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2018 ieee International conference on bioinformatics and Biomedicine, BIBM 2018

作者： Larsonneur, Elise Mercier, Jonathan Wiart, Nicolas Floch, Edith Le Delhomme, Olivier Meyer, Vincent Institut de Biologie Francois Jacob CEA Université Paris-Saclay EvryF-91057 France

ISBN: (纸本)9781538654880

Biological knowledge discovery is a tedious task which relies on computationally intensive analyses to process huge volumes of data and metadata. This task can be facilitated by a well-designed workflow management system, capable of deploying and efficiently orchestrating the scientific analysis. However choosing the right workflow management system remains a critical challenge. In this study, we propose ten metrics for evaluating the efficiency of workflow management systems, and show how the Pegasus-mpi-cluster and Snakemake workflow management systems gave the best overall performance, closely followed by Nextflow. © 2018 ieee.

关键词： bioinformatics

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Using easel for modeling and simulating the interactions of cells in order to better understand the basics of biological processes and to predict their likely behaviors 2

Using easel for modeling and simulating the interactions of ...

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2nd International computational systems bioinformatics conference

作者： Stojkovic, V Steele, G Lupton, W MSU Baltimore MD USA

ISBN: (纸本)0769520006

Modeling, simulation, visualization, and animation play a significant role in the study of bioinformatics. Research in this area is generally multidisciplinary in nature and collaboratively conducted by researchers with expertise in biology, bioinformatics, computer science, artificial intelligence, mathematics, and statistics. Easel programming language is used for modeling, simulation, visualization, and animation of interactions of cells in order to better understand the basics of biological processes and to predict their likely behaviors. This paper presents a computer science - modeling, simulation, visualization, and animation approach to such research. The paper provides a brief overview of the basic ideas in the "Message Passing" Easel program to demonstrate the transmission of signals between cells based on their physical proximity.

关键词： bioinformatics

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A Scalable Architecture for Intrusion-Detection systems Based on a Broadband Network of Embedded Set-Top Boxes

A Scalable Architecture for Intrusion-Detection Systems Base...

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54th ieee International Midwest Symposium on Circuits and systems (MWSCAS)

作者： Neill, Richard Carloni, Luca P. Columbia Univ Dept Comp Sci New York NY 10027 USA

ISBN: (纸本)9781612848570

As the processing power of set-top box (STB) devices continnes to grow with each new product generation and multiple service operators directly manage millions of these devices through a dedicated broadband network, we propose to harness this massive aggregate computational power to execute large-scale parallel applications. We present a prototype implementation of a heterogeneous distributed embedded system that combines a complete head-end cable system with a DOCSIS broadband network of STBs and an interoperable embedded implementation of Open MPI running on the STB operating system. We demonstrate the operations and performance of this system by reporting the experimental results that we obtained for the execution of various instances of Multiple Sequence Alignment, a parallel bioinformatics application. Based on these results we propose a new distributed embedded system architecture for highly-scalable intrusion-detection systems.

关键词： Broadband communication DOCSIS broadband network Frequency modulation Linux Radio frequency Servers Transform coding bioinformatics bioinformatics application computer networks dedicated broadband network embedded set-top boxes embedded systems head end cable system heterogeneous distributed embedded system intrusion detection systems large scale parallel applications massive aggregate computational power multiple sequence alignment scalable architecture security of data set-top boxes

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Fractal Genomics modeling: A new approach to genomic analysis and biomarker discovery

Fractal Genomics modeling: A new approach to genomic analysi...

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ieee computational systems bioinformatics conference (CSB 2004)

作者： Shaw, S Shapshak, P Hlth Discovery Corp Inc Savannah GA 31406 USA

ISBN: (纸本)0769521940

Reverse engineering of genetic networks generally requires establishing correlative behavior within and between a very large number of genes. This becomes a difficult analytical problem for even a few hundred genes and the difficulty tends to grow exponentially as more genes are examined Using a hybrid data analysis method known as Fractal Genomics Modeling (FGM), this problem is reduced to examining correlative behavior within small gene groups that can then be compared and integrated to produce a picture of larger networks using a type of shotgun approach. We have applied FGM toward examining genetic networks involved in HIV infection in the brain. These networks have relevance both to processes related to HIV infection and neurodegenerative disorders. Our preliminary findings have produced conjectures of related pathways and networks as well new candidates for genetic markers in HIV brain infection. Evidence has also been produced which appears to show the presence of a hierarchical network structure within the genes studied We will discuss the background and methodology of FGM as well as our recent findings.

关键词： bioinformatics gene expression fractals network theory scale-free brain HIV infection

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Oscillatory dynamics in the mitogen-activated protein kinase cascade

Oscillatory dynamics in the mitogen-activated protein kinase...

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2005 ieee computational systems bioinformatics conference, Workshops and Poster Abstracts

作者： Chiam, K.-H. Bhargava, Vipul Rajagopal, Gunaretnam Bioinformatics Institute 30 Biopolis Street #07-01 Singapore 138671 Singapore

ISBN: (纸本)0769524427

We have used quantitative modeling of signaling networks to show that the mitogen-activated protein kinase cascade - a highly-conserved signaling network in eukaryotes - can functions as a low-pass filter by amplifying low-frequency oscillations and attenuating high-frequency oscillations. This filtering function of the kinase cascade is in addition to other known functions such as being an ultrasensitive switch. We show how this low-pass filtering regulates downstream cellular functions and cellular physiology. We also show how the presence of scaffold proteins in the kinase cascade modifies the properties of the low-pass filter. In particular, we find that the presence of scaffold proteins destroys the properties of the low-pass filtering, and instead attenuate all oscillations. In particular, the higher the scaffold concentration, the greater the attenuation. © 2005 ieee.

