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Sequence pattern matching on a massively parallel computer.

¹Thinking Machines Corporation, Cambridge, MA 02142.

Computer Applications in the Biosciences : CABIOS

|August 1, 1992

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This study introduces a fast method for finding molecular sequence patterns in large databases. The approach enables complex and approximate pattern matching, improving sequence analysis efficiency.

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Molecular sequence databases are crucial for biological research.
Efficiently searching these databases for specific patterns is a significant computational challenge.

Purpose of the Study:

To develop a method for rapid and comprehensive searching of molecular sequence databases.
To enable complex and approximate pattern matching for enhanced biological data analysis.

Main Methods:

Implementation of a novel sequence pattern matching algorithm on a massively parallel computing architecture.
Development of software supporting approximate pattern matching with adjustable score thresholds.
Incorporation of variable-length gap linking for matched sequence elements.

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Main Results:

Achieved very fast database searches for complex molecular sequence patterns.
Successfully implemented approximate pattern matching capabilities.
Enabled flexible pattern matching with score thresholds and gap linking.

Conclusions:

The described method significantly enhances the speed and capability of molecular sequence database searches.
This approach facilitates more sophisticated analysis of complex biological sequence data.
The software provides a powerful tool for researchers in bioinformatics and genomics.