Phylo

Phylo leverages human-based computing to improve multiple sequence alignment (MSA) of DNA, RNA, and protein sequences by converting alignment problems into crowd-sourced game tasks that augment computational alignment algorithms.

Key Features:

• Crowd-sourced intelligence: Converts MSA problems into game-based tasks so human contributors provide alignment adjustments that complement algorithmic outputs.
• Open-Phylo platform: Operates within the Open-Phylo framework and allows scientists to submit their own datasets for crowd-assisted analysis.
• Sequence type support: Targets multiple sequence alignment for DNA, RNA, and protein sequences to identify regions of similarity across sequences.
• Human–computer integration: Integrates human intuition and pattern recognition with traditional computational alignment algorithms to enhance accuracy and efficiency.

Scientific Applications:

• Multiple sequence alignment (MSA): Produces and refines alignments of three or more biological sequences (DNA, RNA, or proteins) to detect conserved regions.
• Phylogenetic analysis: Supports inference of evolutionary relationships by improving alignment quality used for phylogeny reconstruction.
• Functional genomics and gene function prediction: Aids identification of conserved functional elements and informs gene function prediction through improved alignments.

Methodology:

Phylo converts MSA problems into game-based tasks for crowd-sourced human alignment input and integrates those human contributions with computational alignment algorithms to leverage human pattern recognition and improve algorithmic accuracy and efficiency.