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Updated: May 26, 2026

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Accelerated large-scale multiple sequence alignment.

Scott Lloyd¹, Quinn O Snell

¹Computer Science Department, Brigham Young University, Provo, UT 84602, USA. gscott@byu.edu

BMC Bioinformatics

|December 14, 2011

Summary

This summary is machine-generated.

This study accelerates the third stage of multiple sequence alignment (MSA) using reconfigurable computing. An FPGA accelerator achieved a 150x speedup, enabling larger biological analyses.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Multiple sequence alignment (MSA) is crucial for bioinformatics and comparative genomics.
Previous acceleration efforts focused only on the first stage of MSA, limiting performance gains.
This research pioneers the acceleration of the third stage of progressive alignment on reconfigurable hardware.

Purpose of the Study:

To accelerate the third stage of multiple sequence alignment (MSA) using reconfigurable computing.
To overcome performance limitations imposed by Amdahl's Law in prior MSA acceleration methods.

Main Methods:

Developed a parallel algorithm and architecture for MSA acceleration.
Reduced aligned sequence subgroups into discrete profiles before pairwise alignment.
Utilized a Field-Programmable Gate Array (FPGA) accelerator for computation.

Main Results:

Achieved an overall speedup of up to 150x on a large dataset.
Outperformed a 2.4 GHz Core2 processor in MSA tasks.
Demonstrated significant acceleration for the third stage of progressive alignment.

Conclusions:

The developed parallel algorithm and architecture effectively accelerate large-scale MSA using reconfigurable computing.
This advancement enables researchers to tackle larger and more complex biological problems.
Source code is publicly available for further research and application.