AIMC Topic: Methylation

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iMethyl-Deep: N6 Methyladenosine Identification of Yeast Genome with Automatic Feature Extraction Technique by Using Deep Learning Algorithm.

Genes May 9, 2020
One of the most common and well studied post-transcription modifications in RNAs is N6-methyladenosine (m6A) which has been involved with a wide range of biological processes. Over the past decades, N6-methyladenosine produced some positive consequen...
RNA Processing, Post-Transcriptional RNA, Fungal Computational Biology Datasets as Topic Methylation Saccharomyces cerevisiae Adenosine Genome, Fungal Algorithms Deep Learning ROC Curve
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DeepM6ASeq: prediction and characterization of m6A-containing sequences using deep learning.

BMC bioinformatics Dec 31, 2018
BACKGROUND: N6-methyladensine (m6A) is a common and abundant RNA methylation modification found in various species. As a type of post-transcriptional methylation, m6A plays an important role in diverse RNA activities such as alternative splicing, an ...
Deep Learning Liver Neoplasms Carcinoma, Hepatocellular Mice Computational Biology Sequence Analysis, RNA Humans Brain Animals Adenosine Alternative Splicing Embryonic Stem Cells Zebrafish RNA Methylation
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iRNA-PseKNC(2methyl): Identify RNA 2'-O-methylation sites by convolution neural network and Chou's pseudo components.

Journal of theoretical biology Dec 24, 2018
The 2'-O-methylation transferase is involved in the process of 2'-O-methylation. In catalytic processes, the 2-hydroxy group of the ribose moiety of a nucleotide accept a methyl group. This methylation process is a post-transcriptional modification, ...
RNA Methylation Binding Sites Humans Neural Networks, Computer Machine Learning Algorithms Deep Learning Computational Biology
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BERMP: a cross-species classifier for predicting mA sites by integrating a deep learning algorithm and a random forest approach.

International journal of biological sciences Sep 7, 2018
N-methyladenosine (mA) is a prevalent RNA methylation modification involved in several biological processes. Hundreds or thousands of mA sites identified from different species using high-throughput experiments provides a rich resource to construct ...
RNA Methylation Adenosine Algorithms Deep Learning Computational Biology Machine Learning
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iRNA-2OM: A Sequence-Based Predictor for Identifying 2'-O-Methylation Sites in Homo sapiens.

Journal of computational biology : a journal of computational molecular cell biology Aug 16, 2018
2'-O-methylation plays an important biological role in gene expression. Owing to the explosive increase in genomic sequencing data, it is necessary to develop a method for quickly and efficiently identifying whether a sequence contains the 2'-O-methy...
Methylation Genome, Human RNA Interference Computational Biology Support Vector Machine RNA Humans Software Algorithms
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Aptamer facilitated purification of functional proteins.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences Dec 16, 2017
DNA aptamers are attractive capture probes for affinity chromatography since, in contrast to antibodies, they can be chemically synthesized and, in contrast to tag-specific capture probes (such as Nickel-NTA or Glutathione), they can be used for puri...
Methylation Electrophoresis, Polyacrylamide Gel AlkB Enzymes Immobilized Nucleic Acids MutS DNA Mismatch-Binding Protein Recombinant Proteins Chromatography, Affinity Escherichia coli Aptamers, Nucleotide Electrophoresis, Capillary Protein Binding
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m6A-SPP: Identification of RNA N6-methyladenosine modification sites through multi-source biological features and a hybrid deep learning architecture.

International journal of biological macromolecules Jun 1, 2025
The N6-methyladenosine(m6A) modification plays crucial regulatory roles in various biological processes including gene expression regulation, RNA stability, splicing, and translation. Accurate prediction of m6A modification sites is essential for und...
Humans Neural Networks, Computer HeLa Cells Methylation HEK293 Cells Adenosine Deep Learning Computational Biology RNA
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Nmix: a hybrid deep learning model for precise prediction of 2'-O-methylation sites based on multi-feature fusion and ensemble learning.

Briefings in bioinformatics Sep 23, 2024
RNA 2'-O-methylation (Nm) is a crucial post-transcriptional modification with significant biological implications. However, experimental identification of Nm sites is challenging and resource-intensive. While multiple computational tools have been de...
RNA Processing, Post-Transcriptional Bayes Theorem RNA Methylation Humans Neural Networks, Computer Software Deep Learning Computational Biology
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DeepPRMS: advanced deep learning model to predict protein arginine methylation sites.

Briefings in functional genomics Jul 19, 2024
Protein methylation is a form of post-translational modifications of protein, which is crucial for various cellular processes, including transcription activity and DNA repair. Correctly predicting protein methylation sites is fundamental for research...
Humans Neural Networks, Computer Arginine Protein Processing, Post-Translational Proteins Methylation Algorithms Deep Learning Computational Biology
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m6ACali: machine learning-powered calibration for accurate m6A detection in MeRIP-Seq.

Nucleic acids research May 22, 2024
We present m6ACali, a novel machine-learning framework aimed at enhancing the accuracy of N6-methyladenosine (m6A) epitranscriptome profiling by reducing the impact of non-specific antibody enrichment in MeRIP-Seq. The calibration model serves as a g...
Machine Learning Transcriptome RNA, Messenger Humans Adenosine Sequence Analysis, RNA Methylation Calibration
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