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Updated: Oct 15, 2025
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A Practical Guide to Phylogenetics for Nonexperts
Published on: February 5, 2014
35.5K
PANTHER: Making genome-scale phylogenetics accessible to all.
Paul D Thomas1, Dustin Ebert1, Anushya Muruganujan1
1Division of Bioinformatics, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, USA.
Protein Science : a Publication of the Protein Society
|October 30, 2021
Summary
The Protein Analysis THrough Evolutionary Relationships (PANTHER) knowledgebase provides curated phylogenetic trees and functional annotations for proteins. It aids in understanding protein evolution and function through various analysis tools.
Area of Science:
- Bioinformatics
- Computational Biology
- Evolutionary Biology
Background:
- Phylogenetic analysis of protein sequences is crucial for understanding evolutionary relationships but is computationally intensive and prone to errors.
- Existing methods require careful execution to avoid systematic errors and artifacts.
Purpose of the Study:
- To describe the Protein Analysis THrough Evolutionary Relationships (PANTHER) knowledgebase, its content generation, and applications.
- To provide a user-focused resource for protein sequence analysis.
Main Methods:
- Reconstruction of fully reconciled phylogenetic trees, including ancestral protein sequences, for reference proteins across the tree of life.
- Manual review and annotation of phylogenetic trees with protein function evolution events (gains and losses).
Main Results:
- PANTHER stores extensive results from a phylogenetic reconstruction pipeline with computational, manual, and quality control steps.
- The knowledgebase includes manually reviewed and annotated phylogenetic trees detailing protein function evolution.
Conclusions:
- PANTHER offers a comprehensive, downloadable knowledgebase and API for accessing phylogenetic and functional data.
- Integrated software tools facilitate common protein sequence analysis tasks, including genome exploration, enrichment analysis, homology annotation, and variant effect prediction.
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