AIMC Topic: Nucleic Acid Conformation

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Recent Advances in Machine Learning Based Prediction of RNA-protein Interactions.

Protein and peptide letters Jan 1, 2019
The interactions between RNAs and proteins play critical roles in many biological processes. Therefore, characterizing these interactions becomes critical for mechanistic, biomedical, and clinical studies. Many experimental methods can be used to det...
Machine Learning Hydrophobic and Hydrophilic Interactions Algorithms Nucleic Acid Conformation Computational Biology Molecular Dynamics Simulation RNA-Binding Proteins RNA
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[An RNA Scoring Function for Tertiary Structure Prediction Based on Multi-layer Neural Networks].

Molekuliarnaia biologiia Jan 1, 2019
A good scoring function is necessary for ab inito prediction of RNA tertiary structures. In this study, we explored the power of a machine learning based approach as a scoring function. Compared with the traditional scoring functions, the present app...
RNA Nucleic Acid Conformation Neural Networks, Computer Molecular Dynamics Simulation
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Convolutional neural networks for classification of alignments of non-coding RNA sequences.

Bioinformatics (Oxford, England) Jul 1, 2018
MOTIVATION: The convolutional neural network (CNN) has been applied to the classification problem of DNA sequences, with the additional purpose of motif discovery. The training of CNNs with distributed representations of four nucleotides has successf...
Computational Biology Adenocarcinoma Male Protein Binding Prostatic Neoplasms Nucleic Acid Conformation Cluster Analysis MicroRNAs Humans Neural Networks, Computer Software RNA, Untranslated RNA, Transfer RNA, Small Nucleolar Binding Sites
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Genome-wide pre-miRNA discovery from few labeled examples.

Bioinformatics (Oxford, England) Feb 15, 2018
MOTIVATION: Although many machine learning techniques have been proposed for distinguishing miRNA hairpins from other stem-loop sequences, most of the current methods use supervised learning, which requires a very good set of positive and negative ex...
Anopheles Genome Arabidopsis Eukaryota MicroRNAs Supervised Machine Learning Animals Sequence Analysis, RNA Nucleic Acid Conformation Sequence Analysis, DNA Caenorhabditis elegans Genomics Computational Biology
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DNA sequence+shape kernel enables alignment-free modeling of transcription factor binding.

Bioinformatics (Oxford, England) Oct 1, 2017
MOTIVATION: Transcription factors (TFs) bind to specific DNA sequence motifs. Several lines of evidence suggest that TF-DNA binding is mediated in part by properties of the local DNA shape: the width of the minor groove, the relative orientations of ...
Protein Array Analysis Software Binding Sites Transcription Factors Nucleotide Motifs DNA-Binding Proteins Support Vector Machine Protein Binding Nucleic Acid Conformation Sequence Analysis, DNA Genomics DNA
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Identifying RNA 5-methylcytosine sites via pseudo nucleotide compositions.

Molecular bioSystems Oct 18, 2016
RNA 5-methylcytosine (mC) plays an important role in numerous biological processes. Accurate identification of the mC site is helpful for a better understanding of its biological functions. However, the drawbacks of the experimental methods available...
5-Methylcytosine Methylation Nucleic Acid Conformation Computational Biology Algorithms Support Vector Machine Epigenomics Reproducibility of Results RNA Humans
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