The Experts below are selected from a list of 116691 Experts worldwide ranked by ideXlab platform

Jinn-shyan Wang - One of the best experts on this subject based on the ideXlab platform.

  • An Adaptively Dividable Dual-Port BiTCAM for Virus-Detection Processors in Mobile Devices
    IEEE Journal of Solid-state Circuits, 2009
    Co-Authors: Chao-ching Wang, Chieh-jen Cheng, Tien-fu Chen, Jinn-shyan Wang
    Abstract:

    Network security for mobile devices is in high demand because of the increasing Virus count. Since mobile devices have limited CPU power, dedicated hardware is essential to provide sufficient Virus Detection performance. A TCAM-based Virus-Detection unit provides high throughput, but also challenges for low power and low cost. In this paper, an adaptively dividable dual-port BiTCAM (unifying binary and ternary CAMs) is proposed to achieve a high-throughput, low-power, and low-cost Virus-Detection processor for mobile devices. The proposed dual-port BiTCAM is realized with the dual-port AND-type match-line scheme which is composed of dual-port dynamic AND gates. The dual-port designs reduce power consumption and increase storage efficiency due to shared storage spaces. In addition, the dividable BiTCAM provides high flexibility for regularly updating the Virus-database. The BiTCAM achieves a 48% power reduction and a 40% transistor count reduction compared with the design using a conventional single-port TCAM. The implemented 0.13 mum processor performs up to 3 Gbps Virus Detection with an energy consumption of 0.44 fJ/pattern-byte/scan at peak throughput.

  • ISSCC - An Adaptively Dividable Dual-Port BiTCAM for Virus-Detection Processors in Mobile Devices
    2008 IEEE International Solid-State Circuits Conference - Digest of Technical Papers, 2008
    Co-Authors: Chao-ching Wang, Chieh-jen Cheng, Tien-fu Chen, Jinn-shyan Wang
    Abstract:

    Network security is in high demand because of increasing network attacks. As mobile devices have limited CPU power, dedicated hardware is required to provide sufficient Virus Detection performance with a small energy cost. We present an adaptively dividable dual-port BiTCAM, which unifies binary and ternary CAM, in a Virus-Detection processor for mobile devices. The BiTCAM design achieves a 48% power-consumption reduction and a 40% transistor-count reduction compared to a design with two separate single-port TCAMs.

Hans J Maree - One of the best experts on this subject based on the ideXlab platform.

  • targeted Virus Detection in next generation sequencing data using an automated e probe based approach
    Virology, 2016
    Co-Authors: Marike Visser, Johan T Burger, Hans J Maree
    Abstract:

    The use of next-generation sequencing for plant Virus Detection is rapidly expanding, necessitating the development of bioinformatic pipelines to support analysis of these large datasets. Pipelines need to be easy implementable to mitigate potential insufficient computational infrastructure and/or skills. In this study user-friendly software was developed for the targeted Detection of plant Viruses based on e-probes. It can be used for both custom e-probe design, as well as screening preloaded probes against raw NGS data for Virus Detection. The pipeline was compared to de novo assembly-based Virus Detection in grapevine and produced comparable results, requiring less time and computational resources. The software, named Truffle, is available for the design and screening of e-probes tailored for user-specific Virus species and data, along with preloaded probe-sets for grapevine Virus Detection.

  • Next-generation sequencing for Virus Detection: covering all the bases
    Virology Journal, 2016
    Co-Authors: Marike Visser, Johan T Burger, Rachelle Bester, Hans J Maree
    Abstract:

    Background The use of next-generation sequencing has become an established method for Virus Detection. Efficient study design for accurate Detection relies on the optimal amount of data representing a significant portion of a Virus genome.

Christophe Lambert - One of the best experts on this subject based on the ideXlab platform.

  • Considerations for Optimization of High-Throughput Sequencing Bioinformatics Pipelines for Virus Detection.
    Viruses, 2018
    Co-Authors: Christophe Lambert, Robert L. Charlebois, Cassandra Braxton, Avisek Deyati, Paul Duncan, Fabio La Neve, Heather D. Malicki, Sebastien Ribrioux, Daniel K. Rozelle, Brandye Michaels
    Abstract:

    : High-throughput sequencing (HTS) has demonstrated capabilities for broad Virus Detection based upon discovery of known and novel Viruses in a variety of samples, including clinical, environmental, and biological. An important goal for HTS applications in biologics is to establish parameter settings that can afford adequate sensitivity at an acceptable computational cost (computation time, computer memory, storage, expense or/and efficiency), at critical steps in the bioinformatics pipeline, including initial data quality assessment, trimming/cleaning, and assembly (to reduce data volume and increase likelihood of appropriate sequence identification). Additionally, the quality and reliability of the results depend on the availability of a complete and curated viral database for obtaining accurate results; selection of sequence alignment programs and their configuration, that retains specificity for broad Virus Detection with reduced false-positive signals; removal of host sequences without loss of endogenous viral sequences of interest; and use of a meaningful reporting format, which can retain critical information of the analysis for presentation of readily interpretable data and actionable results. Furthermore, after alignment, both automated and manual evaluation may be needed to verify the results and help assign a potential risk level to residual, unmapped reads. We hope that the collective considerations discussed in this paper aid toward optimization of data analysis pipelines for Virus Detection by HTS.

