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RNAStructureIdentifier

A Mathematica package for identifying the target secondary structure from RNA structure ensemble.

Amongst other things, our implementations allow you to:

  • compute the ensemble tree, a hierarchical bi-partition of the ensemble of structures
  • calculate the base pairs having maximum information entropy
  • predict the target structure via recursively querying about whether or not a base pair of maximum entropy is contained in the target
  • visualize the ensemble tree, together with base pairs of maximum entropy
  • draw a single secondary structure as a diagram
  • present an ensemble of secondary structures as a greyscale diagram

Introduction

The package focuses on how to identify a target from a Boltzmann ensemble of secondary structures. The key idea is to employ an information-theoretic approach to solve the problem, via considering a variant of the Rényi-Ulam game. Our framework is centered around the ensemble tree, a hierarchical bi-partition of the input ensemble, that is constructed by recursively querying about whether or not a base pair of maximum information entropy is contained in the target. These queries are answered via relating local with global chemical probing data, employing the modularity in RNA secondary structures (see References).

In 1, we present that leaves of the tree are comprised of sub-samples exhibiting a distinguished structure with high probability. In particular, for a Boltzmann ensemble incorporating probing data, which is well established in the literature, the probability of our framework correctly identifying the target in the leaf is greater than 90%.

Demonstration

We present a demo of the ensemble trees for 5S rRNA, riboswitch and long non-coding RNA.

Installation

To use the package, the only thing you need to install is Wolfram Mathematica Free Trial.

We have tested our package using Mathematica versions 11.3.0 and 12.0.0 under UNIX and Windows system.

Usage

Download the package to your Notebook directory and load the pacakge with

Get[NotebookDirectory[] <> "RNAStructureIdentifier.wl"]

Quick Start

We provide a quick tutorial (tutorial.nb) to demonstrate functions by examples.

References

If you use our package, you may want to cite the follwing publications:

  1. Thomas J.X. Li and Christian M. Reidys (2020) "On an enhancement of RNA probing data using Information Theory", Algorithms for Molecular Biology, 15: 15.

Contact

We need your feedback! Send your comments, suggestions, and questions to gauss.backyard@gmail.com

Thomas Li, Autumn 2019

About

Identifying the target secondary structure from RNA structure ensemble

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RNAStructureIdentifier
A Mathematica package for identifying the target secondary structure from RNA structure ensemble.
Amongst other things, our implementations allow you to:
  • compute the ensemble tree, a hierarchical bi-partition of the ensemble of structures
  • calculate the base pairs having maximum information entropy
  • predict the target structure via recursively querying about whether or not
a base pair of maximum entropy is contained in the target
  • visualize the ensemble tree, together with base pairs of maximum entropy
  • draw a single secondary structure as a diagram
  • present an ensemble of secondary structures as a greyscale diagram
Introduction
The package focuses on how to identify a target from a Boltzmann ensemble of secondary structures. The key idea is to employ an information-theoretic approach to solve the problem, via considering a variant of the Rényi-Ulam game. Our framework is centered around the ensemble tree, a hierarchical bi-partition of the input ensemble, that is constructed by recursively querying about whether or not a base pair of maximum information entropy is contained in the target. These queries are answered via relating local with global chemical probing data, employing the modularity in RNA secondary structures (see References).
In 1, we present that leaves of the tree are comprised of sub-samples exhibiting a distinguished structure with high probability. In particular, for a Boltzmann ensemble incorporating probing data, which is well established in the literature, the probability of our framework correctly identifying the target in the leaf is greater than 90%.
Demonstration
We present a demo of the ensemble trees for 5S rRNA, riboswitch and long non-coding RNA.
Installation
To use the package, the only thing you need to install is Wolfram Mathematica Free Trial.
We have tested our package using Mathematica versions 11.3.0 and 12.0.0 under UNIX and Windows system.
Usage
Download the package to your Notebook directory and load the pacakge with
Get[NotebookDirectory[] <> "RNAStructureIdentifier.wl"]

