检索结果-内蒙古大学图书馆

56th ACM/EDAC/ieee Design Automation conference (DAC)

作者： Angizi, Shaahin Sun, Jiao Zhang, Wei Fan, Deliang Univ Cent Florida Dept Elect & Comp Engn Orlando FL 32816 USA Univ Cent Florida Dept Comp Sci Orlando FL 32816 USA

ISBN: (纸本)9781450367257

Classified as a complex big data analytics problem, DNA short read alignment serves as a major sequential bottleneck to massive amounts of data generated by next-generation sequencing platforms. With Von-Neumann computing architectures struggling to address such computationally-expensive and memory-intensive task today, Processing-in-Memory (PIM) platforms are gaining growing interests. In this paper, an energy-efficient and parallel PIM accelerator (AlignS) is proposed to execute DNA short read alignment based on an optimized and hardware-friendly alignment algorithm. We first develop AlignS platform that harnesses SOT-MRAM as computational memory and transforms it to a fundamental processing unit for short read alignment. Accordingly, we present a novel, customized, highly parallel read alignment algorithm that only seeks the proposed simple and parallel in-memory operations (i.e. comparisons and additions). AlignS is then optimized through a new correlated data partitioning and mapping methodology that allows local storage and processing of DNA sequence to fully exploit the algorithm-level's parallelism, and to accelerate both exact and inexact matches. The device-to-architecture co-simulation results show that AlignS improves the short read alignment throughput per Watt per mm(2) by similar to 12x compared to the ASIC accelerator. Compared to recent FM-index-based ReRAM platform, AlignS achieves 1.6x higher throughput per Watt.

关键词： DNA Computer architecture Genomics Sequential analysis Magnetic tunneling bioinformatics Micromechanical devices

来源：评论

学校读者我要写书评

暂无评论

A BCHC genetic algorithm model of cotemporal hierarchical Arabidopsis thaliana gene interactions

A BCHC genetic algorithm model of cotemporal hierarchical <i...

引用

ieee International conference on bioinformatics and Biomedicine (BIBM) - Human Genomics

作者： LaPointe, Bree Ann John, David J. Norris, James L. Allen, Edward E. Harkey, Alexandria F. Muhlemann, Joelle K. Muday, Gloria Qualtrix Salt Lake City UT USA Wake Forest Univ Dept Comp Sci Winston Salem NC 27109 USA Wake Forest Univ Winston Salem NC 27109 USA

ISBN: (纸本)9781538654880

Gene interaction network models from time course gene transcript abundance data are algorithmically created using a new aggressive genetic algorithm denoted by BCHC. The BCHC algorithm rigorously integrates probabilistic hierarchical likelihood and Bayesian methodology to produce accurate posterior probabilities of interactions between genes after observance of hierarchical gene transcript abundance data. Forbidden pairwise gene relationships are incorporated into the modeling process. This gene interaction model is compared to a previous gene interaction model utilizing the same data and Bayesian likelihood, however based upon an exponentially slower, less aggressive, and less adaptive Metropolis-Hasting search algorithm. In addition for a smaller data set, our gene interaction model is compared to less rigorous non-probabilistic Lasso estimated partial correlation models which do not fully incorporate the hierarchical structure. A comparison is also made between the smallest Bayesian model and tests for edges based on a restricted non-Bayesian hierarchical technique. The BCHC algorithm performs well when the number of genes is moderately increased, both in terms of execution time and model quality.

关键词： bioinformatics Biological system modeling computational systems biology Genetic algorithms Probability Bayes methods

来源：评论

学校读者我要写书评

暂无评论

Cross-topic Rumour Detection in the Health Domain

Cross-topic Rumour Detection in the Health Domain

引用

2018 ieee International conference on bioinformatics and Biomedicine, BIBM 2018

作者： Sicilia, Rosa Merone, Mario Valenti, Roberto Cordelli, Ermanno Drantoni, Federico Ruvo, Vincenzo De Dragone, Patrizia Benedetta Esposito, Sara Soda, Paolo Unit of Computer Systems and Bioinformatics Universitá Campus Bio-Medico di Roma Via Alvaro Del Portillo 21 Rome00128 Italy

ISBN: (纸本)9781538654880

Nowadays information diffusion has become more and more immediate and fast thanks to social media and its services. However, lack of controls and moderation in resources as social microblogs often leads to spread unverified information, such as rumours, which can become a threat to the society. To improve life quality and good information diffusion, various automatic systems have been studied for rumour detection in microblogs at level of aggregation of posts, whereas a few effort has been tried to the most challenging scenario where the rumour has to be recognized at level of each single post. In this work, we direct our efforts towards individual post rumour detection: we investigate how features describing influence potential, personal interest and network characteristic perform on two different datasets of posts collected from Twitter using two different health-related keywords. As a further contribution, we study what happens in cross-topic tests, i.e. when the rumour detection system is trained with posts with an hashtag and tested on samples with a different one. © 2018 ieee.

