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RNA

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Epigenetics Analysis and Integrated Analysis of Multiomics Data, Including Epigenetic Data, Using Artificial Intelligence in the Era of Precision Medicine.

Biomolecules
To clarify the mechanisms of diseases, such as cancer, studies analyzing genetic mutations have been actively conducted for a long time, and a large number of achievements have already been reported. Indeed, genomic medicine is considered the core di...

Predicting RNA secondary structure via adaptive deep recurrent neural networks with energy-based filter.

BMC bioinformatics
BACKGROUND: RNA secondary structure prediction is an important issue in structural bioinformatics, and RNA pseudoknotted secondary structure prediction represents an NP-hard problem. Recently, many different machine-learning methods, Markov models, a...

RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning.

Nature communications
The majority of our human genome transcribes into noncoding RNAs with unknown structures and functions. Obtaining functional clues for noncoding RNAs requires accurate base-pairing or secondary-structure prediction. However, the performance of such p...

Constructive Prediction of Potential RNA Aptamers for a Protein Target.

IEEE/ACM transactions on computational biology and bioinformatics
Aptamers are short single-stranded nucleic acids that bind to target molecules with high affinity and selectivity. Aptamers are generally identified in vitro by performing SELEX (systematic evolution of ligands by exponential enrichment). Complementi...

A deep learning framework to predict binding preference of RNA constituents on protein surface.

Nature communications
Protein-RNA interaction plays important roles in post-transcriptional regulation. However, the task of predicting these interactions given a protein structure is difficult. Here we show that, by leveraging a deep learning model NucleicNet, attributes...

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal.

Journal of visualized experiments : JoVE
Differential gene expression analysis is an important technique for understanding disease states. The machine learning algorithm CorEx has shown utility in analyzing differential expression of groups of genes in tumor RNA-seq in a way that may be hel...

Capsule Network for Predicting RNA-Protein Binding Preferences Using Hybrid Feature.

IEEE/ACM transactions on computational biology and bioinformatics
RNA-Protein binding is involved in many different biological processes. With the progress of technology, more and more data are available for research. Based on these data, many prediction methods have been proposed to predict RNA-Protein binding pre...

econvRBP: Improved ensemble convolutional neural networks for RNA binding protein prediction directly from sequence.

Methods (San Diego, Calif.)
RNA binding proteins (RBPs) determine RNA process from synthesis to decay, which play a key role in RNA transport, translation and degradation. Therefore, exploring RBPs' function from the amino acid sequence using computational methods has become on...

EternaBrain: Automated RNA design through move sets and strategies from an Internet-scale RNA videogame.

PLoS computational biology
Emerging RNA-based approaches to disease detection and gene therapy require RNA sequences that fold into specific base-pairing patterns, but computational algorithms generally remain inadequate for these secondary structure design tasks. The Eterna p...