bio-rna-structure-secondary-structure-prediction
Predicts RNA secondary structures using minimum free energy folding and partition function analysis with ViennaRNA (RNAfold, RNAalifold, RNAcofold). Computes base-pair probabilities, centroid structures, and consensus structures from alignments. Use when predicting RNA folding, evaluating structural stability, or comparing structures across homologs.
npx skills add BioTender-max/awesome-bio-agent-skills --skill secondary-structure-prediction --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Version Compatibility Reference examples tested with: Infernal 1.1+, matplotlib 3.8+, numpy 1.26+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures - CLI: `<tool> --version` then `<tool> --help` to confirm flags If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Secondary Structure Prediction **"Predict the secondary structure of my RNA sequence"** → Compute minimum free energy (MFE) folding, base-pair probabilities via partition function, and consensus structures from alignments using thermodynamic models. - CLI: `RNAfold` for single-sequence MFE/partition folding - CLI: `RNAalifold` for consensus structure from alignment - CLI: `RNAcofold` for RNA-RNA interaction structure Predict RNA secondary structures using thermodynamic models. ViennaRNA provides MFE folding, partition function analysis, consensus structure prediction from alignments, and RNA-RNA interaction prediction. ## RNAfold: Single Sequence Folding ### MFE Structure ```bash # Basic MFE folding (rea
- Version Compatibility
- RNAfold: Single Sequence Folding
- MFE Structure
- Key RNAfold Options
- Constrained Folding
- RNAalifold: Consensus Structure from Alignment
- RNAcofold: RNA-RNA Interaction
- LinearFold: Fast Folding for Long Sequences
- ViennaRNA Python API
- Folding with Constraints (Python)
- SHAPE-Constrained Folding (Python)
- Structure Comparison
- Structure Formats
- Format Conversion
Basic MFE folding (reads sequence from stdin or file)
echo "GGGAAACCC" | RNAfold
With partition function (-p) and base-pair probabilities
echo "GGGAAACCC" | RNAfold -p
Output PostScript dot plot and structure plot
echo ">myRNA" > input.fa
echo "GGGCUAUUAGCUCAGUUGGUUAGAGCGCACCCCUGAUAAGGGUGAGGUCGCUGAUUCGAAUUCAGCAUAGCCCA" >> input.fa
RNAfold -p --noPS < input.fa # Suppress PostScript files
Force specific positions paired/unpaired
Constraint notation: '.' = unconstrained, 'x' = unpaired, '(' ')' = forced pairWhat does the bio-rna-structure-secondary-structure-prediction skill do?
Predicts RNA secondary structures using minimum free energy folding and partition function analysis with ViennaRNA (RNAfold, RNAalifold, RNAcofold). Computes base-pair probabilities, centroid structures, and consensus structures from alignments. Use when predicting RNA folding, evaluating structural stability, or comparing structures across homologs.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill secondary-structure-prediction --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.