关键词： Health

来源：评论

学校读者我要写书评

暂无评论

OntoKeeper: Semiotic-driven Ontology Evaluation Tool for Biomedical Ontologists

OntoKeeper: Semiotic-driven Ontology Evaluation Tool for Bio...

引用

2018 ieee International conference on bioinformatics and Biomedicine, BIBM 2018

作者： Ltuanr Amith, Muhammad Manion, Frank Liang, Chen Harris, Marcelline Wang, Dennis He, Yongqun Tao, Cui School of Biomedical Informatics University of Texas Health Science Center HoustonTX United States Department of Systems Populations and Leadership University of Michigan School of Nursing Ann ArborMI United States Health Informatics Info. Management Lousiana Tech University RustonLA United States University of Texas AustinTX United States Center for Computational Medicine Bioinformatics University of Michigan Medical School Ann ArborMI United States

ISBN: (纸本)9781538654880

Evaluation for ontologies is an important phase in ontology engineering. When evaluating ontologies the designer needs to assess validation and verification aspects of the knowledge artifact. Yet, this task is often disregarded, and therefore, tools that accommodate the workflow of the biomedical ontologists are needed. In this paper. we introduce OntoKeeper, a tool we developed that utilizes a semiotic-driven metric proposed by Burton-Jones and colleagues. Overall, OntoKeeper is the first of a few ontology evaluation tools that can help provide ontology evaluation functionality for knowledge engineers. © 2018 ieee.

关键词： Knowledge management

来源：评论

学校读者我要写书评

暂无评论

Radiomics for Predicting CyberKnife response in acoustic neuroma: A pilot study

Radiomics for Predicting CyberKnife response in acoustic neu...

引用

2018 ieee International conference on bioinformatics and Biomedicine, BIBM 2018

作者： Dramico, Natascha Claudia Sicilia, Rosa Cordelli, Ermanno Valbusa, Giovanni Grossi, Enzo Zanetti, Isa Bossi Beltramo, Giancarlo Fazzini, Deborah Scotti, Giuseppe Iannello, Giulio Soda, Paolo Imaging Department Centro Diagnostico Italiano S.p.A. Milan Italy Unit of Computer Systems and Bioinformatics Department of Engineering Università Campus Bio-Medico di Roma Italy Joint Laboratory on Precision Medicine and BioData Analytics Università Campus Bio-Medico di Roma Centro Diagnostico Italiano S.p.A. Milan Italy Cyberknife Department Centro Diagnostico Italiano S.p.A. Milan Italy Bracco Imaging S.p.A. Milan Italy

ISBN: (纸本)9781538654880

Vestibular schwannomas, also known as acoustic neuromas, are a primary intracranial tumor of the myelin-forming cells of the 8th cranial nerve. Stereotactic radiosurgery, which can be performed with the CyberKnife robotic device, is one of the approaches for managing this disease, and has shown to be effective in controlling tumor growth. However, it may have side effects and up to two years may be needed to assess its efficacy. In this work we present a machine learning-based radiomics approach that first computes quantitative biomarkers from MR images routinely collected before the CyberKnife treatment and then predicts the treatment response. Furthermore, the degree of class imbalance observed in the available dataset suggested us to resample the data during the learning stage. The results achieved are promising, with an accuracy equal to 85.3%. © 2018 ieee.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

MESGA: An MPSoC Based Embedded System Solution for Short Read Genome Alignment 18

MESGA: An MPSoC Based Embedded System Solution for Short Rea...

引用

23rd Asia and South Pacific Design Automation conference (ASP-DAC)

作者： Gnanasambandapillai, Vikkitharan Bayat, Arash Parameswaran, Sri Univ New South Wales Sch Comp Sci & Engn Sydney NSW 2052 Australia

ISBN: (纸本)9781509006021

computational needs for genome processing are often satiated by enormous servers or by cloud computers. Even though there has been some work in implementing some aspects of genome processing in GPUs and FPGAs, they are often accelerators for such servers and not stand-alone systems. In this paper, for the first time, we present a method to entirely move the alignment process to embedded processors. Such a system is useful in a variety of situations where significant networked infrastructure is not available, and where privacy is a concern. A ring pipelined processor architecture for short read alignment, based on partitioned genome references is shown. A timeout based alignment method is proposed to prevent unnecessary exhaustive search. The proposed partitioning method allows an entire human genome to be processed using small embedded processors. Experimental results show that the proposed solution speeds up the performance by approximately seven times with 16 embedded processors when compared to a linear pipelined system. It is expected that the proposed solution will to lead to a portable genome analyzing device, significantly reducing cost and testing time.

