common metabolites.

关键词： Huntington's disease Metabolomics systems bioinformatics PathwayConnector

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Risk factor prediction of chronic kidney disease based on machine learning algorithms 3

Risk factor prediction of chronic kidney disease based on ma...

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3rd International conference on Intelligent Sustainable systems, ICISS 2020

作者： Islam, Md. Ashiqul Akter, Shamima Hossen, Md. Sagar Keya, Sadia Ahmed Tisha, Sadia Afrin Hossain, Shahed Daffodil International University Dept. of Computer Science and Engineering Dhaka Bangladesh George Mason University Dept. of Bioinformatics and Computational Biology ManassasVA20110 United States

ISBN: (纸本)9781728170893

Chronic kidney disease (CKD) is an increasing medical issue that declines the productivity of renal capacities and subsequently damages the kidneys. CKD is very common nowadays;cardiovascular infection and end-stage renal illness are two life threatening diseases that can be caused as after-effects of CKD. These are conceivably preventable through early recognizable conditions and treatment of people who are in danger. The expectation of medical problems is a very troublesome assignment. CKD is particularly one of the most lethal diseases in the clinical field. Before it becomes too late to recognize CKD forecast, to get rid of risks, the prediction of risk factor is a major necessary step in the immediate stage. In this research work six algorithms such as Naïve Bayes, Random forest, Simple logistic regression, Decision Stump, Linear regression model, simple linear regression model is used to predict the risk factors of CKD. Considering the orderly execution and investigations of these strategies, six algorithms give a superior and quicker characterization execution. Six individual algorithms are applied to the dataset and the best outcomes have been acquired through the classification of predicting risk factors. © 2020 ieee.

关键词： Forecasting

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Techno Economic Feasibility Analysis of Grid-Connected Microgrid by Using Solar PV for Residential Usage

Techno Economic Feasibility Analysis of Grid-Connected Micro...

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ieee Region 10 Humanitarian Technology conference (R10-HTC)

作者： Dewan Mahnaaz Mahmud Sayeed Hasan S.M. Masum Ahmed Mohammad Zeyad Energy and Technology Research Division Advanced Bioinformatics Computational Biology and Data Science Laboratory Bangladesh Chattogram Bangladesh Erasmus+ Joint MSC in Smart Cities and Communities Faculty of Engineering University of Mons (UMONS) Mons Belgium Erasmus+ Joint MSC in Smart Cities and Communities University of the Basque Country (UPV/EHU) Bilbao Spain

Renewable energy systems (RES) are becoming more prominent because of the depletion of natural resources. Optimum sizing of the hybrid RES is necessary to ensure that renewable energy sources penetrate. Improper sizing may result in higher initiating costs or an inability to meet load demand under various weather conditions. By analyzing with Hybrid Optimization Multiple Energy Resources (HOMER pro), this study shows the ideal hybrid energy system that provides the lowest cost of energy production, emissions, and so on. This study provides a grid-connected hybrid power system model based on metrological data collected from a residential building in Mohammadpur, Dhaka, Bangladesh. Solar energy is used as a sustainable energy source thus the cost of the system was decreased, which is also environmentally friendly. This renewable energy also helped to minimize the levelized cost of energy (COE). The conclusion estimates operational costs, production costs, net present cost, and energy cost for the two combinations evaluated for the proposed microgrid system. According to the simulation results, delivering power to the load via a microgrid would be a viable and cost-effective solution.

关键词： Renewable energy sources Costs Simulation Buildings Microgrids Production Solar energy

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A Formative Usability Study to Improve Prescriptive systems for bioinformatics Big Data

A Formative Usability Study to Improve Prescriptive Systems ...

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ieee International conference on bioinformatics and Biomedicine (BIBM)

作者： Kanupriya Singh Shangman Li Isa Jahnke Ashish Pandey Zhen Lyu Trupti Joshi Prasad Calyam School of Information Science and Learning Technologies Dept. of Electical Engineering and Computer Science University of Missouri-Columbia USA

ISBN: (数字)9781728162157

ISBN: (纸本)9781728162164

Big data computation tools are vital for researchers and educators from various domains such as plant science, animal science, biomedical science and others. With the growing computational complexity of biology big data, advanced analytic systems, known as prescriptive systems, are being built using machine learning models to intelligently predict optimum computation solutions for users for better data analysis. However, lack of user-friendly prescriptive systems poses a critical roadblock to facilitating informed decision-making by users. In this paper, we detail a formative usability study to address the complexities faced by users while using prescriptive systems. Our usability research approach considers bioinformatics workflows and community cloud resources in the KBCommons framework's science gateway. The results show that recommendations from usability studies performed in iterations during the development of prescriptive systems can improve user experience, user satisfaction and help novice as well as expert users to make decisions in a well-informed manner.

