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Updated: Feb 23, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

Optimizing Phylogenetic Queries for Performance.

IEEE/ACM Transactions on Computational Biology and Bioinformatics

|September 1, 2017

Summary

This summary is machine-generated.

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Phylogenetic databases lack flexible querying. A new visual query language, PhyQL, offers powerful, phylogeny-specific querying and optimization strategies for large datasets.

Area of Science:

Bioinformatics
Computational Biology
Phylogenetics

Background:

Phylogenetic databases lack declarative querying capabilities, limiting data access and flexibility.
Existing general-purpose graph query languages are often too complex and inefficient for biological applications.

Purpose of the Study:

Introduce PhyQL, a visual query language tailored for phylogenetic data.
Develop and evaluate query optimization strategies for large-scale phylogenetic analysis.

Main Methods:

Leveraging phylogeny-specific properties within the PhyQL visual query language.
Developing pruning aids and query optimization strategies, including hybrid approaches with indexing and graphlet partitioning.
Implementing a "fail soonest" strategy to enhance processing efficiency.

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A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Related Experiment Videos

Last Updated: Feb 23, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Main Results:

PhyQL supports essential and powerful constructs for a wide range of phylogenetic queries.
Proposed optimization strategies are suitable for large phylogeny querying.
The "fail soonest" strategy demonstrates significant benefits in avoiding inefficient processing.

Conclusions:

PhyQL provides a more accessible and efficient solution for querying phylogenetic databases.
Advanced optimization techniques are crucial for handling large phylogenetic datasets.
Further exploration of novel optimization techniques holds potential for future advancements.