关键词： Genomics bioinformatics Program processors Field programmable gate arrays Indexes Memory management

来源：评论

学校读者我要写书评

暂无评论

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

2017 IEEE Conference on Computational Intelligence in Bioinf...

引用

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.

关键词：

来源：评论

学校读者我要写书评

暂无评论

proceedings - 2017 ieee International conference on bioinformatics and Biomedicine, BIBM 2017

Proceedings - 2017 IEEE International Conference on Bioinfor...

引用

2017 ieee International conference on bioinformatics and Biomedicine, BIBM 2017

ISBN: (纸本)9781509030491

The proceedings contain 421 papers. The topics discussed include: quantification of visual diagnostic heuristics during simulated pathology diagnosis;on the robustness of mixture model-based unsupervised learning in single-cell analyses;an adaptive refinement for community detection methods for disease module identification in biological networks using novel metric based on connectivity, conductance & modularity;improving quality of ligand-binding site prediction with bayesian optimization;application of deep learning in genomic selection;development of 'KBCommons' - universal informatics framework for multi-omics translational research;near-light perspective shape from shading for 3D visualizations in endoscopy systems;development of an informatics analytics workflow for DAPSEQ data exploration and validation for auxin response factors in maize;discovering multifactorial associations with the development of age-related cataract using contrast mining;a deep-learning framework for amidation site prediction;schema matching and data integration on protein ncounter data;inductive identification of functional status information and establishing a gold standard corpus;and identification of cancer drug sensitivity biomarkers.

关键词：

来源：评论

学校读者我要写书评

暂无评论

ieee BIBM 2016 Special Issue

IEEE TRANSACTIONS ON NANOBIOSCIENCE

引用

ieee TRANSACTIONS ON NANOBIOSCIENCE 2017年第5期16卷 312-313页

作者： Hu, Xiaohua Tony Drexel Univ Philadelphia PA 19104 USA Nortel Res Ctr Brampton ON Canada Verizon Lab Waltham MA USA DMW Software Silicon Valley CA USA Coll Comp & Informat Data Min & Bioinformat Lab Philadelphia PA 19104 USA NSF Ctr I U CRC Visual & Decis Informat NSF CVDI Philadelphia PA 19104 USA

bioinformatics and biomedicine research is fundamental to our understanding of complex biological systems, impacting the science and technology of fields ranging from agricultural and environmental sciences to pharmaceutical and medical sciences. This type of research requires close collaboration among multidisciplinary teams of researchers in computer science, statistics, physics, engineering, life sciences and medical sciences, and their interfaces. The ieee International conference on bioinformatics and Biomedicine aims to provide an open and interactive forum to catalyze the cross-fertilization of ideas from these disciplines and to bridge our knowledge gaps.

关键词： Special issues and sections Meetings bioinformatics computational systems biology Drugs

来源：评论

学校读者我要写书评

暂无评论

引用

2017 ieee International conference on bioinformatics and Biomedicine, BIBM 2017

作者： Sicilia, Rosa Giudice, Stella Lo Pei, Yulong Pechenizkiy, Mykola Soda, Paolo Unit of Computer Systems and Bioinformatics Department of Engineering Università Campus Bio-Medico di Roma Via Alvaro del Portillo 21 Rome00128 Italy 2M Engineering Ltd Valkenswaard Netherlands Department of Mathematics and Computer Science Eindhoven University of Technology Eindhoven5600 MB Netherlands

ISBN: (纸本)9781509030491

In the last years social networks have emerged as a critical mean for information spreading. In spite of all the positive consequences this phenomenon brings, unverified and instrumentally relevant information statements in circulation, named as rumours, are becoming a potential threat to the society. Recently, there have been several studies on topic-independent rumour detection on Twitter. In this paper we present a novel rumour detection system which focuses on a specific topic, that is health-related rumours on Twitter. To this aim, we constructed a new subset of features including influence potential and network characteristics features. We tested our approach on a real dataset observing promising results, as it is able to correctly detect about 89% of rumours, with acceptable levels of precision. © 2017 ieee.

关键词： Health

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：