AIMC Topic: DNA

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DeepDBS: Identification of DNA-binding sites in protein sequences by using deep representations and random forest.

Methods (San Diego, Calif.) Sep 11, 2024
Interactions of biological molecules in organisms are considered to be primary factors for the lifecycle of that organism. Various important biological functions are dependent on such interactions and among different kinds of interactions, the protei...
Binding Sites Sequence Analysis, Protein DNA-Binding Proteins Amino Acid Sequence Protein Binding Computational Biology Algorithms DNA Deep Learning Random Forest Neural Networks, Computer Databases, Protein
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Rewireable Building Blocks for Enzyme-Powered DNA Computing Networks.

Journal of the American Chemical Society Sep 10, 2024
Neural networks enable the processing of large, complex data sets with applications in disease diagnosis, cell profiling, and drug discovery. Beyond electronic computers, neural networks have been implemented using programmable biomolecules such as D...
Neurons DNA, Single-Stranded Computers, Molecular Neural Networks, Computer DNA
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Deciphering the Language of Protein-DNA Interactions: A Deep Learning Approach Combining Contextual Embeddings and Multi-Scale Sequence Modeling.

Journal of molecular biology Aug 29, 2024
Deciphering the mechanisms governing protein-DNA interactions is crucial for understanding key cellular processes and disease pathways. In this work, we present a powerful deep learning approach that significantly advances the computational predictio...
DNA-Binding Proteins Neural Networks, Computer Computational Biology Deep Learning Binding Sites DNA Protein Binding
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Quantum mechanical electronic and geometric parameters for DNA k-mers as features for machine learning.

Scientific data Aug 22, 2024
We are witnessing a steep increase in model development initiatives in genomics that employ high-end machine learning methodologies. Of particular interest are models that predict certain genomic characteristics based solely on DNA sequence. These mo...
Machine Learning DNA Quantum Theory
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A novel deep learning identifier for promoters and their strength using heterogeneous features.

Methods (San Diego, Calif.) Aug 19, 2024
Promoters, which are short (50-1500 base-pair) in DNA regions, have emerged to play a critical role in the regulation of gene transcription. Numerous dangerous diseases, likewise cancer, cardiovascular, and inflammatory bowel diseases, are caused by ...
Humans Promoter Regions, Genetic Computational Biology Neural Networks, Computer DNA Deep Learning
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Machine Learning-Assisted Near-Infrared Spectral Fingerprinting for Macrophage Phenotyping.

ACS nano Aug 15, 2024
Spectral fingerprinting has emerged as a powerful tool that is adept at identifying chemical compounds and deciphering complex interactions within cells and engineered nanomaterials. Using near-infrared (NIR) fluorescence spectral fingerprinting coup...
RAW 264.7 Cells DNA Nanotubes, Carbon Spectroscopy, Near-Infrared Mice Machine Learning Phenotype Animals Macrophages
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Deep learning based method for predicting DNA N6-methyladenosine sites.

Methods (San Diego, Calif.) Aug 6, 2024
DNA N6 methyladenine (6mA) plays an important role in many biological processes, and accurately identifying its sites helps one to understand its biological effects more comprehensively. Previous traditional experimental methods are very labor-intens...
Computational Biology DNA Methylation DNA Humans Deep Learning Adenosine
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Geometric deep learning of protein-DNA binding specificity.

Nature methods Aug 5, 2024
Predicting protein-DNA binding specificity is a challenging yet essential task for understanding gene regulation. Protein-DNA complexes usually exhibit binding to a selected DNA target site, whereas a protein binds, with varying degrees of binding sp...
DNA-Binding Proteins Binding Sites DNA Models, Molecular Deep Learning Protein Binding Computational Biology
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Exploring the roles of RNAs in chromatin architecture using deep learning.

Nature communications Jul 29, 2024
Recent studies have highlighted the impact of both transcription and transcripts on 3D genome organization, particularly its dynamics. Here, we propose a deep learning framework, called AkitaR, that leverages both genome sequences and genome-wide RNA...
RNA, Long Noncoding Humans DNA RNA Deep Learning Chromatin Cell Line
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DeepPGD: A Deep Learning Model for DNA Methylation Prediction Using Temporal Convolution, BiLSTM, and Attention Mechanism.

International journal of molecular sciences Jul 26, 2024
As part of the field of DNA methylation identification, this study tackles the challenge of enhancing recognition performance by introducing a specialized deep learning framework called DeepPGD. DNA methylation, a crucial biological modification, pla...
Computational Biology Algorithms Humans DNA Deep Learning Neural Networks, Computer DNA Methylation
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