关键词： Usability Big Data bioinformatics Task analysis Data visualization Interviews Prototypes

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Nucleotide composition bias in high throughput gene expression measurement methods 13

Nucleotide composition bias in high throughput gene expressi...

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13th ieee International conference on Signal Processing and Communication systems (ICSPCS)

作者： Jaksik, Roman Lalik, Anna Puszynski, Krzysztof Silesian Tech Univ Inst Automat Control Gliwice Poland

ISBN: (纸本)9781728121949

Studies of gene expression levels are known to be affected by biases related to the experimental procedure. Nucleotide composition of the studied genes significantly affects the efficiency of biochemical reactions used to prepare the material for study which translates to the measured expression levels. Data pre-processing methods aim at reducing such differences and the use of replicate samples is expected to increase the data quality, however all commonly used methods suffer from the reproducibility problems. In this work we utilize information provided by over two thousand experiments in order to explain the origin of nucleotide composition bias, highlight the magnitude of the problem and show its consequences for the interpretation of gene expression studies. We show that despite data standardization and the use of sample replicates the effect can have significant impact on the detection of differentially expressed genes between analyzed conditions, affecting interpretation of results from such studies.

关键词： RNA sequencing oligonucleotide microarrays detection of differentially expressed genes bioinformatics

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13th International conference on Parallel Processing and Applied Mathematics, PPAM 2019

13th International Conference on Parallel Processing and App...

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13th International conference on Parallel Processing and Applied Mathematics, PPAM 2019

ISBN: (纸本)9783030432218

The proceedings contain 91 papers. The special focus in this conference is on Parallel Processing and Applied Mathematics. The topics include: Performance/Energy Aware Optimization of Parallel Applications on GPUs Under Power Capping;improving Energy Consumption in Iterative Problems Using Machine Learning;automatic Software Tuning of Parallel Programs for Energy-Aware Executions;overview of Application Instrumentation for Performance Analysis and Tuning;Energy-Efficiency Tuning of a Lattice Boltzmann Simulation Using MERIC;Evaluating the Advantage of Reactive MPI-aware Power Control Policies;application-Aware Power Capping Using Nornir;A New Hardware Counters Based Thread Migration Strategy for NUMA systems;alea – Complex Job Scheduling Simulator;studying the Performance of Vector-Based Quicksort Algorithm;makespan Minimization in Data Gathering Networks with Dataset Release Times;overlapping Schwarz Preconditioner for Fourth Order Multiscale Elliptic Problems;MATLAB Implementation of C1 Finite Elements: Bogner-Fox-Schmit Rectangle;simple Preconditioner for a Thin Membrane Diffusion Problem;a Numerical Scheme for Evacuation Dynamics;Additive Average Schwarz with Adaptive Coarse Space for Morley FE;application of Multiscale computational Techniques to the Study of Magnetic Nanoparticle systems;clique: A Parallel Tool for the Molecular Nanomagnets Simulation and Modelling;Modelling of Limitations of BHJ Architecture in Organic Solar Cells;monte Carlo Study of Spherical and Cylindrical Micelles in Multiblock Copolymer Solutions;Parallel Tiled Cache and Energy Efficient Code for Zukers RNA Folding;electronic and Optical Properties of Carbon Nanotubes Directed to Their Applications in Solar Cells;The MPFI Library: Towards ieee 17882015 Compliance;softmax and McFaddens Discrete Choice Under Interval (and Other) Uncertainty;experiments with Heterogenous Automata-Based Multi-agent systems.

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A Scalable bioinformatics Analysis Platform based on Microservices Architecture

A Scalable Bioinformatics Analysis Platform based on Microse...

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2019 ieee International Research conference on Smart Computing and systems Engineering, SCSE 2019

作者： Rajapaksa, S. Wickramarachchi, A. Mallawaarachchi, V. Rasanjana, W. Perera, I. Meedeniya, D. Department of Computer Science and Engineering University of Moratuwa Sri Lanka

ISBN: (纸本)9789557041216

With the advancement of technologies, web services play a significant role to maintain infrastructure in healthcare domain due to the increasing demand of performance. In such systems, adoption of novel technologies is necessary to increase the productivity and reduce the burden of maintenance associated with legacy systems. Microservices architecture has become prominent in deploying server-side enterprise applications by allowing maintainable functionalities. However, it is challenging to utilize microservices in the domain of bioinformatics, although it enables independent process execution and maintenance. This paper introduces the utilization of microservices architecture to build an optimized platform for bioinformatics analyses. We present a hybrid architecture that consists of different hardware platforms to execute accelerated computational services, independently. The core communication is based on an Application Programming Interface (API) gateway. Furthermore, the paper presents the evaluation of results related to the performance of the proposed solution under varying biological sequences as inputs and algorithms. © 2019 University of Kelaniya.

关键词： Legacy systems

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