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A divide and conquer approach to multiple alignment

A Dress¹, G Füllen, S Perrey

¹Research Center for Studies on Structure Formation (RCSF), University of Bielefeld, Germany.

Proceedings. International Conference on Intelligent Systems for Molecular Biology

|January 1, 1995

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This study introduces a divide and conquer algorithm for multiple sequence alignment, utilizing pairwise alignment costs to efficiently partition sequences. The method aims to reduce computational complexity for large datasets in bioinformatics.

Area of Science:

Bioinformatics
Computational Biology
Algorithm Development

Background:

Multiple sequence alignment is a fundamental task in bioinformatics.
Existing algorithms can be computationally intensive for large datasets.

Purpose of the Study:

To develop an efficient divide and conquer algorithm for multiple sequence alignment.
To reduce the computational complexity of multiple sequence alignment.

Main Methods:

The algorithm uses costs from pairwise alignment dynamic programming.
It calculates secondary matrices for additional costs at specific alignment points.
A weighted sum of pairwise costs estimates the cost of partitioning sequences.

Main Results:

Related Experiment Videos

The divide and conquer approach iteratively halves the problem size.
The method prioritizes promising partitions to manage computational load.
The algorithm is designed to handle large-scale sequence alignment problems.

Conclusions:

The proposed divide and conquer strategy offers a promising approach to scalable multiple sequence alignment.
Further refinement of partition enumeration is key to optimizing performance.
This work contributes to advancing computational methods in bioinformatics.