The RNAfold web server will predict secondary structures of single stranded RNA or DNA sequences. Current limits are 7,500 nt for partition function calculations and 10,000 nt for minimum free energy only predicitions.

Simply paste or upload your sequence below and click Proceed. To get more information on the meaning of the options click the symbols. You can test the server using this sample sequence.

Paste or type your sequence here:

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Show constraint folding

| : paired with another base		> : base i is paired with a base j>i
x : base must not pair		< : base i is paired with a base j<i
. : no constraint at all		matching brackets ( ): base i pairs base j

Paste or type your structure constraint using the symbols described above here:

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 Enforce Constrained pairing pattern

Enforce base pairs and pairing preferences given in the structure constraint instead of just removing all conflicting pairs.

Note: The string for the structure constraint must be of the length of the sequence. Leave this field blank if no constaints should be applied during structure predicitions.

Or upload a file in FASTA format:

 Fold algorithms and basic options 

	minimum free energy (MFE) and partition function Calculate the partition function and base pairing probability matrix in addition to the minimum free energy (MFE) structure.
	minimum free energy (MFE) only Predicts only the optimal secondary structure.
	no GU pairs at the end of helices Apart from the canonical AU and GC pairs RNA frequently forms (weaker) GU pairs. Check this box to disallow GU at the end of helices.
	avoid isolated base pairs Predicted structures can contain isolated base pairs (helices of length 1), which may be undesirable. Check this box to avoid such lonely pairs.

Show advanced options

 Advanced folding options 

Dangling end options

Dangling end energies are stabilizing energies assigned to unpaired bases adjacent to a helix in multi-loops and free ends.

   no dangling end energies
   unpaired bases can participate in at most one dangling end (MFE folding only)
   dangling energies on both sides of a helix in any case
   allow coaxial stacking of adjacent helices in multi-loops (MFE folding only)

Energy Parameters

Change the energy parameter file used to predict secondary structures.

   RNA parameters (Turner model, 2004)
   RNA parameters (Turner model, 1999)
   RNA parameters (Andronescu model, 2007)
   DNA parameters (Matthews model, 2004)

SHAPE reactivity data

Use SHAPE reactivity data to guide the prediction according to experimental data.

Paste or type your SHAPE reactivity data here:

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Or upload a file with the reactivities:

After conversion of SHAPE reactivities, apply pseudo energies to: Stacked pairs (Deigan et al. 2009) All loops (Zarringhalam et al. 2012) Pertubation vector (Washietl et al. 2012)

Please enter non-default parameters for selected method if necessary:

slope (m): intercept (b):

beta (b):
Convert SHAPE reactivities into pairing probabilities using: Linear Mapping Cutoff Identity (Skip normalization) Linear model Linear log model cutoff threshold: slope (s) intercept (i) slope (s) intercept (i)

Other Parameters
   rescale energy parameters to given temperature (C)

The energy parameters used in the calculation have been measured at 37C. Parameters at other temperatures can be extrapolated, but for temperatures far from 37C results will be increasingly unreliable.

   assume RNA molecule to be circular

RNA molecule is treated to be circular. Since Vienna RNA package v. 1.7 this options is also valid for partition function folding.

   Incorporate G–Quadruplex formation into the structure prediction algorithm

Incorporate G–Quadruplex formation into the structure prediction algorithm

 Output options 

	interactive RNA secondary structure plot Generates an interactive SVG-File displaying reliability information.
	RNA secondary structure plots with reliability annotation (Partition function folding only) Colorize a secondary structure plot with reliability annotation from positional entropy and base-pairing probabilities.
	Mountain plot A mountain plot represents a secondary structure in a plot of height versus position, where the height m(k) is given by the number of base pairs enclosing the base at position k. I.e. loops correspond to plateaus (hairpin loops are peaks), helices to slopes. Check this box to produce a PNG image with the mountain plot.

Notification via e-mail upon completion of the job (optional):