AIMC Topic: Adenine

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i6mA-VC: A Multi-Classifier Voting Method for the Computational Identification of DNA N6-methyladenine Sites.

Interdisciplinary sciences, computational life sciences
DNA N6-methyladenine (6 mA), as an essential component of epigenetic modification, cannot be neglected in genetic regulation mechanism. The efficient and accurate prediction of 6 mA sites is beneficial to the development of biological genetics. Bioch...

Deep6mA: A deep learning framework for exploring similar patterns in DNA N6-methyladenine sites across different species.

PLoS computational biology
N6-methyladenine (6mA) is an important DNA modification form associated with a wide range of biological processes. Identifying accurately 6mA sites on a genomic scale is crucial for under-standing of 6mA's biological functions. However, the existing ...

Using Chou's 5-steps rule to identify N-methyladenine sites by ensemble learning combined with multiple feature extraction methods.

Journal of biomolecular structure & dynamics
-methyladenine (m6A), a type of modification mostly affecting the downstream biological functions and determining the levels of gene expression, is mediated by the methylation of adenine in nucleic acids. It is also a key factor for influencing biolo...

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...

Using artificial neural network and multivariate calibration methods for simultaneous spectrophotometric analysis of Emtricitabine and Tenofovir alafenamide fumarate in pharmaceutical formulation of HIV drug.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Spectrophotometric analysis method based on artificial neural network (ANN), partial least squares regression (PLS) and principal component regression (PCR) models was proposed for the simultaneous determination of Emtricitabine (ETB) and Tenofovir a...

Tenofovir alafenamide versus tenofovir disoproxil fumarate for the treatment of patients with HBeAg-negative chronic hepatitis B virus infection: a randomised, double-blind, phase 3, non-inferiority trial.

The lancet. Gastroenterology & hepatology
BACKGROUND: The novel prodrug tenofovir alafenamide delivers the nucleotide reverse transcriptase inhibitor tenofovir to target cells more efficiently at a lower dose than tenofovir disoproxil fumarate, thereby reducing systemic exposure. We compared...

Tenofovir alafenamide versus tenofovir disoproxil fumarate for the treatment of HBeAg-positive chronic hepatitis B virus infection: a randomised, double-blind, phase 3, non-inferiority trial.

The lancet. Gastroenterology & hepatology
BACKGROUND: Tenofovir alafenamide is a novel prodrug formulated to deliver the active metabolite to target cells more efficiently than tenofovir disoproxil fumarate at a lower dose, thereby reducing systemic exposure. In patients with HIV, tenofovir ...

DNA methyltransferase detection based on digestion triggering the combination of poly adenine DNA with gold nanoparticles.

Biosensors & bioelectronics
DNA methyltransferase (MTase) has received a large amount of attention due to its catalyzation of DNA methylation in both eukaryotes and prokaryotes, which has a close relationship to cancer and bacterial diseases. Herein, a novel electrochemical str...

Predicting the risk of ibrutinib in combination with R-ICE in patients with relapsed or refractory DLBCL using explainable machine learning algorithms.

Clinical and experimental medicine
Relapsed or refractory diffuse large B-cell lymphoma (DLBCL) poses significant therapeutic challenges due to heterogeneous patient outcomes. This study aimed to evaluate the efficacy of the ibrutinib plus R-ICE regimen and to leverage explainable mac...

Predicting adenine base editing efficiencies in different cellular contexts by deep learning.

Genome biology
BACKGROUND: Adenine base editors (ABEs) enable the conversion of A•T to G•C base pairs. Since the sequence of the target locus influences base editing efficiency, efforts have been made to develop computational models that can predict base editing ou...