  • Advanced Virus Detection Technologies Interest Group (AVDTIG): Efforts on High Throughput Sequencing (HTS) for Virus Detection
    Pda Journal of Pharmaceutical Science and Technology, 2016
    Co-Authors: Arifa S. Khan, Dominick A. Vacante, Jean-pol Cassart, Siemon H. S. Ng, Robert L. Charlebois, Christophe Lambert, Kathryn E. King
    Abstract:

    Several nucleic-acid based technologies have recently emerged with capabilities for broad Virus Detection. One of these, high throughput sequencing, has the potential for novel Virus Detection because this method does not depend upon prior viral sequence knowledge. However, the use of high throughput sequencing for testing biologicals poses greater challenges as compared to other newly introduced tests due to its technical complexities and big data bioinformatics. Thus, the Advanced Virus Detection Technologies Users Group was formed as a joint effort by regulatory and industry scientists to facilitate discussions and provide a forum for sharing data and experiences using advanced new Virus Detection technologies, with a focus on high throughput sequencing technologies. The group was initiated as a task force that was coordinated by the Parenteral Drug Association and subsequently became the Advanced Virus Detection Technologies Interest Group to continue efforts for using new technologies for Detection of adventitious Viruses with broader participation, including international government agencies, academia, and technology service providers.

Chao-ching Wang - One of the best experts on this subject based on the ideXlab platform.

  • An Adaptively Dividable Dual-Port BiTCAM for Virus-Detection Processors in Mobile Devices
    IEEE Journal of Solid-state Circuits, 2009
    Co-Authors: Chao-ching Wang, Chieh-jen Cheng, Tien-fu Chen, Jinn-shyan Wang
    Abstract:

    Network security for mobile devices is in high demand because of the increasing Virus count. Since mobile devices have limited CPU power, dedicated hardware is essential to provide sufficient Virus Detection performance. A TCAM-based Virus-Detection unit provides high throughput, but also challenges for low power and low cost. In this paper, an adaptively dividable dual-port BiTCAM (unifying binary and ternary CAMs) is proposed to achieve a high-throughput, low-power, and low-cost Virus-Detection processor for mobile devices. The proposed dual-port BiTCAM is realized with the dual-port AND-type match-line scheme which is composed of dual-port dynamic AND gates. The dual-port designs reduce power consumption and increase storage efficiency due to shared storage spaces. In addition, the dividable BiTCAM provides high flexibility for regularly updating the Virus-database. The BiTCAM achieves a 48% power reduction and a 40% transistor count reduction compared with the design using a conventional single-port TCAM. The implemented 0.13 mum processor performs up to 3 Gbps Virus Detection with an energy consumption of 0.44 fJ/pattern-byte/scan at peak throughput.

  • ISSCC - An Adaptively Dividable Dual-Port BiTCAM for Virus-Detection Processors in Mobile Devices
    2008 IEEE International Solid-State Circuits Conference - Digest of Technical Papers, 2008
    Co-Authors: Chao-ching Wang, Chieh-jen Cheng, Tien-fu Chen, Jinn-shyan Wang
    Abstract:

    Network security is in high demand because of increasing network attacks. As mobile devices have limited CPU power, dedicated hardware is required to provide sufficient Virus Detection performance with a small energy cost. We present an adaptively dividable dual-port BiTCAM, which unifies binary and ternary CAM, in a Virus-Detection processor for mobile devices. The BiTCAM design achieves a 48% power-consumption reduction and a 40% transistor-count reduction compared to a design with two separate single-port TCAMs.

Brandye Michaels - One of the best experts on this subject based on the ideXlab platform.

  • Considerations for Optimization of High-Throughput Sequencing Bioinformatics Pipelines for Virus Detection.
    Viruses, 2018
    Co-Authors: Christophe Lambert, Robert L. Charlebois, Cassandra Braxton, Avisek Deyati, Paul Duncan, Fabio La Neve, Heather D. Malicki, Sebastien Ribrioux, Daniel K. Rozelle, Brandye Michaels
    Abstract:

    : High-throughput sequencing (HTS) has demonstrated capabilities for broad Virus Detection based upon discovery of known and novel Viruses in a variety of samples, including clinical, environmental, and biological. An important goal for HTS applications in biologics is to establish parameter settings that can afford adequate sensitivity at an acceptable computational cost (computation time, computer memory, storage, expense or/and efficiency), at critical steps in the bioinformatics pipeline, including initial data quality assessment, trimming/cleaning, and assembly (to reduce data volume and increase likelihood of appropriate sequence identification). Additionally, the quality and reliability of the results depend on the availability of a complete and curated viral database for obtaining accurate results; selection of sequence alignment programs and their configuration, that retains specificity for broad Virus Detection with reduced false-positive signals; removal of host sequences without loss of endogenous viral sequences of interest; and use of a meaningful reporting format, which can retain critical information of the analysis for presentation of readily interpretable data and actionable results. Furthermore, after alignment, both automated and manual evaluation may be needed to verify the results and help assign a potential risk level to residual, unmapped reads. We hope that the collective considerations discussed in this paper aid toward optimization of data analysis pipelines for Virus Detection by HTS.