Quick Start
We provide a quick tutorial (tutorial.nb) to demonstrate functions by examples.
References
If you use our package, you may want to cite the follwing publications:
  1. Thomas J.X. Li and Christian M. Reidys (2020) "On an enhancement of RNA probing data using Information Theory", Algorithms for Molecular Biology, 15: 15.
Contact
We need your feedback! Send your comments, suggestions, and questions to
gauss.backyard@gmail.com
Thomas Li, Autumn 2019
About
Identifying the target secondary structure from RNA structure ensemble
Resources
Readme
Activity
Stars
1 star
Watchers
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3 forks
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RNAStructureIdentifier
A Mathematica package for identifying the target secondary structure from RNA structure ensemble.
Amongst other things, our implementations allow you to:
  • compute the ensemble tree, a hierarchical bi-partition of the ensemble of structures
  • calculate the base pairs having maximum information entropy
  • predict the target structure via recursively querying about whether or not
a base pair of maximum entropy is contained in the target
  • visualize the ensemble tree, together with base pairs of maximum entropy
  • draw a single secondary structure as a diagram
  • present an ensemble of secondary structures as a greyscale diagram
Introduction
The package focuses on how to identify a target from a Boltzmann ensemble of secondary structures. The key idea is to employ an information-theoretic approach to solve the problem, via considering a variant of the Rényi-Ulam game. Our framework is centered around the ensemble tree, a hierarchical bi-partition of the input ensemble, that is constructed by recursively querying about whether or not a base pair of maximum information entropy is contained in the target. These queries are answered via relating local with global chemical probing data, employing the modularity in RNA secondary structures (see References).
In 1, we present that leaves of the tree are comprised of sub-samples exhibiting a distinguished structure with high probability. In particular, for a Boltzmann ensemble incorporating probing data, which is well established in the literature, the probability of our framework correctly identifying the target in the leaf is greater than 90%.
Demonstration
We present a demo of the ensemble trees for 5S rRNA, riboswitch and long non-coding RNA.
Installation
To use the package, the only thing you need to install is Wolfram Mathematica Free Trial.
We have tested our package using Mathematica versions 11.3.0 and 12.0.0 under UNIX and Windows system.
Usage
Download the package to your Notebook directory and load the pacakge with
Get[NotebookDirectory[] <> "RNAStructureIdentifier.wl"]

Quick Start
We provide a quick tutorial (tutorial.nb) to demonstrate functions by examples.
References
If you use our package, you may want to cite the follwing publications:
  1. Thomas J.X. Li and Christian M. Reidys (2020) "On an enhancement of RNA probing data using Information Theory", Algorithms for Molecular Biology, 15: 15.
Contact
We need your feedback! Send your comments, suggestions, and questions to
gauss.backyard@gmail.com
Thomas Li, Autumn 2019
About
Identifying the target secondary structure from RNA structure ensemble
Resources
Readme
Activity
Stars
1 star
Watchers
1 watching
Forks
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Report repository
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RNAStructureIdentifier
A Mathematica package for identifying the target secondary structure from RNA structure ensemble.
Amongst other things, our implementations allow you to:
  • compute the ensemble tree, a hierarchical bi-partition of the ensemble of structures
  • calculate the base pairs having maximum information entropy
  • predict the target structure via recursively querying about whether or not
a base pair of maximum entropy is contained in the target
  • visualize the ensemble tree, together with base pairs of maximum entropy
  • draw a single secondary structure as a diagram
  • present an ensemble of secondary structures as a greyscale diagram
Introduction
The package focuses on how to identify a target from a Boltzmann ensemble of secondary structures. The key idea is to employ an information-theoretic approach to solve the problem, via considering a variant of the Rényi-Ulam game. Our framework is centered around the ensemble tree, a hierarchical bi-partition of the input ensemble, that is constructed by recursively querying about whether or not a base pair of maximum information entropy is contained in the target. These queries are answered via relating local with global chemical probing data, employing the modularity in RNA secondary structures (see References).
In 1, we present that leaves of the tree are comprised of sub-samples exhibiting a distinguished structure with high probability. In particular, for a Boltzmann ensemble incorporating probing data, which is well established in the literature, the probability of our framework correctly identifying the target in the leaf is greater than 90%.
Demonstration
We present a demo of the ensemble trees for 5S rRNA, riboswitch and long non-coding RNA.
Installation
To use the package, the only thing you need to install is Wolfram Mathematica Free Trial.
We have tested our package using Mathematica versions 11.3.0 and 12.0.0 under UNIX and Windows system.
Usage
Download the package to your Notebook directory and load the pacakge with
Get[NotebookDirectory[] <> "RNAStructureIdentifier.wl"]

