AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

RNA Editing

Showing 1 to 10 of 13 articles

Clear Filters

[Application of machine learning in the CRISPR/Cas9 system].

Yi chuan = Hereditas
The third generation of the CRISPR/Cas9-mediated genome fixed-point editing technology has been widely used in the field of gene editing and gene expression regulation. How to improve the on-target efficiency and specificity of this system, as well a...

EPAI-NC: Enhanced prediction of adenosine to inosine RNA editing sites using nucleotide compositions.

Analytical biochemistry
RNA editing process like Adenosine to Intosine (A-to-I) often influences basic functions like splicing stability and most importantly the translation. Thus knowledge about editing sites is of great importance in molecular biology. With the growth of ...

Evaluation of off-targets predicted by sgRNA design tools.

Genomics
The ease of programming CRISPR/Cas9 system for targeting a specific location within the genome has paved way for many clinical and industrial applications. However, its widespread use is still limited owing to its off-target effects. Though this off-...

Deep Neural Networks for Epistatic Sequence Analysis.

Methods in molecular biology (Clifton, N.J.)
We report a step-by-step protocol to use pysster, a TensorFlow-based package for building deep neural networks on a broad range of epistatic sequences such as DNA, RNA, or annotated secondary structure sequences. Pysster provides users comprehensive ...

EditPredict: Prediction of RNA editable sites with convolutional neural network.

Genomics
RNA editing exerts critical impacts on numerous biological processes. While millions of RNA editings have been identified in humans, much more are expected to be discovered. In this work, we constructed Convolutional Neural Network (CNN) models to pr...

RDDSVM: accurate prediction of A-to-I RNA editing sites from sequence using support vector machines.

Functional & integrative genomics
Adenosine to inosine (A-to-I) editing in RNA is involved in various biological processes like gene expression, alternative splicing, and mRNA degradation associated with carcinogenesis and various human diseases. Therefore, accurate identification of...

miTDS: Uncovering miRNA-mRNA interactions with deep learning for functional target prediction.

Methods (San Diego, Calif.)
MicroRNAs (miRNAs) are vital in regulating gene expression through binding to specific target sites on messenger RNAs (mRNAs), a process closely tied to cancer pathogenesis. Identifying miRNA functional targets is essential but challenging, due to in...

PlantC2U: deep learning of cross-species sequence landscapes predicts plastid C-to-U RNA editing in plants.

Journal of experimental botany
In plants, C-to-U RNA editing mainly occurs in plastid and mitochondrial transcripts, which contributes to a complex transcriptional regulatory network. More evidence reveals that RNA editing plays critical roles in plant growth and development. Howe...

Exploring functional conservation in silico: a new machine learning approach to RNA-editing.

Briefings in bioinformatics
Around 50 years ago, molecular biology opened the path to understand changes in forms, adaptations, complexity, or the basis of human diseases through myriads of reports on gene birth, gene duplication, gene expression regulation, and splicing regula...

RNA Editing Signatures Powered by Artificial Intelligence: A New Frontier in Differentiating Schizophrenia, Bipolar, and Schizoaffective Disorders.

International journal of molecular sciences
Mental health disorders are devastating illnesses, often misdiagnosed due to overlapping clinical symptoms. Among these conditions, bipolar disorder, schizophrenia, and schizoaffective disorder are particularly difficult to distinguish, as they share...