AIMC Topic: Base Sequence

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Prediction of RBP binding sites on circRNAs using an LSTM-based deep sequence learning architecture.

Briefings in bioinformatics Nov 5, 2021
Circular RNAs (circRNAs) are widely expressed in highly diverged eukaryotes. Although circRNAs have been known for many years, their function remains unclear. Interaction with RNA-binding protein (RBP) to influence post-transcriptional regulation is ...
Algorithms Reproducibility of Results Deep Learning Databases, Genetic Base Sequence Binding Sites RNA, Circular ROC Curve Computational Biology RNA-Binding Proteins
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Explainability in transformer models for functional genomics.

Briefings in bioinformatics Sep 2, 2021
The effectiveness of deep learning methods can be largely attributed to the automated extraction of relevant features from raw data. In the field of functional genomics, this generally concerns the automatic selection of relevant nucleotide motifs fr...
Genomics DNA, Bacterial Transcription Factors Escherichia coli Deep Learning Genome, Bacterial Transcription Initiation Site Base Sequence Promoter Regions, Genetic Binding Sites
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Feature extraction approaches for biological sequences: a comparative study of mathematical features.

Briefings in bioinformatics Sep 2, 2021
As consequence of the various genomic sequencing projects, an increasing volume of biological sequence data is being produced. Although machine learning algorithms have been successfully applied to a large number of genomic sequence-related problems,...
Humans Deep Learning Open Reading Frames RNA, Long Noncoding RNA, Circular Base Sequence Entropy Fourier Analysis Computational Biology RNA, Messenger Models, Theoretical
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Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles.

Briefings in bioinformatics Sep 2, 2021
The exploration of three-dimensional chromatin interaction and organization provides insight into mechanisms underlying gene regulation, cell differentiation and disease development. Advances in chromosome conformation capture technologies, such as h...
Chromatin Assembly and Disassembly Base Sequence Humans Genome, Human Unsupervised Machine Learning Chromatin Epigenesis, Genetic Supervised Machine Learning Sequence Analysis, DNA
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iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization.

Nucleic acids research Jun 4, 2021
Sequence-based analysis and prediction are fundamental bioinformatic tasks that facilitate understanding of the sequence(-structure)-function paradigm for DNAs, RNAs and proteins. Rapid accumulation of sequences requires equally pervasive development...
Base Sequence Sequence Analysis Humans Machine Learning Computational Biology Amino Acid Sequence Software Animals
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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...
Rosaceae Adenosine Genome, Plant DNA, Plant Arabidopsis Oryza Base Sequence Species Specificity Machine Learning Algorithms Computational Biology Support Vector Machine Internet Epigenesis, Genetic Models, Genetic
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A machine learning-based framework for modeling transcription elongation.

Proceedings of the National Academy of Sciences of the United States of America Feb 9, 2021
RNA polymerase II (Pol II) generally pauses at certain positions along gene bodies, thereby interrupting the transcription elongation process, which is often coupled with various important biological functions, such as precursor mRNA splicing and gen...
DNA Methylation Nucleotide Motifs Humans Histones Protein Processing, Post-Translational RNA Splicing Machine Learning Binding Sites Models, Biological Epigenesis, Genetic RNA Splice Sites RNA Polymerase II Base Sequence Transcription Elongation, Genetic HeLa Cells Genome, Human HEK293 Cells
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Towards peptide-based tunable multistate memristive materials.

Physical chemistry chemical physics : PCCP Jan 28, 2021
Development of new memristive hardware is a technological requirement towards widespread neuromorphic computing. Molecular spintronics seems to be a fertile field for the design and preparation of this hardware. Within molecular spintronics, recent r...
Metalloproteins Amino Acid Sequence Base Sequence Lanthanoid Series Elements Neural Networks, Computer Peptides
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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 ...
Deep Learning ROC Curve Models, Genetic RNA Humans Sequence Analysis Software Datasets as Topic RNA Editing Base Sequence Epistasis, Genetic
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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...
Computational Biology Nucleotide Motifs Deep Learning Humans RNA-Binding Proteins Nucleic Acid Conformation RNA Computer Simulation Protein Binding Mutation Binding Sites Base Sequence Animals Mice
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