Quick Start
We provide a quick tutorial (tutorial.nb) to demonstrate functions by examples.
References
If you use our package, you may want to cite the follwing publications:
  1. Thomas J.X. Li and Christian M. Reidys (2020) "On an enhancement of RNA probing data using Information Theory", Algorithms for Molecular Biology, 15: 15.
Contact
We need your feedback! Send your comments, suggestions, and questions to
gauss.backyard@gmail.com
Thomas Li, Autumn 2019
About
Identifying the target secondary structure from RNA structure ensemble
Resources
Readme
Activity
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1 star
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RNAStructureIdentifier
A Mathematica package for identifying the target secondary structure from RNA structure ensemble.
Amongst other things, our implementations allow you to:
  • compute the ensemble tree, a hierarchical bi-partition of the ensemble of structures
  • calculate the base pairs having maximum information entropy
  • predict the target structure via recursively querying about whether or not
a base pair of maximum entropy is contained in the target
  • visualize the ensemble tree, together with base pairs of maximum entropy
  • draw a single secondary structure as a diagram
  • present an ensemble of secondary structures as a greyscale diagram
Introduction
The package focuses on how to identify a target from a Boltzmann ensemble of secondary structures. The key idea is to employ an information-theoretic approach to solve the problem, via considering a variant of the Rényi-Ulam game. Our framework is centered around the ensemble tree, a hierarchical bi-partition of the input ensemble, that is constructed by recursively querying about whether or not a base pair of maximum information entropy is contained in the target. These queries are answered via relating local with global chemical probing data, employing the modularity in RNA secondary structures (see References).
In 1, we present that leaves of the tree are comprised of sub-samples exhibiting a distinguished structure with high probability. In particular, for a Boltzmann ensemble incorporating probing data, which is well established in the literature, the probability of our framework correctly identifying the target in the leaf is greater than 90%.
Demonstration
We present a demo of the ensemble trees for 5S rRNA, riboswitch and long non-coding RNA.
Installation
To use the package, the only thing you need to install is Wolfram Mathematica Free Trial.
We have tested our package using Mathematica versions 11.3.0 and 12.0.0 under UNIX and Windows system.
Usage
Download the package to your Notebook directory and load the pacakge with
Get[NotebookDirectory[] <> "RNAStructureIdentifier.wl"]

Quick Start
We provide a quick tutorial (tutorial.nb) to demonstrate functions by examples.
References
If you use our package, you may want to cite the follwing publications:
  1. Thomas J.X. Li and Christian M. Reidys (2020) "On an enhancement of RNA probing data using Information Theory", Algorithms for Molecular Biology, 15: 15.
Contact
We need your feedback! Send your comments, suggestions, and questions to
gauss.backyard@gmail.com
Thomas Li, Autumn 2019
About
Identifying the target secondary structure from RNA structure ensemble
Resources
Readme
Activity
Stars
1 star
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3 forks
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RNAStructureIdentifier
A Mathematica package for identifying the target secondary structure from RNA structure ensemble.
Amongst other things, our implementations allow you to:
  • compute the ensemble tree, a hierarchical bi-partition of the ensemble of structures
  • calculate the base pairs having maximum information entropy
  • predict the target structure via recursively querying about whether or not
a base pair of maximum entropy is contained in the target
  • visualize the ensemble tree, together with base pairs of maximum entropy
  • draw a single secondary structure as a diagram
  • present an ensemble of secondary structures as a greyscale diagram
Introduction
The package focuses on how to identify a target from a Boltzmann ensemble of secondary structures. The key idea is to employ an information-theoretic approach to solve the problem, via considering a variant of the Rényi-Ulam game. Our framework is centered around the ensemble tree, a hierarchical bi-partition of the input ensemble, that is constructed by recursively querying about whether or not a base pair of maximum information entropy is contained in the target. These queries are answered via relating local with global chemical probing data, employing the modularity in RNA secondary structures (see References).
In 1, we present that leaves of the tree are comprised of sub-samples exhibiting a distinguished structure with high probability. In particular, for a Boltzmann ensemble incorporating probing data, which is well established in the literature, the probability of our framework correctly identifying the target in the leaf is greater than 90%.
Demonstration
We present a demo of the ensemble trees for 5S rRNA, riboswitch and long non-coding RNA.
Installation
To use the package, the only thing you need to install is Wolfram Mathematica Free Trial.
We have tested our package using Mathematica versions 11.3.0 and 12.0.0 under UNIX and Windows system.
Usage
Download the package to your Notebook directory and load the pacakge with
Get[NotebookDirectory[] <> "RNAStructureIdentifier.wl"]

