• DocumentCode
    3706211
  • Title

    A hardware approach to protein identification

  • Author

    Gea Bianchi;Fabiola Casasopra;Gianluca C. Durelli;Marco D. Santambrogio

  • Author_Institution
    Politecnico di Milano, Italy, Dipartimento di Elettronica Informazione e Bioingegneria
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    At the basis of proteins identification we have a string matching algorithm, which has a computational complexity that scales with the length of both the searched and the reference string. This complexity, as well as the fact that to match a single protein we need multiple search of different string in the whole database, makes the protein identification a computational intensive task taking tens of seconds to complete. When performing this task with General Purpose Processors (GPPs), as it might be in a large scale installation (such as medical or research centers), this long execution time translates into a high energy requirement which greatly impacts the scalability and maintenance cost of the system. This paper illustrates a possible way to exploit Field Programmable Gate Arrays (FPGAs) to implement a string matching algorithm with an higher energy efficiency, up to 6 times better, than a standard GPP; such solution can be a building block for large-scale installations aimed at improving protein identification.
  • Keywords
    "Proteins","Peptides","Program processors","Databases","Field programmable gate arrays","Algorithm design and analysis","Proteomics"
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Circuits and Systems Conference (BioCAS), 2015 IEEE
  • Type

    conf

  • DOI
    10.1109/BioCAS.2015.7348382
  • Filename
    7348382