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Graph regularized non-negative matrix factorization with prior knowledge consistency constraint for drug–target interactions prediction
BackgroundIdentifying drug–target interactions (DTIs) plays a key role in drug development. Traditional wet experiments to identify DTIs are...
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Thresholds and prediction models to support the sustainable management of herbivorous insects in wheat. A review
Wheat is one of the most important arable crops grown worldwide, providing a significant proportion of the daily calorific intake for countries...
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Genetic map** and genomic prediction of sclerotinia stem rot resistance to rapeseed/canola (Brassica napus L.) at seedling stage
Key messageGWAS detected ninety-eight significant SNPs associated with Sclerotinia sclerotiorum resistance. Six statistical models resulted in...
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GCRNN: graph convolutional recurrent neural network for compound–protein interaction prediction
BackgroundCompound–protein interaction prediction is necessary to investigate health regulatory functions and promotes drug discovery. Machine...
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CircSSNN: circRNA-binding site prediction via sequence self-attention neural networks with pre-normalization
BackgroundCircular RNAs (circRNAs) play a significant role in some diseases by acting as transcription templates. Therefore, analyzing the...
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EMDLP: Ensemble multiscale deep learning model for RNA methylation site prediction
BackgroundRecent research recommends that epi-transcriptome regulation through post-transcriptional RNA modifications is essential for all sorts of...
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Machine learning based mass prediction and discrimination of chickpea (Cicer arietinum L.) cultivars
Chickpea is an important edible legume that can be grown in rain fed conditions. Image analysis and machine learning could be used for rapid and...
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Prediction of moisture-induced cracks in wooden cross sections using finite element simulations
Wood absorbs and desorbs moisture due to its hygroscopic behavior, leading to moisture gradients in timber elements as well as swelling and...
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Improving the Prediction of Potential Kinase Inhibitors with Feature Learning on Multisource Knowledge
PurposeThe identification of potential kinase inhibitors plays a key role in drug discovery for treating human diseases. Currently, most existing...
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Spatial prediction of soil micronutrients using machine learning algorithms integrated with multiple digital covariates
The design and application of multiple tools to map soil micronutrients is key to efficient land management. While collecting a representative number...
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Prediction of lncRNA functions using deep neural networks based on multiple networks
BackgroundMore and more studies show that lncRNA is widely involved in various physiological processes of the organism. However, the functions of the...
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Genome-Wide Association Study (GWAS) and genome prediction of seedling salt tolerance in bread wheat (Triticum aestivum L.)
BackgroundSalinity tolerance in wheat is imperative for improving crop genetic capacity in response to the expanding phenomenon of soil salinization....
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Climate limits vegetation green-up more than slope, soil erodibility, and immediate precipitation following high-severity wildfire
BackgroundIn the southwestern United States, post-fire vegetation recovery is increasingly variable in forest burned at high severity. Many factors,...
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Pushing the limits: ship rat (Rattus rattus) population dynamics across an elevational gradient in response to mast seeding and supplementary feeding
Understanding marginal habitat use by invasive species is important for predicting how distributions may change under future climates. We...
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KEGG orthology prediction of bacterial proteins using natural language processing
BackgroundThe advent of high-throughput technologies has led to an exponential increase in uncharacterized bacterial protein sequences, surpassing...
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Benchmarking AutoML frameworks for disease prediction using medical claims
ObjectivesAscertain and compare the performances of Automated Machine Learning (AutoML) tools on large, highly imbalanced healthcare datasets.
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Prediction of hot spots in protein–DNA binding interfaces based on discrete wavelet transform and wavelet packet transform
BackgroundIdentification of hot spots in protein–DNA binding interfaces is extremely important for understanding the underlying mechanisms of...
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Genomic prediction in hybrid breeding: II. Reciprocal recurrent genomic selection with full-sib and half-sib families
Key messageGenomic prediction of GCA effects based on model training with full-sib rather than half-sib families yields higher short- and long-term...
