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Ensemble Machine Learning and Predicted Properties Promote Antimicrobial Peptide Identification
AbstractThe emergence of antibiotic-resistant microbes raises a pressing demand for novel alternative treatments. One promising alternative is the...
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Improved Regularized Multi-class Logistic Regression for Gene Classification with Optimal Kernel PCA and HC Algorithm
A significant challenge in high-dimensional and big data analysis is related to the classification and prediction of the variables of interest. The...
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Exploring brain plasticity in developmental dyslexia through implicit sequence learning
Developmental dyslexia (DD) is defined as difficulties in learning to read even with normal intelligence and adequate educational guidance. Deficits...
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Computer-Aided Diagnosis of Complications After Liver Transplantation Based on Transfer Learning
AbstractLiver transplantation is one of the most effective treatments for acute liver failure, cirrhosis, and even liver cancer. The prediction of...
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Hybrid deep learning approach to improve classification of low-volume high-dimensional data
BackgroundThe performance of machine learning classification methods relies heavily on the choice of features. In many domains, feature generation...
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Machine learning provides specific detection of salt and drought stresses in cucumber based on miRNA characteristics
BackgroundSpecific detection of the type and severity of plant abiotic stresses helps prevent yield loss by considering timely actions. This study...
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Predicting Microbe-Disease Associations Based on a Linear Neighborhood Label Propagation Method with Multi-order Similarity Fusion Learning
AbstractComputational approaches employed for predicting potential microbe-disease associations often rely on similarity information between microbes...
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A stacked deep learning approach for multiclass classification of plant diseases
PurposePlant diseases are one of the main factors affecting food production and reducing production losses, they must be swiftly identified and...
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Detecting gene–gene interactions from GWAS using diffusion kernel principal components
Genes and gene products do not function in isolation but as components of complex networks of macromolecules through physical or biochemical...
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Learning single-cell perturbation responses using neural optimal transport
Understanding and predicting molecular responses in single cells upon chemical, genetic or mechanical perturbations is a core question in biology....
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PrCRS: a prediction model of severe CRS in CAR-T therapy based on transfer learning
BackgroundCAR-T cell therapy represents a novel approach for the treatment of hematologic malignancies and solid tumors. However, its implementation...
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DeepHLAPred: a deep learning-based method for non-classical HLA binder prediction
Human leukocyte antigen (HLA) is closely involved in regulating the human immune system. Despite great advance in detecting classical HLA Class I...
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Liraglutide restores impaired associative learning in individuals with obesity
Survival under selective pressure is driven by the ability of our brain to use sensory information to our advantage to control physiological needs....
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A self-supervised deep learning method for data-efficient training in genomics
Deep learning in bioinformatics is often limited to problems where extensive amounts of labeled data are available for supervised classification. By...
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Use of kernel dorsal basal pigmentation in the absence of crown pigmentation for haploid classification in maize using R1-nj-based haploid inducers
Doubled haploid (DH) technology is growingly becoming an integral component of maize breeding programmes worldwide. The currently popular method of...
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PlantNh-Kcr: a deep learning model for predicting non-histone crotonylation sites in plants
BackgroundLysine crotonylation (Kcr) is a crucial protein post-translational modification found in histone and non-histone proteins. It plays a...
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Using transfer learning-based plant disease classification and detection for sustainable agriculture
Subsistence farmers and global food security depend on sufficient food production, which aligns with the UN's “Zero Hunger,” “Climate Action,” and...
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Classification of strawberry ripeness stages using machine learning algorithms and colour spaces
Accurate classification of strawberry ripeness is a crucial aspect of ensuring high-quality food products, optimizing harvesting and storage...
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A Random Forest-Convolutional Neural Network Deep Learning Model for Predicting the Wholesale Price Index of Potato in India
The wholesale price index (WPI) is a crucial economic indicator that provides insights into the pricing dynamics of different goods within a country,...
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A machine learning toolbox for the analysis of sharp-wave ripples reveals common waveform features across species
The study of sharp-wave ripples has advanced our understanding of memory function, and their alteration in neurological conditions such as epilepsy...
