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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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Reconfigurable hardware-software codesign methodology for protein identification.

Venkateshwarlu Y Gudur, Sandeep Thallada, Abhinay R Deevi

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 9, 2017
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a flexible hardware-software system for rapid protein identification. The reconfigurable design accelerates biomarker discovery and protein analysis in real-time, adapting to new data without hardware changes.

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    Area of Science:

    • Biotechnology
    • Bioinformatics
    • Computer Engineering

    Background:

    • The increasing volume of sequenced data and identified biomarkers necessitates advanced processing capabilities.
    • Current systems often require hardware modifications for new protein or biomarker discoveries.

    Purpose of the Study:

    • To propose an on-the-fly reconfigurable hardware-software codesign solution for real-time protein identification.
    • To enhance flexibility and adaptability in biomarker discovery and protein analysis.

    Main Methods:

    • Implementation of reconfigurable string matching algorithms.
    • Hardware-software codesign for an adaptive system.
    • Testing on the human proteome database (UniProtKB, ID up000005640) with 42,132 proteins.

    Main Results:

    • The proposed system demonstrates favorable performance compared to state-of-the-art methods.
    • Achieved real-time protein identification and biomarker discovery capabilities.
    • Validated on a comprehensive human proteome dataset.

    Conclusions:

    • The developed on-the-fly reconfigurable system offers a flexible and efficient solution for real-time protein identification.
    • This approach facilitates adaptability in medical science with evolving biomarker and protein data.
    • The system provides a significant advantage for the medical science community by avoiding complete hardware overhauls.