Folding Paths that start at a single Secondary Structure

Implementation of gradient- and random walks starting from a single secondary structure.

Defines

VRNA_PATH_STEEPEST_DESCENT
#include <ViennaRNA/landscape/walk.h>

Option flag to request a steepest descent / gradient path.

See also

vrna_path()

VRNA_PATH_RANDOM
#include <ViennaRNA/landscape/walk.h>

Option flag to request a random walk path.

See also

vrna_path()

VRNA_PATH_NO_TRANSITION_OUTPUT
#include <ViennaRNA/landscape/walk.h>

Option flag to omit returning the transition path.

See also

vrna_path(), vrna_path_gradient(), vrna_path_random()

VRNA_PATH_DEFAULT
#include <ViennaRNA/landscape/walk.h>

Option flag to request defaults (steepest descent / default move set)

See also

vrna_path(), VRNA_PATH_STEEPEST_DESCENT, VRNA_MOVESET_DEFAULT

Functions

vrna_move_t *vrna_path(vrna_fold_compound_t *fc, short *pt, unsigned int steps, unsigned int options)
#include <ViennaRNA/landscape/walk.h>

Compute a path, store the final structure, and return a list of transition moves from the start to the final structure.

This function computes, given a start structure in pair table format, a transition path, updates the pair table to the final structure of the path. Finally, if not requested otherwise by using the VRNA_PATH_NO_TRANSITION_OUTPUT flag in the options field, this function returns a list of individual transitions that lead from the start to the final structure if requested.

The currently available transition paths are

The type of transitions must be set through the options parameter

SWIG Wrapper Notes:

This function is attached as an overloaded method path() to objects of type fold_compound. The optional parameter options defaults to VRNA_PATH_DEFAULT if it is omitted. See, e.g. RNA.fold_compound.path() in the Python API.

See also

vrna_path_gradient(), vrna_path_random(), vrna_ptable(), vrna_ptable_copy(), vrna_fold_compound() VRNA_PATH_STEEPEST_DESCENT, VRNA_PATH_RANDOM, VRNA_MOVESET_DEFAULT, VRNA_MOVESET_SHIFT, VRNA_PATH_NO_TRANSITION_OUTPUT

Note

Since the result is written to the input structure you may want to use vrna_ptable_copy() before calling this function to keep the initial structure

Parameters:

  • fc – [in] A vrna_fold_compound_t containing the energy parameters and model details

  • pt – [inout] The pair table containing the start structure. Used to update to the final structure after execution of this function

  • options – [in] Options to modify the behavior of this function

Returns:

A list of transition moves (default), or NULL (if options & VRNA_PATH_NO_TRANSITION_OUTPUT)

vrna_move_t *vrna_path_gradient(vrna_fold_compound_t *fc, short *pt, unsigned int options)
#include <ViennaRNA/landscape/walk.h>

Compute a steepest descent / gradient path, store the final structure, and return a list of transition moves from the start to the final structure.

This function computes, given a start structure in pair table format, a steepest descent path, updates the pair table to the final structure of the path. Finally, if not requested otherwise by using the VRNA_PATH_NO_TRANSITION_OUTPUT flag in the options field, this function returns a list of individual transitions that lead from the start to the final structure if requested.

SWIG Wrapper Notes:

This function is attached as an overloaded method path_gradient() to objects of type fold_compound. The optional parameter options defaults to VRNA_PATH_DEFAULT if it is omitted. See, e.g. RNA.fold_compound.path_gradient() in the Python API.

See also

vrna_path_random(), vrna_path(), vrna_ptable(), vrna_ptable_copy(), vrna_fold_compound() VRNA_MOVESET_DEFAULT, VRNA_MOVESET_SHIFT, VRNA_PATH_NO_TRANSITION_OUTPUT

Note

Since the result is written to the input structure you may want to use vrna_ptable_copy() before calling this function to keep the initial structure

Parameters:

  • fc – [in] A vrna_fold_compound_t containing the energy parameters and model details

  • pt – [inout] The pair table containing the start structure. Used to update to the final structure after execution of this function

  • options – [in] Options to modify the behavior of this function

Returns:

A list of transition moves (default), or NULL (if options & VRNA_PATH_NO_TRANSITION_OUTPUT)

vrna_move_t *vrna_path_random(vrna_fold_compound_t *fc, short *pt, unsigned int steps, unsigned int options)
#include <ViennaRNA/landscape/walk.h>

Generate a random walk / path of a given length, store the final structure, and return a list of transition moves from the start to the final structure.

This function generates, given a start structure in pair table format, a random walk / path, updates the pair table to the final structure of the path. Finally, if not requested otherwise by using the VRNA_PATH_NO_TRANSITION_OUTPUT flag in the options field, this function returns a list of individual transitions that lead from the start to the final structure if requested.

SWIG Wrapper Notes:

This function is attached as an overloaded method path_gradient() to objects of type fold_compound. The optional parameter options defaults to VRNA_PATH_DEFAULT if it is omitted. See, e.g. RNA.fold_compound.path_random() in the Python API.

See also

vrna_path_gradient(), vrna_path(), vrna_ptable(), vrna_ptable_copy(), vrna_fold_compound() VRNA_MOVESET_DEFAULT, VRNA_MOVESET_SHIFT, VRNA_PATH_NO_TRANSITION_OUTPUT

Note

Since the result is written to the input structure you may want to use vrna_ptable_copy() before calling this function to keep the initial structure

Parameters:

  • fc – [in] A vrna_fold_compound_t containing the energy parameters and model details

  • pt – [inout] The pair table containing the start structure. Used to update to the final structure after execution of this function

  • steps – [in] The length of the path, i.e. the total number of transitions / moves

  • options – [in] Options to modify the behavior of this function

Returns:

A list of transition moves (default), or NULL (if options & VRNA_PATH_NO_TRANSITION_OUTPUT)