AIMC Topic: Nucleotide Motifs

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DiscMLA: An Efficient Discriminative Motif Learning Algorithm over High-Throughput Datasets.

IEEE/ACM transactions on computational biology and bioinformatics May 3, 2016
The transcription factors (TFs) can activate or suppress gene expression by binding to specific sites, hence are crucial regulatory elements for transcription. Recently, series of discriminative motif finders have been tailored to offering promising ...
Area Under Curve High-Throughput Nucleotide Sequencing Nucleotide Motifs Chromatin Immunoprecipitation Transcription Factors Databases, Genetic Sequence Analysis, DNA Cell Line, Tumor Computational Biology Humans Machine Learning Algorithms
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SVM2Motif--Reconstructing Overlapping DNA Sequence Motifs by Mimicking an SVM Predictor.

PloS one Dec 21, 2015
Identifying discriminative motifs underlying the functionality and evolution of organisms is a major challenge in computational biology. Machine learning approaches such as support vector machines (SVMs) achieve state-of-the-art performances in genom...
Models, Genetic Humans Sequence Analysis, DNA Machine Learning Nucleotide Motifs
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A Further Study on Mining DNA Motifs Using Fuzzy Self-Organizing Maps.

IEEE transactions on neural networks and learning systems Jun 9, 2015
Self-organizing map (SOM)-based motif mining, despite being a promising approach for problem solving, mostly fails to offer a consistent interpretation of clusters with respect to the mixed composition of signal and noise in the nodes. The main reaso...
Humans Fuzzy Logic Cluster Analysis Nucleotide Motifs Animals Computational Biology Databases, Genetic Neural Networks, Computer Algorithms
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De novo transcriptome assembly of pummelo and molecular marker development.

PloS one Mar 23, 2015
Pummelo (Citrus grandis) is an important fruit crop worldwide because of its nutritional value. To accelerate the pummelo breeding program, it is essential to obtain extensive genetic information and develop relative molecular markers. Here, we obtai...
Physical Chromosome Mapping Genetic Markers High-Throughput Nucleotide Sequencing Phenotype Gene Frequency Phylogeny Nucleotide Motifs Polymorphism, Single Nucleotide Reproducibility of Results Citrus Gene Expression Profiling Gene Library Cluster Analysis Molecular Sequence Annotation Transcriptome Microsatellite Repeats Gene Ontology
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An improved poly(A) motifs recognition method based on decision level fusion.

Computational biology and chemistry Dec 30, 2014
Polyadenylation is the process of addition of poly(A) tail to mRNA 3' ends. Identification of motifs controlling polyadenylation plays an essential role in improving genome annotation accuracy and better understanding of the mechanisms governing gene...
Nucleotide Motifs Molecular Sequence Data Poly A Polyadenylation RNA, Messenger Support Vector Machine Principal Component Analysis Computational Biology
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iM-Seeker: a webserver for DNA i-motifs prediction and scoring via automated machine learning.

Nucleic acids research Jul 5, 2024
DNA, beyond its canonical B-form double helix, adopts various alternative conformations, among which the i-motif, emerging in cytosine-rich sequences under acidic conditions, holds significant biological implications in transcription modulation and t...
Humans Machine Learning DNA Internet Nucleotide Motifs Software Algorithms Sequence Analysis, DNA
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Unveil cis-acting combinatorial mRNA motifs by interpreting deep neural network.

Bioinformatics (Oxford, England) Jun 28, 2024
SUMMARY: Cis-acting mRNA elements play a key role in the regulation of mRNA stability and translation efficiency. Revealing the interactions of these elements and their impact plays a crucial role in understanding the regulation of the mRNA translati...
Nucleotide Motifs Computational Biology RNA, Messenger Humans Neural Networks, Computer Deep Learning
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Prediction of DNA i-motifs via machine learning.

Nucleic acids research Mar 21, 2024
i-Motifs (iMs), are secondary structures formed in cytosine-rich DNA sequences and are involved in multiple functions in the genome. Although putative iM forming sequences are widely distributed in the human genome, the folding status and strength of...
Base Sequence Humans Nucleotide Motifs Machine Learning Cytosine DNA
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DeepLocRNA: an interpretable deep learning model for predicting RNA subcellular localization with domain-specific transfer-learning.

Bioinformatics (Oxford, England) Feb 1, 2024
MOTIVATION: Accurate prediction of RNA subcellular localization plays an important role in understanding cellular processes and functions. Although post-transcriptional processes are governed by trans-acting RNA binding proteins (RBPs) through intera...
Humans Computational Biology RNA, Messenger RNA-Binding Proteins Animals Deep Learning Mice RNA Nucleotide Motifs
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ScanNet uncovers binding motifs in protein structures with deep learning.

Nature methods Jun 1, 2022
Nucleotide Motifs Amino Acid Motifs Protein Binding Binding Sites Deep Learning
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