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Nucleotides

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Long-term safety and efficacy of rilpivirine in combination with nucleoside/nucleotide reverse transcriptase inhibitors in HIV-1 infected patients: 336-week rollover study of phase 2b and 3 clinical studies.

Antiviral therapy
BACKGROUND: To evaluate the long-term safety and efficacy of rilpivirine (RPV), a non-nucleoside reverse transcriptase inhibitor (NNRTI), in combination with nucleoside/nucleotide reverse transcriptase inhibitors (NRTIs) in human immunodeficiency vir...

Predicting RNA secondary structure by a neural network: what features may be learned?

PeerJ
Deep learning is a class of machine learning techniques capable of creating internal representation of data without explicit preprogramming. Hence, in addition to practical applications, it is of interest to analyze what features of biological data m...

m1A-pred: Prediction of Modified 1-methyladenosine Sites in RNA Sequences through Artificial Intelligence.

Combinatorial chemistry & high throughput screening
BACKGROUND: The process of nucleotides modification or methyl groups addition to nucleotides is known as post-transcriptional modification (PTM). 1-methyladenosine (m1A) is a type of PTM formed by adding a methyl group to the nitrogen at the 1st posi...

Identification of DNA N4-methylcytosine sites based on multi-source features and gradient boosting decision tree.

Analytical biochemistry
N4-methylcytosine (4 mC) is an important and common methylation which widely exists in prokaryotes. It plays a crucial role in correcting DNA replication errors and protecting host DNA against degradation by restrictive enzymes. Hence, the accurate i...

Predicting RNA solvent accessibility from multi-scale context feature via multi-shot neural network.

Analytical biochemistry
Knowledge of RNA solvent accessibility has recently become attractive due to the increasing awareness of its importance for key biological process. Accurately predicting the solvent accessibility of RNA is crucial for understanding its 3D structure a...

Deep Learning Approaches for Detection of Breast Adenocarcinoma Causing Carcinogenic Mutations.

International journal of molecular sciences
Genes are composed of DNA and each gene has a specific sequence. Recombination or replication within the gene base ends in a permanent change in the nucleotide collection in a DNA called mutation and some mutations can lead to cancer. Breast adenocar...

DLm6Am: A Deep-Learning-Based Tool for Identifying N6,2'-O-Dimethyladenosine Sites in RNA Sequences.

International journal of molecular sciences
N6,2'-O-dimethyladenosine (mAm) is a post-transcriptional modification that may be associated with regulatory roles in the control of cellular functions. Therefore, it is crucial to accurately identify transcriptome-wide mAm sites to understand under...

R5hmCFDV: computational identification of RNA 5-hydroxymethylcytosine based on deep feature fusion and deep voting.

Briefings in bioinformatics
RNA 5-hydroxymethylcytosine (5hmC) is a kind of RNA modification, which is related to the life activities of many organisms. Studying its distribution is very important to reveal its biological function. Previously, high-throughput sequencing was use...

MetaRNN: differentiating rare pathogenic and rare benign missense SNVs and InDels using deep learning.

Genome medicine
Multiple computational approaches have been developed to improve our understanding of genetic variants. However, their ability to identify rare pathogenic variants from rare benign ones is still lacking. Using context annotations and deep learning me...

DNA-MP: a generalized DNA modifications predictor for multiple species based on powerful sequence encoding method.

Briefings in bioinformatics
Accurate prediction of deoxyribonucleic acid (DNA) modifications is essential to explore and discern the process of cell differentiation, gene expression and epigenetic regulation. Several computational approaches have been proposed for particular ty...