AIMC Topic: RNA

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Cardiovascular RNA markers and artificial intelligence may improve COVID-19 outcome: a position paper from the EU-CardioRNA COST Action CA17129.

Cardiovascular research Jul 7, 2021
The coronavirus disease 2019 (COVID-19) pandemic has been as unprecedented as unexpected, affecting more than 105 million people worldwide as of 8 February 2020 and causing more than 2.3 million deaths according to the World Health Organization (WHO)...
Humans Artificial Intelligence COVID-19 Quality of Life RNA Cardiovascular System Biomarkers SARS-CoV-2 Cardiovascular Diseases
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Research on automatic preprocessing equipment of salivary analyte for PCR inspection of coronavirus.

Science progress Jul 1, 2021
Polymerase chain reaction (PCR) inspection of salivary analyte is performed by pretreatment, RNA extraction setup, RNA extraction, PCR setup, and the PCR process. However, the pretreatment process is conducted manually, and it is a bottleneck to the ...
Polymerase Chain Reaction Robotics Coronavirus Saliva RNA
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GraphBind: protein structural context embedded rules learned by hierarchical graph neural networks for recognizing nucleic-acid-binding residues.

Nucleic acids research May 21, 2021
Knowledge of the interactions between proteins and nucleic acids is the basis of understanding various biological activities and designing new drugs. How to accurately identify the nucleic-acid-binding residues remains a challenging task. In this pap...
Neural Networks, Computer RNA Protein Conformation Binding Sites RNA-Binding Proteins DNA DNA-Binding Proteins Software Protein Binding
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Interpretation of deep learning in genomics and epigenomics.

Briefings in bioinformatics May 20, 2021
Machine learning methods have been widely applied to big data analysis in genomics and epigenomics research. Although accuracy and efficiency are common goals in many modeling tasks, model interpretability is especially important to these studies tow...
Protein Binding Genomics Computational Biology Neural Networks, Computer Deep Learning RNA Chromatin Epigenesis, Genetic DNA Gene Expression
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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, ...
Sequence Analysis, RNA Databases, Genetic RNA Datasets as Topic Gene Expression Regulation Adenosine Animals Transcriptome RNA-Binding Proteins Machine Learning Software Humans
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Prediction of bio-sequence modifications and the associations with diseases.

Briefings in functional genomics Mar 2, 2021
Modifications of protein, RNA and DNA play an important role in many biological processes and are related to some diseases. Therefore, accurate identification and comprehensive understanding of protein, RNA and DNA modification sites can promote rese...
Machine Learning Computational Biology Proteins DNA RNA
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Deep Neural Networks for Epistatic Sequence Analysis.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2021
We report a step-by-step protocol to use pysster, a TensorFlow-based package for building deep neural networks on a broad range of epistatic sequences such as DNA, RNA, or annotated secondary structure sequences. Pysster provides users comprehensive ...
Humans Software Deep Learning ROC Curve Models, Genetic RNA Datasets as Topic Epistasis, Genetic Base Sequence Sequence Analysis RNA Editing
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DeepCLIP: predicting the effect of mutations on protein-RNA binding with deep learning.

Nucleic acids research Jul 27, 2020
Nucleotide variants can cause functional changes by altering protein-RNA binding in various ways that are not easy to predict. This can affect processes such as splicing, nuclear shuttling, and stability of the transcript. Therefore, correct modeling...
Humans Nucleic Acid Conformation Computer Simulation Binding Sites Computational Biology RNA Animals Nucleotide Motifs Deep Learning Base Sequence RNA-Binding Proteins Protein Binding Mutation Mice
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Graph neural representational learning of RNA secondary structures for predicting RNA-protein interactions.

Bioinformatics (Oxford, England) Jul 1, 2020
MOTIVATION: RNA-protein interactions are key effectors of post-transcriptional regulation. Significant experimental and bioinformatics efforts have been expended on characterizing protein binding mechanisms on the molecular level, and on highlighting...
RNA Neural Networks, Computer Protein Structure, Secondary Software Protein Binding
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iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data.

Briefings in bioinformatics May 21, 2020
With the explosive growth of biological sequences generated in the post-genomic era, one of the most challenging problems in bioinformatics and computational biology is to computationally characterize sequences, structures and functions in an efficie...
RNA Proteins Machine Learning DNA Sequence Analysis Algorithms Internet
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