Quick Start
We provide a quick tutorial (tutorial.nb) to demonstrate functions by examples.
References
If you use our package, you may want to cite the follwing publications:
  1. Thomas J.X. Li and Christian M. Reidys (2020) "On an enhancement of RNA probing data using Information Theory", Algorithms for Molecular Biology, 15: 15.
Contact
We need your feedback! Send your comments, suggestions, and questions to
gauss.backyard@gmail.com
Thomas Li, Autumn 2019
About
Identifying the target secondary structure from RNA structure ensemble
Resources
Readme
Activity
Stars
1 star
Watchers
1 watching
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3 forks
Report repository
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Used by
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RNAStructureIdentifier
A Mathematica package for identifying the target secondary structure from RNA structure ensemble.
Amongst other things, our implementations allow you to:
  • compute the ensemble tree, a hierarchical bi-partition of the ensemble of structures
  • calculate the base pairs having maximum information entropy
  • predict the target structure via recursively querying about whether or not
a base pair of maximum entropy is contained in the target
  • visualize the ensemble tree, together with base pairs of maximum entropy
  • draw a single secondary structure as a diagram
  • present an ensemble of secondary structures as a greyscale diagram
Introduction
The package focuses on how to identify a target from a Boltzmann ensemble of secondary structures. The key idea is to employ an information-theoretic approach to solve the problem, via considering a variant of the Rényi-Ulam game. Our framework is centered around the ensemble tree, a hierarchical bi-partition of the input ensemble, that is constructed by recursively querying about whether or not a base pair of maximum information entropy is contained in the target. These queries are answered via relating local with global chemical probing data, employing the modularity in RNA secondary structures (see References).
In 1, we present that leaves of the tree are comprised of sub-samples exhibiting a distinguished structure with high probability. In particular, for a Boltzmann ensemble incorporating probing data, which is well established in the literature, the probability of our framework correctly identifying the target in the leaf is greater than 90%.
Demonstration
We present a demo of the ensemble trees for 5S rRNA, riboswitch and long non-coding RNA.
Installation
To use the package, the only thing you need to install is Wolfram Mathematica Free Trial.
We have tested our package using Mathematica versions 11.3.0 and 12.0.0 under UNIX and Windows system.
Usage
Download the package to your Notebook directory and load the pacakge with
Get[NotebookDirectory[] <> "RNAStructureIdentifier.wl"]

Quick Start
We provide a quick tutorial (tutorial.nb) to demonstrate functions by examples.
References
If you use our package, you may want to cite the follwing publications:
  1. Thomas J.X. Li and Christian M. Reidys (2020) "On an enhancement of RNA probing data using Information Theory", Algorithms for Molecular Biology, 15: 15.
Contact
We need your feedback! Send your comments, suggestions, and questions to
gauss.backyard@gmail.com
Thomas Li, Autumn 2019
About
Identifying the target secondary structure from RNA structure ensemble
Resources
Readme
Activity
Stars
1 star
Watchers
1 watching
Forks
3 forks
Report repository
Releases
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Used by
Contributors
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RNAStructureIdentifier
A Mathematica package for identifying the target secondary structure from RNA structure ensemble.
Amongst other things, our implementations allow you to:
  • compute the ensemble tree, a hierarchical bi-partition of the ensemble of structures
  • calculate the base pairs having maximum information entropy
  • predict the target structure via recursively querying about whether or not
a base pair of maximum entropy is contained in the target
  • visualize the ensemble tree, together with base pairs of maximum entropy
  • draw a single secondary structure as a diagram
  • present an ensemble of secondary structures as a greyscale diagram
Introduction
The package focuses on how to identify a target from a Boltzmann ensemble of secondary structures. The key idea is to employ an information-theoretic approach to solve the problem, via considering a variant of the Rényi-Ulam game. Our framework is centered around the ensemble tree, a hierarchical bi-partition of the input ensemble, that is constructed by recursively querying about whether or not a base pair of maximum information entropy is contained in the target. These queries are answered via relating local with global chemical probing data, employing the modularity in RNA secondary structures (see References).
In 1, we present that leaves of the tree are comprised of sub-samples exhibiting a distinguished structure with high probability. In particular, for a Boltzmann ensemble incorporating probing data, which is well established in the literature, the probability of our framework correctly identifying the target in the leaf is greater than 90%.
Demonstration
We present a demo of the ensemble trees for 5S rRNA, riboswitch and long non-coding RNA.
Installation
To use the package, the only thing you need to install is Wolfram Mathematica Free Trial.
We have tested our package using Mathematica versions 11.3.0 and 12.0.0 under UNIX and Windows system.
Usage
Download the package to your Notebook directory and load the pacakge with
Get[NotebookDirectory[] <> "RNAStructureIdentifier.wl"]

Quick Start
We provide a quick tutorial (tutorial.nb) to demonstrate functions by examples.
References
If you use our package, you may want to cite the follwing publications:
  1. Thomas J.X. Li and Christian M. Reidys (2020) "On an enhancement of RNA probing data using Information Theory", Algorithms for Molecular Biology, 15: 15.
Contact
We need your feedback! Send your comments, suggestions, and questions to
gauss.backyard@gmail.com
Thomas Li, Autumn 2019
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Identifying the target secondary structure from RNA structure ensemble
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