ConsAlifold

ConsAlifold predicts consensus RNA secondary structures from RNA sequence alignments by detecting conserved base-pairings among RNA homologs.

Key Features:

• Dynamic Programming-Based Approach: Employs dynamic programming to predict consensus secondary structures from aligned RNA sequences.
• Probabilistic Consideration of Structural Alignments: Incorporates probabilistic models to account for RNA structural alignments and homology in predictions.
• Optimized Performance: Balances running time and prediction accuracy for efficient consensus structure prediction.

Scientific Applications:

• Structural Biology: Identifies conserved structural motifs across RNA families to inform studies of RNA structure and stability.
• Evolutionary Studies: Detects conserved base-pairings among RNA homologs to support analyses of evolutionary relationships.
• Functional Genomics: Characterizes consensus secondary structures of non-coding RNAs to aid investigations of gene regulation.

Methodology:

Uses dynamic programming and probabilistic models to predict consensus secondary structures from RNA sequence alignments.