AIMC Topic: Adenosine
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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...
Deep and accurate detection of m6A RNA modifications using miCLIP2 and m6Aboost machine learning.
Nucleic acids research
Sep 20, 2021
N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic mRNAs and influences many aspects of RNA processing. miCLIP (m6A individual-nucleotide resolution UV crosslinking and immunoprecipitation) is an antibody-based appr...
Meta-i6mA: an interspecies predictor for identifying DNA N6-methyladenine sites of plant genomes by exploiting informative features in an integrative machine-learning framework.
Briefings in bioinformatics
May 20, 2021
DNA N6-methyladenine (6mA) represents important epigenetic modifications, which are responsible for various cellular processes. The accurate identification of 6mA sites is one of the challenging tasks in genome analysis, which leads to an understandi...
Modeling multi-species RNA modification through multi-task curriculum learning.
Nucleic acids research
Apr 19, 2021
N6-methyladenosine (m6A) is the most pervasive modification in eukaryotic mRNAs. Numerous biological processes are regulated by this critical post-transcriptional mark, such as gene expression, RNA stability, RNA structure and translation. Recently, ...
m6A-Atlas: a comprehensive knowledgebase for unraveling the N6-methyladenosine (m6A) epitranscriptome.
Nucleic acids research
Jan 8, 2021
N 6-Methyladenosine (m6A) is the most prevalent RNA modification on mRNAs and lncRNAs. It plays a pivotal role during various biological processes and disease pathogenesis. We present here a comprehensive knowledgebase, m6A-Atlas, for unraveling the ...
DeepMRMP: A new predictor for multiple types of RNA modification sites using deep learning.
Mathematical biosciences and engineering : MBE
Jul 4, 2019
RNA modification plays an indispensable role in the regulation of organisms. RNA modification site prediction offers an insight into diverse cellular processing. Regarding different types of RNA modification site prediction, it is difficult to tell t...
WHISTLE: a high-accuracy map of the human N6-methyladenosine (m6A) epitranscriptome predicted using a machine learning approach.
Nucleic acids research
Apr 23, 2019
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...
[Determination of Nucleosides and Nucleobases in Natural, Cultured and Tissue Culture Anoectochilus roxburghii Using LC-MS].
Zhong yao cai = Zhongyaocai = Journal of Chinese medicinal materials
Nov 1, 2015
OBJECTIVE: To establish a method for simultaneous determination of nucleosides and nucleobases in natural, cultured and tissue culture Anoectochilus roxburghii by high performance liquid chromatography-electrospray ionization/ion trap mass spectromet...
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