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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

A parallel approach to multiple sequences alignment and phylogenetic tree node labelling.

Jingjing Wang¹, Mengxia Zhu

¹Department of Computer Science, Southern Illinois University, Carbondale, IL 62901, USA. jeffwang@cs.siu.edu

International Journal of Computational Biology and Drug Design

|January 14, 2011

Summary

This summary is machine-generated.

This study introduces a parallel algorithm for optimal three sequence alignment, significantly reducing memory usage. It also presents a parallelized node labeling method for evolutionary tree construction.

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Area of Science:

Bioinformatics
Computational Biology
Evolutionary Biology

Background:

Evolutionary trees illustrate species or sequence relationships.
High-quality tree topology depends on efficient Multiple Sequence Alignment (MSA).
Parallel algorithms leverage supercomputing power for MSA.

Purpose of the Study:

To develop an efficient parallel algorithm for optimal three sequence alignment.
To reduce memory costs associated with sequence alignment.
To parallelize the node labeling process in evolutionary tree construction.

Main Methods:

Implementation of a divide and conquer based parallel algorithm for three sequence alignment.
Utilization of a level order based parallel approach for labeling internal nodes.
Development of a two-level nested parallel computing strategy.

Main Results:

Achieved optimal three sequence alignment with significantly reduced memory requirements.
Successfully labeled internal nodes of a parallel Maximum Likelihood tree.
Demonstrated a parallelized node labeling process.

Conclusions:

The developed parallel algorithm enhances the efficiency of sequence alignment.
The parallelized node labeling strategy improves evolutionary tree construction.
This approach offers a more efficient computational method for phylogenetic analysis.