AIMC Topic: DNA

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DeepATT: a hybrid category attention neural network for identifying functional effects of DNA sequences.

Briefings in bioinformatics May 20, 2021
Quantifying DNA properties is a challenging task in the broad field of human genomics. Since the vast majority of non-coding DNA is still poorly understood in terms of function, this task is particularly important to have enormous benefit for biology...
Databases, Nucleic Acid Regulatory Sequences, Nucleic Acid Sequence Analysis, DNA DNA Neural Networks, Computer
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DeepTorrent: a deep learning-based approach for predicting DNA N4-methylcytosine sites.

Briefings in bioinformatics May 20, 2021
DNA N4-methylcytosine (4mC) is an important epigenetic modification that plays a vital role in regulating DNA replication and expression. However, it is challenging to detect 4mC sites through experimental methods, which are time-consuming and costly...
DNA Methylation DNA Deep Learning Epigenesis, Genetic
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Prediction of bio-sequence modifications and the associations with diseases.

Briefings in functional genomics Mar 2, 2021
Modifications of protein, RNA and DNA play an important role in many biological processes and are related to some diseases. Therefore, accurate identification and comprehensive understanding of protein, RNA and DNA modification sites can promote rese...
Proteins DNA RNA Machine Learning Computational Biology
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Deep learning for nanopore ionic current blockades.

The Journal of chemical physics Jan 28, 2021
DNA molecules can electrophoretically be driven through a nanoscale opening in a material, giving rise to rich and measurable ionic current blockades. In this work, we train machine learning models on experimental ionic blockade data from DNA nucleot...
Deep Learning Ions Disulfides DNA Molybdenum Nanopores
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[Identification of nucleosome positioning using support vector machine method based on comprehensive DNA sequence feature].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Jun 25, 2020
In this article, based on z-curve theory and position weight matrix (PWM), a model for nucleosome sequences was constructed. Nucleosome sequence dataset was transformed into three-dimensional coordinates, PWM of the nucleosome sequences was calculate...
Caenorhabditis elegans Reproducibility of Results Nucleosomes Saccharomyces cerevisiae Animals DNA Drosophila melanogaster Support Vector Machine
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DNA4mC-LIP: a linear integration method to identify N4-methylcytosine site in multiple species.

Bioinformatics (Oxford, England) Jun 1, 2020
MOTIVATION: DNA N4-methylcytosine (4mC) is a crucial epigenetic modification. However, the knowledge about its biological functions is limited. Effective and accurate identification of 4mC sites will be helpful to reveal its biological functions and ...
DNA Epigenesis, Genetic Machine Learning Research Design
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iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data.

Briefings in bioinformatics May 21, 2020
With the explosive growth of biological sequences generated in the post-genomic era, one of the most challenging problems in bioinformatics and computational biology is to computationally characterize sequences, structures and functions in an efficie...
Machine Learning Algorithms Sequence Analysis Internet RNA Proteins DNA
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Identifying enhancer-promoter interactions with neural network based on pre-trained DNA vectors and attention mechanism.

Bioinformatics (Oxford, England) Feb 15, 2020
MOTIVATION: Identification of enhancer-promoter interactions (EPIs) is of great significance to human development. However, experimental methods to identify EPIs cost too much in terms of time, manpower and money. Therefore, more and more research ef...
Promoter Regions, Genetic Regulatory Sequences, Nucleic Acid DNA Attention Neural Networks, Computer Humans
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Deep Learning in the Study of Protein-Related Interactions.

Protein and peptide letters Jan 1, 2020
Protein-related interaction prediction is critical to understanding life processes, biological functions, and mechanisms of drug action. Experimental methods used to determine proteinrelated interactions have always been costly and inefficient. In re...
RNA Protein Binding Pharmaceutical Preparations Proteins Databases, Protein DNA Drug Design Humans Deep Learning
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DeePaC: predicting pathogenic potential of novel DNA with reverse-complement neural networks.

Bioinformatics (Oxford, England) Jan 1, 2020
MOTIVATION: We expect novel pathogens to arise due to their fast-paced evolution, and new species to be discovered thanks to advances in DNA sequencing and metagenomics. Moreover, recent developments in synthetic biology raise concerns that some stra...
Neural Networks, Computer DNA Deep Learning Sequence Analysis, DNA
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