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Updated: May 24, 2026

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Phylo: a citizen science approach for improving multiple sequence alignment.

Alexander Kawrykow¹, Gary Roumanis, Alfred Kam

¹School of Computer Science and McGill Centre for Bioinformatics, McGill University, Montreal, Quebec, Canada.

|March 14, 2012

Summary

This summary is machine-generated.

Citizen science games like Phylo leverage human problem-solving skills to improve multiple sequence alignment (MSA) accuracy. This approach transforms complex computational biology problems into engaging games for the public.

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An Integrated Approach for Microprotein Identification and Sequence Analysis

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Area of Science:

Computational Biology
Genomics
Citizen Science

Background:

Comparative genomics aids evolution studies and disease research by analyzing genome structure and function across species.
Multiple Sequence Alignment (MSA) is crucial for genomic analysis but presents significant computational challenges.
Citizen science utilizes human cognitive abilities for complex computational tasks, increasingly through game-based platforms.

Purpose of the Study:

To introduce Phylo, a human-based computing framework for solving the Multiple Sequence Alignment (MSA) problem.
To demonstrate the efficacy of crowd-sourcing techniques in computational biology.
To explore the potential of citizen science in addressing computationally intensive biological research.

Main Methods:

Developed Phylo, a framework converting the MSA problem into a casual online game accessible to non-experts.
Applied Phylo to align promoters of disease-related genes across 44 vertebrate species.
Collected over 350,000 solutions from more than 12,000 registered users since November 2010.

Main Results:

Phylo significantly improved the accuracy of alignment blocks, with contributions to up to 70% of blocks analyzed.
The framework successfully engaged a large number of citizen scientists in a complex biological task.
Demonstrated the practical application of crowd computing in enhancing genomic analysis.

Conclusions:

Crowd computing, when integrated with traditional algorithms, can enhance the accuracy of Multiple Sequence Alignment.
Complex computational problems, such as those in bioinformatics, can be effectively addressed through casual, game-based citizen science initiatives.
Citizen science offers a scalable solution to harness collective human intelligence for scientific advancement, tapping into 'human-brain peta-flops'.