AIMC Topic: Nucleotide Motifs

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DeepMotifSyn: a deep learning approach to synthesize heterodimeric DNA motifs.

Briefings in bioinformatics Jan 17, 2022
The cooperativity of transcription factors (TFs) is a widespread phenomenon in the gene regulation system. However, the interaction patterns between TF binding motifs remain elusive. The recent high-throughput assays, CAP-SELEX, have identified over ...
Protein Binding Transcription Factors Binding Sites Nucleotide Motifs Humans Deep Learning
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DISMIR: Deep learning-based noninvasive cancer detection by integrating DNA sequence and methylation information of individual cell-free DNA reads.

Briefings in bioinformatics Nov 5, 2021
Detecting cancer signals in cell-free DNA (cfDNA) high-throughput sequencing data is emerging as a novel noninvasive cancer detection method. Due to the high cost of sequencing, it is crucial to make robust and precise predictions with low-depth cfDN...
Humans Neoplasms DNA Methylation Cell-Free Nucleic Acids High-Throughput Nucleotide Sequencing Deep Learning Early Detection of Cancer Liquid Biopsy Computational Biology Neoplasm Staging DNA, Neoplasm Sequence Analysis, DNA Organ Specificity Nucleotide Motifs
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Identifying complex motifs in massive omics data with a variable-convolutional layer in deep neural network.

Briefings in bioinformatics Nov 5, 2021
Motif identification is among the most common and essential computational tasks for bioinformatics and genomics. Here we proposed a novel convolutional layer for deep neural network, named variable convolutional (vConv) layer, for effective motif ide...
Genomics Computational Biology Benchmarking High-Throughput Nucleotide Sequencing Software Algorithms Deep Learning Nucleotide Motifs Amino Acid Motifs Humans Neural Networks, Computer
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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...
RNA, Messenger HEK293 Cells Methyltransferases Nucleotide Motifs Adenosine Mouse Embryonic Stem Cells RNA Processing, Post-Transcriptional Sensitivity and Specificity Animals RNA-Seq Mice Humans Machine Learning
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A sequence-based deep learning approach to predict CTCF-mediated chromatin loop.

Briefings in bioinformatics Sep 2, 2021
Three-dimensional (3D) architecture of the chromosomes is of crucial importance for transcription regulation and DNA replication. Various high-throughput chromosome conformation capture-based methods have revealed that CTCF-mediated chromatin loops a...
MCF-7 Cells Datasets as Topic Gene Expression Regulation Genome, Human Humans Neural Networks, Computer Software Chromatin CCCTC-Binding Factor Molecular Conformation K562 Cells Nucleotide Motifs
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A self-attention model for inferring cooperativity between regulatory features.

Nucleic acids research Jul 21, 2021
Deep learning has demonstrated its predictive power in modeling complex biological phenomena such as gene expression. The value of these models hinges not only on their accuracy, but also on the ability to extract biologically relevant information fr...
Humans Arabidopsis Chromatin Immunoprecipitation Sequencing Cell Line Promoter Regions, Genetic Nucleotide Motifs Regulatory Elements, Transcriptional Deep Learning Genomics Transcription Factors
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A survey on deep learning in DNA/RNA motif mining.

Briefings in bioinformatics Jul 20, 2021
DNA/RNA motif mining is the foundation of gene function research. The DNA/RNA motif mining plays an extremely important role in identifying the DNA- or RNA-protein binding site, which helps to understand the mechanism of gene regulation and managemen...
Nucleotide Motifs Neural Networks, Computer Sequence Analysis, RNA Sequence Analysis, DNA DNA RNA
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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...
Binding Sites RNA Polymerase II Nucleotide Motifs RNA Splicing RNA Splice Sites Transcription Elongation, Genetic HEK293 Cells Base Sequence Genome, Human Histones Protein Processing, Post-Translational Models, Biological HeLa Cells Humans Machine Learning Epigenesis, Genetic DNA Methylation
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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...
RNA-Binding Proteins Mutation RNA Base Sequence Protein Binding Humans Mice Computer Simulation Computational Biology Animals Deep Learning Nucleic Acid Conformation Binding Sites Nucleotide Motifs
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Prediction of regulatory motifs from human Chip-sequencing data using a deep learning framework.

Nucleic acids research Sep 5, 2019
The identification of transcription factor binding sites and cis-regulatory motifs is a frontier whereupon the rules governing protein-DNA binding are being revealed. Here, we developed a new method (DEep Sequence and Shape mOtif or DESSO) for cis-re...
K562 Cells Binding Sites Computational Biology Nucleotide Motifs Transcription Factors DNA Humans Gene Expression Regulation Deep Learning Protein Binding
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