Ribo

Ribo refines RNA family alignments in the Rfam database by using a game-based human-computing approach to correct and improve non-coding RNA (ncRNA) alignments.

Key Features:

• Human-Computing Integration: Uses a game-based human-computing approach to leverage human pattern recognition for identifying and correcting alignment errors.
• Focus on Non-Coding RNAs (ncRNAs): Targets ncRNA family alignments within Rfam for annotation refinement.
• Collaborative Annotation: Aggregates corrections from multiple participants (crowdsourcing) to generate consensus improvements to alignments.
• Quality Control and Integration: Evaluates user-submitted corrections and integrates validated changes back into the Rfam database.

Scientific Applications:

• Gene Regulation Studies: Improved ncRNA alignments enable more accurate identification of functional elements and analyses of gene regulatory networks.
• Disease Research: Enhanced alignments support investigation of ncRNA involvement in disease mechanisms and aid biomarker or therapeutic target discovery.

Methodology:

Game-based human-computing collects participant-corrected alignments; human pattern recognition is used to identify discrepancies in Rfam alignments; user inputs are evaluated and validated and validated corrections are integrated back into Rfam.