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Updated: May 18, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

Negative information for building phylogenies.

Supaporn Chairungsee¹, Maxime Crochemore

¹Department of Informatics, King's College London, London WC2R 2LS, United Kingdom. supaporn.chairungsee@kcl.ac.uk

Recent Patents on DNA & Gene Sequences

|September 15, 2012

Summary

This summary is machine-generated.

Researchers developed an efficient method to find minimal absent words in DNA sequences. This technique aids in distinguishing between different organisms and constructing phylogenetic trees.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Minimal absent words are segments not present in a sequence, with all their sub-segments present.
This concept is related to, but stronger than, shortest absent words.
Identifying these words can reveal unique characteristics of biological sequences.

Purpose of the Study:

To present an efficient method for computing minimal absent words of bounded length in DNA sequences.
To demonstrate the utility of minimal absent words for distinguishing between sequences of different organisms.
To develop a method for constructing phylogenetic trees based on sequence discrimination.

Main Methods:

Utilized a Trie of bounded depth to represent bounded length factors of DNA sequences.
Developed a linear-time algorithm for computing the complete set of minimal absent words.
Applied a length-weighted index to discriminate between DNA sequences.

Main Results:

The proposed method efficiently computes all minimal absent words of bounded length.
The algorithm offers improved memory usage compared to existing solutions.
The approach successfully distinguishes between sequences from different organisms.
Phylogenetic trees were constructed based on the sequence discrimination results.

Conclusions:

The Trie-based method provides an efficient and memory-conscious way to compute minimal absent words in DNA.
Minimal absent words are effective features for sequence discrimination and phylogenetic analysis.
This approach has potential applications in comparative genomics and evolutionary studies.