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TISSUE: uncertainty-calibrated prediction of single-cell spatial transcriptomics improves downstream analyses
Whole-transcriptome spatial profiling of genes at single-cell resolution remains a challenge. To address this limitation, spatial gene expression...
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ENGEP: advancing spatial transcriptomics with accurate unmeasured gene expression prediction
Imaging-based spatial transcriptomics techniques provide valuable spatial and gene expression information at single-cell resolution. However, their...
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Spatial Gene Expression Prediction from Histology Images with STco
In recent years, the rapid development of spatial transcriptome technology has fundamentally transformed our understanding of gene expression...
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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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Genomic prediction for root and yield traits of barley under a water availability gradient: a case study comparing different spatial adjustments
BackgroundIn drought periods, water use efficiency depends on the capacity of roots to extract water from deep soil. A semi-field phenoty**...
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Drug-target interaction prediction based on spatial consistency constraint and graph convolutional autoencoder
BackgroundDrug-target interaction (DTI) prediction plays an important role in drug discovery and repositioning. However, most of the computational...
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Nonnegative spatial factorization applied to spatial genomics
Nonnegative matrix factorization (NMF) is widely used to analyze high-dimensional count data because, in contrast to real-valued alternatives such as...
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Benchmarking spatial and single-cell transcriptomics integration methods for transcript distribution prediction and cell type deconvolution
Spatial transcriptomics approaches have substantially advanced our capacity to detect the spatial distribution of RNA transcripts in tissues, yet it...
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Inferring super-resolution tissue architecture by integrating spatial transcriptomics with histology
Spatial transcriptomics (ST) has demonstrated enormous potential for generating intricate molecular maps of cells within tissues. Here we present...
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Gray Prediction
Prediction is a kind of activity that makes use of the knowledge and means that people have already mastered to predict and judge the future...
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PRMxAI: protein arginine methylation sites prediction based on amino acid spatial distribution using explainable artificial intelligence
BackgroundProtein methylation, a post-translational modification, is crucial in regulating various cellular functions. Arginine methylation is...
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Climate model selection via conformal clustering of spatial functional data
Climate model selection stands as a critical process in climate science and research. It involves choosing the most appropriate climate models to...
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RNA contact prediction by data efficient deep learning
On the path to full understanding of the structure-function relationship or even design of RNA, structure prediction would offer an intriguing...
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High-resolution prediction models for Rhipicephalus microplus and Amblyomma cajennense s.l. ticks affecting cattle and their spatial distribution in continental Ecuador using bioclimatic factors
In Ecuador, the main tick species affecting cattle are Rhipicephalus microplus and Amblyomma cajennense sensu lato. Understanding their spatial...
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GraphsformerCPI: Graph Transformer for Compound–Protein Interaction Prediction
Accurately predicting compound–protein interactions (CPI) is a critical task in computer-aided drug design. In recent years, the exponential growth...
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Deep learning-based fishing ground prediction with multiple environmental factors
Improving the accuracy of fishing ground prediction for oceanic economic species has always been one of the most concerning issues in fisheries...
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Sampling Design and Spatial Modeling of Available Phosphorus in a Complex Agricultural Area in Southern Brazil
In this study, we have compared three sampling designs and two modeling methods applied in the spatial prediction of available P in the soil. The...
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Spatial prediction of soil acidity and nutrients for site-specific soil management in Bedele district, Southwestern Ethiopia
BackgroundUnderstanding the spatial variability of soil properties is useful to tailor site-specific agricultural inputs to enhance crop production...
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Enhancing direct-seeded rice yield prediction using UAV-derived features acquired during the reproductive phase
Pre-harvest yield prediction of direct-seeded rice is critical for guiding crop interventions and food security assessment in precision agriculture....
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Benchmarking spatial clustering methods with spatially resolved transcriptomics data
Spatial clustering, which shares an analogy with single-cell clustering, has expanded the scope of tissue physiology studies from cell-centroid to...
