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Related Experiment Video

Updated: Jun 4, 2026

DNA Sequence Recognition by DNA Primase Using High-Throughput Primase Profiling

DNA Sequence Recognition by DNA Primase Using High-Throughput Primase Profiling

Published on: October 8, 2019

Generalised sequence signatures through symbolic clustering.

Dietmar H Dorr¹, Anne M Denton

¹Research and Development, Thomson Reuters, St. Paul, MN 55123, USA. dietmar.dorr@thomsonreuters.com

International Journal of Data Mining and Bioinformatics

|March 2, 2011

Summary

This summary is machine-generated.

This study introduces Generalised Sequence Signatures (GSS), an algorithm identifying sequence patterns with flexible regions. GSS offers higher confidence in sequence annotations compared to traditional methods.

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Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Traditional sequence motif and domain identification methods struggle with insertions, deletions, and mismatches.
Existing approaches often require matched regions to be significantly larger than variations.

Purpose of the Study:

To develop a novel algorithm for identifying Generalised Sequence Signatures (GSS).
To enable the recognition of sequence patterns with distributed, flexible regions.
To improve the confidence of sequence annotation through a new signature recognition method.

Main Methods:

Developed an algorithm based on clustering analysis of recurring subsequences ('symbols').
Sequences are grouped to maximize the number of shared symbols.
Identified Generalised Sequence Signatures (GSS) composed of distributed windows.

Main Results:

The Generalised Sequence Signatures (GSS) algorithm successfully identifies sequence patterns with variable regions.
Clustering analysis of recurring subsequences effectively groups related sequences.
GSS demonstrates higher confidence values in deriving sequence annotations compared to existing methods.

Conclusions:

Generalised Sequence Signatures (GSS) provide a more robust method for sequence pattern identification.
This approach enhances the accuracy and reliability of sequence annotation in bioinformatics.
GSS offers a significant advancement over traditional signature recognition techniques.