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How Parameters Influence Shape-Directed Predictions
The structure of an rna sequence encodes information about its biological function. Dynamic programming algorithms are often used to predict the...
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AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination
Artificial intelligence-based protein structure prediction methods such as AlphaFold have revolutionized structural biology. The accuracies of these...
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Digital Yield Predictions
Yield prediction is a vast area of study involving different fields of science such as agriculture, plant physiology, informatics, and machine...
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Epidemiology: Gray immunity model gives qualitatively different predictions
Compartmental models that dynamically divide the host population into categories such as susceptible, infected, and immune constitute the mainstream...
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Portability of genomic predictions trained on sparse factorial designs across two maize silage breeding cycles
Key messageWe validated the efficiency of genomic predictions calibrated on sparse factorial training sets to predict the next generation of hybrids...
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A comparison of RNA-Seq data preprocessing pipelines for transcriptomic predictions across independent studies
BackgroundRNA sequencing combined with machine learning techniques has provided a modern approach to the molecular classification of cancer. Class...
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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 effect of prediction error on episodic memory encoding is modulated by the outcome of the predictions
Expectations can lead to prediction errors of varying degrees depending on the extent to which the information encountered in the environment...
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Predictions of rhizosphere microbiome dynamics with a genome-informed and trait-based energy budget model
Soil microbiomes are highly diverse, and to improve their representation in biogeochemical models, microbial genome data can be leveraged to infer...
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Root anatomy and biomechanical properties: improving predictions through root cortical and stele properties
PurposeQuantifying the stability of individual plants or their contribution to soil reinforcement against erosion or landslides requires an...
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Chromatin profiling and state predictions reveal insights into epigenetic regulation during early porcine development
BackgroundGiven their physiological similarities to humans, pigs are increasingly used as model organisms in human-oriented biomedical studies....
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Optimizing age-related hearing risk predictions: an advanced machine learning integration with HHIE-S
ObjectivesThe elderly are disproportionately affected by age-related hearing loss (ARHL). Despite being a well-known tool for ARHL evaluation, the...
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Using the risk of spatial extrapolation by machine-learning models to assess the reliability of model predictions for conservation
ContextPredictive modeling is an integral part of broad-scale conservation efforts, and machine-learning (ML) models are increasingly being used for...
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SEMplMe: a tool for integrating DNA methylation effects in transcription factor binding affinity predictions
MotivationAberrant DNA methylation in transcription factor binding sites has been shown to lead to anomalous gene regulation that is strongly...
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Diurnal temperature fluctuations improve predictions of developmental rates in the spruce bark beetle Ips typographus
The European spruce bark beetle Ips typographus is a widespread pest in Norway spruce-dominated forests in Eurasia. Predicting its phenology and...
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FRETpredict: a Python package for FRET efficiency predictions using rotamer libraries
Förster resonance energy transfer (FRET) is a widely-used and versatile technique for the structural characterization of biomolecules. Here, we...
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Using pre-selected variants from large-scale whole-genome sequence data for single-step genomic predictions in pigs
BackgroundWhole-genome sequence (WGS) data harbor causative variants that may not be present in standard single nucleotide polymorphism (SNP) chip...
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Residual networks without pooling layers improve the accuracy of genomic predictions
Key messageResidual neural network genomic selection is the first GS algorithm to reach 35 layers, and its prediction accuracy surpasses previous...
