AIMC Topic: Riboswitch

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Identification of potential riboswitch elements in Homo sapiens mRNA 5'UTR sequences using positive-unlabeled machine learning.

PloS one Apr 24, 2025
Riboswitches are a class of noncoding RNA structures that interact with target ligands to cause a conformational change that can then execute some regulatory purpose within the cell. Riboswitches are ubiquitous and well characterized in bacteria and ...
Humans Machine Learning RNA, Messenger 5' Untranslated Regions Nucleic Acid Conformation Riboswitch Ligands Base Sequence
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RNAmigos2: accelerated structure-based RNA virtual screening with deep graph learning.

Nature communications Mar 21, 2025
RNAs are a vast reservoir of untapped drug targets. Structure-based virtual screening (VS) identifies candidate molecules by leveraging binding site information, traditionally using molecular docking simulations. However, docking struggles to scale w...
Nucleic Acid Conformation Binding Sites Deep Learning Riboswitch RNA Molecular Docking Simulation
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Sequence-to-function deep learning frameworks for engineered riboregulators.

Nature communications Oct 7, 2020
While synthetic biology has revolutionized our approaches to medicine, agriculture, and energy, the design of completely novel biological circuit components beyond naturally-derived templates remains challenging due to poorly understood design rules....
Deep Learning Models, Genetic Natural Language Processing Datasets as Topic Structure-Activity Relationship Humans Computer Simulation Mutagenesis Biotechnology Riboswitch Genetic Engineering Genome, Human Genome, Viral Synthetic Biology Base Sequence
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A deep learning approach to programmable RNA switches.

Nature communications Oct 7, 2020
Engineered RNA elements are programmable tools capable of detecting small molecules, proteins, and nucleic acids. Predicting the behavior of these synthetic biology components remains a challenge, a situation that could be addressed through enhanced ...
Synthetic Biology Genome, Viral Genetic Engineering Riboswitch Thermodynamics Kinetics Datasets as Topic Deep Learning Transcription Factors Humans
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A novel riboswitch classification based on imbalanced sequences achieved by machine learning.

PLoS computational biology Jul 20, 2020
Riboswitch, a part of regulatory mRNA (50-250nt in length), has two main classes: aptamer and expression platform. One of the main challenges raised during the classification of riboswitch is imbalanced data. That is a circumstance in which the recor...
Sequence Analysis, RNA Riboswitch Software Algorithms Machine Learning Computational Biology
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Tuning the Performance of Synthetic Riboswitches using Machine Learning.

ACS synthetic biology Jan 8, 2019
Riboswitch development for clinical, technological, and synthetic biology applications constantly seeks to optimize regulatory behavior. Here, we present a machine learning approach to improve the regulation of a tetracycline (tc)-dependent riboswitc...
Nucleic Acid Conformation Tetracycline Computational Biology Synthetic Biology Riboswitch Machine Learning Aptamers, Nucleotide
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Generative Modeling of RNA Sequence Families with Restricted Boltzmann Machines.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2025
In this chapter, we discuss the potential application of Restricted Boltzmann machines (RBM) to model sequence families of structured RNA molecules. RBMs are a simple two-layer machine learning model able to capture intricate sequence dependencies in...
Nucleic Acid Conformation Riboswitch Models, Molecular RNA Machine Learning Algorithms Computational Biology Software
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CoCoNet-boosting RNA contact prediction by convolutional neural networks.

Nucleic acids research Dec 16, 2021
Co-evolutionary models such as direct coupling analysis (DCA) in combination with machine learning (ML) techniques based on deep neural networks are able to predict accurate protein contact or distance maps. Such information can be used as constraint...
Models, Molecular RNA Neural Networks, Computer Algorithms Nucleic Acid Conformation Riboswitch
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Application of supervised machine learning algorithms for the classification of regulatory RNA riboswitches.

Briefings in functional genomics Mar 1, 2017
Riboswitches, the small structured RNA elements, were discovered about a decade ago. It has been the subject of intense interest to identify riboswitches, understand their mechanisms of action and use them in genetic engineering. The accumulation of ...
Supervised Machine Learning Models, Theoretical Markov Chains Bayes Theorem Riboswitch Humans Algorithms
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