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Nucleotide Motifs

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Machine Learning Techniques for Classifying the Mutagenic Origins of Point Mutations.

Genetics May 1, 2020
There is increasing interest in developing diagnostics that discriminate individual mutagenic mechanisms in a range of applications that include identifying population-specific mutagenesis and resolving distinct mutation signatures in cancer samples....
Nucleotide Motifs Point Mutation Ethylnitrosourea Machine Learning Animals Mice Sequence Analysis, DNA Mutagens
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Discovery and annotation of novel microRNAs in the porcine genome by using a semi-supervised transductive learning approach.

Genomics May 1, 2020
Despite the broad variety of available microRNA (miRNA) prediction tools, their application to the discovery and annotation of novel miRNA genes in domestic species is still limited. In this study we designed a comprehensive pipeline (eMIRNA) for miR...
Muscle, Skeletal Genetic Loci Molecular Sequence Annotation Genomics Liver MicroRNAs Genome Sequence Homology, Nucleic Acid Sus scrofa RNA Precursors Nucleotide Motifs Machine Learning Algorithms Animals Transcriptome RNA-Seq
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gammaBOriS: Identification and Taxonomic Classification of Origins of Replication in Gammaproteobacteria using Motif-based Machine Learning.

Scientific reports Apr 21, 2020
The biology of bacterial cells is, in general, based on information encoded on circular chromosomes. Regulation of chromosome replication is an essential process that mostly takes place at the origin of replication (oriC), a locus unique per chromoso...
Machine Learning Software Phylogeny Consensus Sequence Gammaproteobacteria Replication Origin Models, Genetic Base Sequence Nucleotide Motifs
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Deep neural networks for interpreting RNA-binding protein target preferences.

Genome research Feb 1, 2020
Deep learning has become a powerful paradigm to analyze the binding sites of regulatory factors including RNA-binding proteins (RBPs), owing to its strength to learn complex features from possibly multiple sources of raw data. However, the interpreta...
Humans Nucleotide Motifs Protein Binding RNA-Binding Proteins Neural Networks, Computer Binding Sites Algorithms Deep Learning
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Fast and accurate microRNA search using CNN.

BMC bioinformatics Dec 27, 2019
BACKGROUND: There are many different types of microRNAs (miRNAs) and elucidating their functions is still under intensive research. A fundamental step in functional annotation of a new miRNA is to classify it into characterized miRNA families, such a...
Nucleotide Motifs Base Sequence RNA, Transfer Base Pairing Neural Networks, Computer MicroRNAs Algorithms Probability
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Deciphering epigenomic code for cell differentiation using deep learning.

BMC genomics Sep 12, 2019
BACKGROUND: Although DNA sequence plays a crucial role in establishing the unique epigenome of a cell type, little is known about the sequence determinants that lead to the unique epigenomes of different cell types produced during cell differentiatio...
Cell Differentiation CD4-Positive T-Lymphocytes Nucleotide Motifs Cell Lineage Conserved Sequence Humans Histone Code Deep Learning Epigenomics
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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...
Gene Expression Regulation Computational Biology Nucleotide Motifs K562 Cells Transcription Factors Humans Binding Sites DNA Deep Learning Protein Binding
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Clustering and Candidate Motif Detection in Exosomal miRNAs by Application of Machine Learning Algorithms.

Interdisciplinary sciences, computational life sciences Jun 1, 2019
BACKGROUND: The clustering pattern and motifs give immense information about any biological data. An application of machine learning algorithms for clustering and candidate motif detection in miRNAs derived from exosomes is depicted in this paper. Re...
Gene Ontology Nucleotide Motifs Phylogeny Mice Cluster Analysis Humans Algorithms MicroRNAs Machine Learning Reproducibility of Results Exosomes Animals Base Sequence
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MD-SVM: a novel SVM-based algorithm for the motif discovery of transcription factor binding sites.

BMC bioinformatics May 1, 2019
BACKGROUND: Transcription factors (TFs) play important roles in the regulation of gene expression. They can activate or block transcription of downstream genes in a manner of binding to specific genomic sequences. Therefore, motif discovery of these ...
Support Vector Machine Binding Sites Algorithms Nucleotide Motifs Humans Protein Binding Transcription Factors
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Prediction of binding property of RNA-binding proteins using multi-sized filters and multi-modal deep convolutional neural network.

PloS one Jan 1, 2019
RNA-binding proteins (RBPs) are important in gene expression regulations by post-transcriptional control of RNAs and immune system development and its function. Due to the help of sequencing technology, numerous RNA sequences are newly discovered wit...
Deep Learning Protein Binding Area Under Curve Neural Networks, Computer Base Sequence Nucleotide Motifs
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