AIMC Topic: Methylation

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DeepPRMS: advanced deep learning model to predict protein arginine methylation sites.

Briefings in functional genomics
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...

m6ACali: machine learning-powered calibration for accurate m6A detection in MeRIP-Seq.

Nucleic acids research
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...

H2Opred: a robust and efficient hybrid deep learning model for predicting 2'-O-methylation sites in human RNA.

Briefings in bioinformatics
2'-O-methylation (2OM) is the most common post-transcriptional modification of RNA. It plays a crucial role in RNA splicing, RNA stability and innate immunity. Despite advances in high-throughput detection, the chemical stability of 2OM makes it diff...

DeepGpgs: a novel deep learning framework for predicting arginine methylation sites combined with Gaussian prior and gated self-attention mechanism.

Briefings in bioinformatics
Protein arginine methylation is an important posttranslational modification (PTM) associated with protein functional diversity and pathological conditions including cancer. Identification of methylation binding sites facilitates a better understandin...

Geographic encoding of transcripts enabled high-accuracy and isoform-aware deep learning of RNA methylation.

Nucleic acids research
As the most pervasive epigenetic mark present on mRNA and lncRNA, N6-methyladenosine (m6A) RNA methylation regulates all stages of RNA life in various biological processes and disease mechanisms. Computational methods for deciphering RNA modification...

NmRF: identification of multispecies RNA 2'-O-methylation modification sites from RNA sequences.

Briefings in bioinformatics
2'-O-methylation (Nm) is a post-transcriptional modification of RNA that is catalyzed by 2'-O-methyltransferase and involves replacing the H on the 2'-hydroxyl group with a methyl group. The 2'-O-methylation modification site is detected in a variety...

DeepRMethylSite: a deep learning based approach for prediction of arginine methylation sites in proteins.

Molecular omics
Methylation, which is one of the most prominent post-translational modifications on proteins, regulates many important cellular functions. Though several model-based methylation site predictors have been reported, all existing methods employ machine ...

Identification of 2'-O-methylation Site by Investigating Multi-feature Extracting Techniques.

Combinatorial chemistry & high throughput screening
BACKGROUND: RNA methylation is a reversible post-transcriptional modification involving numerous biological processes. Ribose 2'-O-methylation is part of RNA methylation. It has shown that ribose 2'-O-methylation plays an important role in immune rec...

[Methylation level of MEG3 and semen quality].

Zhonghua nan ke xue = National journal of andrology
OBJECTIVE: To study the relationship between semen quality and the methylation level of maternally expressed gene 3 (MEG3) in sperm.

WHISTLE: a high-accuracy map of the human N6-methyladenosine (m6A) epitranscriptome predicted using a machine learning approach.

Nucleic acids research
N 6-methyladenosine (m6A) is the most prevalent post-transcriptional modification in eukaryotes, and plays a pivotal role in various biological processes, such as splicing, RNA degradation and RNA-protein interaction. We report here a prediction fram...