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Related Experiment Video

Updated: Jul 5, 2026

A Simple, Robust, and High Throughput Single Molecule Flow Stretching Assay Implementation for Studying Transport of Molecules Along DNA
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Accelerating string set matching in FPGA hardware for bioinformatics research.

Yoginder S Dandass1, Shane C Burgess, Mark Lawrence

  • 1Institute of Digital Biology, Mississippi State University, Mississippi 39762, USA. yogi@cse.msstate.edu

BMC Bioinformatics
|April 17, 2008
PubMed
Summary
This summary is machine-generated.

This study accelerates computational proteomics by adapting the Aho-Corasick algorithm for Field Programmable Gate Arrays (FPGAs). The optimized FPGA implementation significantly enhances string matching performance for proteogenomic mapping.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Computer Engineering

Background:

  • String set matching is crucial for computational proteomics.
  • Proteogenomic mapping involves matching peptide sequences against translated genomes.
  • Existing methods require efficient algorithms for large-scale data analysis.

Purpose of the Study:

  • To accelerate string set matching for computational proteomics.
  • To adapt the Aho-Corasick algorithm for Field Programmable Gate Array (FPGA) execution.
  • To optimize space and performance in proteogenomic mapping pipelines.

Main Methods:

  • Adapted the Aho-Corasick algorithm for FPGAs.
  • Split the traditional Aho-Corasick finite state machine (FSM) into smaller, parallel FSMs.
  • Further divided FSMs into simpler, bit-position-based FSMs for efficient processing.

Main Results:

  • Achieved storage efficiencies exceeding 80% across various datasets.
  • The FPGA implementation operated at 100 MHz.
  • Demonstrated a performance increase nearly 20 times faster than a traditional workstation implementation.

Conclusions:

  • The bit-split FPGA organization efficiently utilizes FPGA RAM resources.
  • This approach allows rapid FPGA reconfiguration without complex design delays.
  • The optimized Aho-Corasick algorithm offers significant speedups for proteogenomic applications.