AIMC Topic: Deep Learning

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N6-methyladenine identification using deep learning and discriminative feature integration.

BMC medical genomics Mar 29, 2025
N6-methyladenine (6 mA) is a pivotal DNA modification that plays a crucial role in epigenetic regulation, gene expression, and various biological processes. With advancements in sequencing technologies and computational biology, there is an increasin...
Humans Algorithms Adenine Deep Learning DNA Methylation Computational Biology Principal Component Analysis
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A deep-learning algorithm (AIFORIA) for classification of hematopoietic cells in bone marrow aspirate smears based on nine cell classes-a feasible approach for routine screening?

Journal of hematopathology Mar 29, 2025
Bone marrow cytology plays a key role for the diagnosis and classification of hematological disease and is often the first step in the acute setting of unclear cytopenia. AI applications represent a powerful tool in digital image analysis and can imp...
Bone Marrow Examination Algorithms Deep Learning Bone Marrow Bone Marrow Cells Humans Neural Networks, Computer
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Enhancing convolutional neural networks in electroencephalogram driver drowsiness detection using human inspired optimizers.

Scientific reports Mar 29, 2025
Driver drowsiness is a significant safety concern, contributing to numerous traffic accidents. To address this issue, researchers have explored electroencephalogram (EEG)-based detection systems. Due to the high-dimensional nature of EEG signals and ...
Sleep Stages Accidents, Traffic Automobile Driving Adult Male Deep Learning Electroencephalography Neural Networks, Computer Algorithms Humans
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pACPs-DNN: Predicting anticancer peptides using novel peptide transformation into evolutionary and structure matrix-based images with self-attention deep learning model.

Computational biology and chemistry Mar 28, 2025
Globally, cancer remains a major health challenge due to its high mortality rates. Traditional experimental approaches and therapies are resource-intensive and often cause significant side effects. Anticancer peptides (ACPs) have emerged as alternati...
Neural Networks, Computer Peptides Humans Antineoplastic Agents Deep Learning
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Perspectives: Comparison of deep learning segmentation models on biophysical and biomedical data.

Biophysical journal Mar 28, 2025
Deep learning-based approaches are now widely used across biophysics to help automate a variety of tasks including image segmentation, feature selection, and deconvolution. However, the presence of multiple competing deep learning architectures, each...
Deep Learning Image Processing, Computer-Assisted Humans Neural Networks, Computer
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Enhancing visual speech perception through deep automatic lipreading: A systematic review.

Computers in biology and medicine Mar 28, 2025
Communication involves exchanging information between individuals or groups through various media sources. However, limitations such as hearing loss can make it difficult for some individuals to understand the information delivered during speech comm...
Lipreading Humans Deep Learning Speech Perception
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Fitting Atomic Structures into Cryo-EM Maps by Coupling Deep Learning-Enhanced Map Processing with Global-Local Optimization.

Journal of chemical information and modeling Mar 28, 2025
With the breakthroughs in protein structure prediction technology, constructing atomic structures from cryo-electron microscopy (cryo-EM) density maps through structural fitting has become increasingly critical. However, the accuracy of the construct...
Proteins Deep Learning Models, Molecular Protein Conformation Cryoelectron Microscopy
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Atomic context-conditioned protein sequence design using LigandMPNN.

Nature methods Mar 28, 2025
Protein sequence design in the context of small molecules, nucleotides and metals is critical to enzyme and small-molecule binder and sensor design, but current state-of-the-art deep-learning-based sequence design methods are unable to model nonprote...
Protein Binding Proteins Deep Learning Ligands Crystallography, X-Ray Models, Molecular Amino Acid Sequence Protein Conformation
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CRISPR-MFH: A Lightweight Hybrid Deep Learning Framework with Multi-Feature Encoding for Improved CRISPR-Cas9 Off-Target Prediction.

Genes Mar 28, 2025
BACKGROUND: The CRISPR-Cas9 system has emerged as one of the most promising gene-editing technologies in biology. However, off-target effects remain a significant challenge. While recent advances in deep learning have led to the development of models...
Gene Editing Deep Learning Humans RNA, Guide, CRISPR-Cas Systems CRISPR-Cas Systems
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Prediction and Prioritisation of Novel Anthelmintic Candidates from Public Databases Using Deep Learning and Available Bioactivity Data Sets.

International journal of molecular sciences Mar 28, 2025
The control of socioeconomically important parasitic roundworms (nematodes) of animals has become challenging or ineffective due to problems associated with widespread resistance in these worms to most classes of chemotherapeutic drugs (anthelmintics...
Deep Learning Haemonchus Animals Anthelmintics Databases, Factual Drug Discovery Computer Simulation
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