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PredAPP: Predicting Anti-Parasitic Peptides with Undersampling and Ensemble Approaches
Anti-parasitic peptides (APPs) have been regarded as promising therapeutic candidate drugs against parasitic diseases. Due to the fact that the...
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Human Multi-omics Data Pre-processing for Predictive Purposes Using Machine Learning: A Case Study in Childhood Obesity
The Machine Learning applications in the medical field using omics data are countless and promising, highlighting the possibility of creating...
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Multi-labelled proteins recognition for high-throughput microscopy images using deep convolutional neural networks
BackgroundProteins are of extremely vital importance in the human body, and no movement or activity can be performed without proteins. Currently,...
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Large-scale protein-protein post-translational modification extraction with distant supervision and confidence calibrated BioBERT
MotivationProtein-protein interactions (PPIs) are critical to normal cellular function and are related to many disease pathways. A range of protein...
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Multiple Protein Subcellular Locations Prediction Based on Deep Convolutional Neural Networks with Self-Attention Mechanism
As an important research field in bioinformatics, protein subcellular location prediction is critical to reveal the protein functions and provide...
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Hellinger distance-based stable sparse feature selection for high-dimensional class-imbalanced data
BackgroundFeature selection in class-imbalance learning has gained increasing attention in recent years due to the massive growth of high-dimensional...
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Characterizing the impacts of dataset imbalance on single-cell data integration
Computational methods for integrating single-cell transcriptomic data from multiple samples and conditions do not generally account for imbalances in...
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HostNet: improved sequence representation in deep neural networks for virus-host prediction
BackgroundThe escalation of viruses over the past decade has highlighted the need to determine their respective hosts, particularly for emerging ones...
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Application of the class-balancing strategies with bootstrap** for fitting logistic regression models for post-fire tree mortality in South Korea
We aimed to tackle a common problem in post-fire tree mortality where the number of trees that survived surpasses the number of dead trees. Here, we...
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A novel two-way rebalancing strategy for identifying carbonylation sites
BackgroundAs an irreversible post-translational modification, protein carbonylation is closely related to many diseases and aging. Protein...
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Generalizability of machine learning in predicting antimicrobial resistance in E. coli: a multi-country case study in Africa
BackgroundAntimicrobial resistance (AMR) remains a significant global health threat particularly impacting low- and middle-income countries (LMICs)....
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The effect of data balancing approaches on the prediction of metabolic syndrome using non-invasive parameters based on random forest
BackgroundMetabolic syndrome (MetS) is a cluster of metabolic abnormalities (including obesity, insulin resistance, hypertension, and dyslipidemia),...
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Machine learning and drug discovery for neglected tropical diseases
Neglected tropical diseases affect millions of individuals and cause loss of productivity worldwide. They are common in develo** countries without...
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Optimizing diabetes classification with a machine learning-based framework
BackgroundDiabetes is a metabolic disorder usually caused by insufficient secretion of insulin from the pancreas or insensitivity of cells to...
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Faster and more accurate pathogenic combination predictions with VarCoPP2.0
BackgroundThe prediction of potentially pathogenic variant combinations in patients remains a key task in the field of medical genetics for the...
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The DeepFaune initiative: a collaborative effort towards the automatic identification of European fauna in camera trap images
Camera traps have revolutionized how ecologists monitor wildlife, but their full potential is realized only when the hundreds of thousands of...
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Cervical Cancer Classification From Pap Smear Images Using Deep Convolutional Neural Network Models
As one of the most common female cancers, cervical cancer often develops years after a prolonged and reversible pre-cancerous stage. Traditional...
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Oxygen-Dependent Aspects of Asprosin Action
AbstractAsprosin, a novel adipokine secreted mainly by white adipose tissue, regulates organismal responses to short-term fasting, initiates glucose...
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GBDT_KgluSite: An improved computational prediction model for lysine glutarylation sites based on feature fusion and GBDT classifier
BackgroundLysine glutarylation (Kglu) is one of the most important Post-translational modifications (PTMs), which plays significant roles in various...
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MONTAGE: a new tool for high-throughput detection of mosaic copy number variation
BackgroundNot all cells in a given individual are identical in their genomic makeup. Mosaicism describes such a phenomenon where a mixture of...
