AIMC Topic: Adenosine

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Metabolomics Analysis in Acute Paraquat Poisoning Patients Based on UPLC-Q-TOF-MS and Machine Learning Approach.

Chemical research in toxicology Mar 11, 2019
Most paraquat (PQ) poisoned patients died from acute multiple organ failure (MOF) such as lung, kidney, and heart. However, the exact mechanism of intoxication is still unclear. In order to find out the initial toxic mechanism of PQ poisoning, a bloo...
Humans Chromatography, High Pressure Liquid Paraquat Adenosine Mass Spectrometry Metabolomics Machine Learning
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EPAI-NC: Enhanced prediction of adenosine to inosine RNA editing sites using nucleotide compositions.

Analytical biochemistry Jan 18, 2019
RNA editing process like Adenosine to Intosine (A-to-I) often influences basic functions like splicing stability and most importantly the translation. Thus knowledge about editing sites is of great importance in molecular biology. With the growth of ...
Machine Learning Inosine ROC Curve Area Under Curve RNA Editing User-Computer Interface RNA Adenosine
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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 ...
Brain Animals Deep Learning Humans Mice Embryonic Stem Cells Computational Biology Sequence Analysis, RNA Liver Neoplasms Carcinoma, Hepatocellular Methylation Adenosine Alternative Splicing Zebrafish RNA
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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 Deep Learning Computational Biology Machine Learning Algorithms
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iMethyl-STTNC: Identification of N-methyladenosine sites by extending the idea of SAAC into Chou's PseAAC to formulate RNA sequences.

Journal of theoretical biology Jul 19, 2018
N- methyladenosine (mA) is a vital post-transcriptional modification, which adds another layer of epigenetic regulation at RNA level. It chemically modifies mRNA that effects protein expression. RNA sequence contains many genetic code motifs (GAC). A...
Adenosine Neural Networks, Computer Sequence Analysis, RNA RNA Base Sequence Support Vector Machine
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Kinematics optimization and static analysis of a modular continuum robot used for minimally invasive surgery.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine Dec 11, 2017
For the outstanding compliance and dexterity of continuum robot, it is increasingly used in minimally invasive surgery. The wide workspace, high dexterity and strong payload capacity are essential to the continuum robot. In this article, we investiga...
Equipment Design Motion Robotics Biomechanical Phenomena Adenosine Minimally Invasive Surgical Procedures
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Identifying N-methyladenosine sites using multi-interval nucleotide pair position specificity and support vector machine.

Scientific reports Apr 25, 2017
N6-methyladenosine (mA) refers to methylation of the adenosine nucleotide acid at the nitrogen-6 position. It plays an important role in a series of biological processes, such as splicing events, mRNA exporting, nascent mRNA synthesis, nuclear transl...
RNA, Messenger Support Vector Machine Datasets as Topic Saccharomyces cerevisiae Nucleotides Humans Algorithms Computational Biology Adenosine Arabidopsis
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Detecting N-methyladenosine sites from RNA transcriptomes using ensemble Support Vector Machines.

Scientific reports Jan 12, 2017
As one of the most abundant RNA post-transcriptional modifications, N-methyladenosine (mA) involves in a broad spectrum of biological and physiological processes ranging from mRNA splicing and stability to cell differentiation and reprogramming. Howe...
Support Vector Machine RNA Saccharomyces cerevisiae Adenosine Transcriptome RNA Processing, Post-Transcriptional Computational Biology
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TargetM6A: Identifying N-Methyladenosine Sites From RNA Sequences via Position-Specific Nucleotide Propensities and a Support Vector Machine.

IEEE transactions on nanobioscience Aug 10, 2016
As one of the most ubiquitous post-transcriptional modifications of RNA, N-methyladenosine ( [Formula: see text]) plays an essential role in many vital biological processes. The identification of [Formula: see text] sites in RNAs is significantly imp...
RNA Saccharomyces cerevisiae Adenosine Sequence Analysis, RNA Support Vector Machine Computational Biology
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Dynamic regulation of RNA editing in human brain development and disease.

Nature neuroscience Jun 27, 2016
RNA editing is increasingly recognized as a molecular mechanism regulating RNA activity and recoding proteins. Here we surveyed the global landscape of RNA editing in human brain tissues and identified three unique patterns of A-to-I RNA editing rate...
Adenosine Adenosine Deaminase RNA Editing RNA-Binding Proteins Humans Inosine Gene Ontology Brain Diagnosis
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