关键词： Proteins

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An 8-bit 2 MS/s Successive Approximation Register Analog-To-Digital Converter for bioinformatics and computational Biology Application 12

An 8-bit 2 MS/s Successive Approximation Register Analog-To-...

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ieee 12th International conference on Networking, Sensing and Control

作者： Lai, Wen Cheng Huang, Jhin-Fang Hsieh, Cheng Gu Kao, Fan-Tsai Natl Taiwan Univ Sci & Technol Taipei Taiwan

ISBN: (纸本)9781479980697

In this paper, a 1.8-V 8-bit successive approximation register (SAR) analog-to-digital converter (ADC) implemented in TSMC 0.18-um CMOS process is presented. By applying SAR control logic that reduces half comparator and digital circuit power consumption, the proposed SAR ADC achieves low power consumption. Also, bootstrapped switch method is used to solve varying on-resistance of analog sampling switch caused from varying input signal. Measured results show that at the supply voltage of 1.8 V and sampling rate of 2 MS/s, the proposed SAR ADC achieves a signal-to-noise and distortion ratio (SNDR) of 42.7 dB, an effective number of bits (ENOB) of 6.8 bits, a differential nonlinearity (DNL) of 0.98 LSB, an integral nonlinearity (INL) of 2.01 LSB and a power consumption of 128 mu W. The overall chip area is only 0.67 mm(2) with a small ADC core area of 0.226 mm(2) for bioinformatics and computational Application.

关键词： Analog-to-digital converter successive approximation register bio-signals and systems

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Biomarker Discovery, High Performance and Cloud Computing: A Comprehensive Review

Biomarker Discovery, High Performance and Cloud Computing: A...

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ieee International conference on bioinformatics and Biomedicine - Medical Informatics and Decision Making

作者： Blayney, Jaine Haberland, Valeriia Lightbody, Gaye Browne, Fiona Queens Univ Belfast Sch Med Dent & Biomed Sci Belfast BT7 1NN Antrim North Ireland Univ London Tungsten Ctr Intelligent Data Analyt London WC1E 7HU England Univ Ulster Sch Comp & Math Coleraine BT52 1SA Londonderry North Ireland

ISBN: (纸本)9781467367981

The analysis of biological markers (biomarkers) have the ability to improve clinical outcomes of a disease through prediction and early detection. The constant improvement of next generation sequencing (NGS) technologies coupled with falling equipment price are driving research and application especially in the medical domain. NGS technology is being applied to cancer research promising greater understanding of carcinogenesis. However, as sequence capacity grows, algorithmic speed is becoming an important bottleneck. To understand these challenges we present a review on difficulties currently faced in discovering biomarkers. The review places the spotlight on sequencing technologies and the bottlenecks encountered in these pipelines. Cloud computing and high performance computing technologies such as Grid are summarized in tackling computational challenges presented by technologies and algorithms used in biomarker research.

关键词： bioinformatics Decision support systems Genomics Robustness Sequential analysis

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IAS: Interaction Specific GO Term Associations for Predicting Protein-Protein Interaction Networks

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ieee-ACM TRANSACTIONS ON computational BIOLOGY AND bioinformatics 2018年第4期15卷 1247-1258页

作者： Yerneni, Satwica Khan, Ishita K. Wei, Qing Kihara, Daisuke Mayo Clin Div Biomed Stat & Informat Rochester MN 55905 USA Purdue Univ Dept Comp Sci W Lafayette IN 47906 USA Purdue Univ Dept Biol Sci W Lafayette IN 47906 USA

Proteins carry out their function in a cell through interactions with other proteins. A large scale protein-protein interaction (PPI)network of an organism provides static yet an essential structure of interactions, which is valuable clue for understanding the functions of proteins and pathways. PPIs are determined primarily by experimental methods;however, computational PPI prediction methods can supplement or verify PPIs identified by experiment. Here, we developed a novel scoring method for predicting PPIs from Gene Ontology (GO) annotations of proteins. Unlike existing methods that consider functional similarity as an indication of interaction between proteins, the new score, named the protein-protein Interaction Association Score (IAS), was computed from GO term associations of known interacting protein pairs in 49 organisms. IAS was evaluated on PPI data of six organisms and found to outperform existing GO term-based scoring methods. Moreover, consensus scoring methods that combine different scores further improved performance of PPI prediction.

关键词： bioinformatics proteins computational systems biology biological interactions

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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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A Classification System for Predicting RNA Hairpin Loops

A Classification System for Predicting RNA Hairpin Loops

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International Joint conference on bioinformatics, systems Biology and Intelligent Computing

作者： Aldwairi, Monther Duwairi, Rehab Algarqaz, Wafa'a Jordan Univ Sci & Technol Dept Comp Engn Irbid Jordan

ISBN: (纸本)9780769537399

RiboNucleic Acid (RNA) molecules fold back over themselves to form secondary structures which determine the RNA's functionality in living cells. RNA secondary structure can be determined in laboratory by X-ray diffraction and nuclear magnetic resonance (NMR) techniques. However, these techniques are slow and expensive. Therefore, computational approaches are used to predict the secondary structure of RNA molecules. A new approach. RNA-SSP, for predicting RNA secondary structure elements is proposed. It combines computational approaches and machine learning classifiers to predict individual structure elements using a new search heuristic. The approach is implemented and tested for hairpin loops and a methodology for extending the approach to predict the remaining secondary structure elements is proposed. The experiments showed a significant improvement in prediction accuracy to 95% for stem regions and 80% for loops. The overall weighted-average accuracy for predicting hairpin loop sub-structure is 89% with a sensitivity of 85.29%.

关键词： bioinformatics RNA Secondary Structure Prediction computational RNA

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