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Related Experiment Video

Updated: Jan 18, 2026

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

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Trace alignment and some of its applications

¹Informatics Group, Sanger Centre, Cambridge, UK.

Bioinformatics (Oxford, England)

|April 1, 1998

Summary

Analyzing DNA chromatogram traces offers more information than DNA sequences alone. A new dynamic programming algorithm aids in aligning these traces for various sequencing applications.

Area of Science:

Molecular Biology
Bioinformatics

Background:

DNA chromatogram traces contain valuable data beyond base-called sequences.
Examining these traces can enhance numerous DNA sequencing applications.

Purpose of the Study:

To describe and implement a novel algorithm for aligning DNA chromatograms to DNA sequences.
To demonstrate the utility of this algorithm in key molecular biology applications.

Main Methods:

Development of a dynamic programming algorithm for DNA chromatogram-sequence alignment.
Implementation and testing of the algorithm on specific bioinformatics tasks.

Main Results:

Successfully aligned DNA chromatograms to DNA sequences using the developed algorithm.

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Demonstrated effectiveness in vector clipping, EST alignment, and mutation detection.

Conclusions:

The dynamic programming algorithm provides a robust method for extracting additional information from DNA chromatogram traces.
This approach offers significant benefits for various DNA sequencing and analysis workflows.