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Comparative analysis of parametric and non-parametric statistics for grain yield stability in rice (Oryza sativa L.)
Basmati rice is an important cereal crop occupying a unique position in Indian agriculture. More than 90% of global rice is produced and consumed in...
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A fast non-parametric test of association for multiple traits
The increasing availability of multidimensional phenotypic data in large cohorts of genotyped individuals requires efficient methods to identify...
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Non-parametric synergy modeling of chemical compounds with Gaussian processes
BackgroundUnderstanding the synergetic and antagonistic effects of combinations of drugs and toxins is vital for many applications, including...
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Bayesian non-parametric detection heterogeneity in ecological models
Detection heterogeneity is inherent to ecological data, arising from factors such as varied terrain or weather conditions, inconsistent sampling...
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A direct approach of causal detection for agriculture related variables via spatial and temporal non-parametric analysis
Understanding the causality between biological variables or their related variables is beneficial in environmental or biological policy making. The...
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Rooting of forest species mini-cuttings: an application of non-parametric survival analysis
The adventitious rooting of mini-cuttings with less time spent in the greenhouse is a desired step in plant production in forestry companies. This...
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SPARK-X: non-parametric modeling enables scalable and robust detection of spatial expression patterns for large spatial transcriptomic studies
Spatial transcriptomic studies are becoming increasingly common and large, posing important statistical and computational challenges for many...
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Non-parametric and semi-parametric support estimation using SEquential RESampling random walks on biomolecular sequences
Non-parametric and semi-parametric resampling procedures are widely used to perform support estimation in computational biology and bioinformatics....
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A transformer model for cause-specific hazard prediction
BackgroudModelling discrete-time cause-specific hazards in the presence of competing events and non-proportional hazards is a challenging task in...
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Rethinking model-based and model-free influences on mental effort and striatal prediction errors
A standard assumption in neuroscience is that low-effort model-free learning is automatic and continuously used, whereas more complex model-based...
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Model Building
This introductory chapter is about fundamental ideas involved in model selection such as between a model-based or design-based approach, or a...
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Feasibility in MacArthur’s consumer-resource model
Finding the conditions that ensure the survival of species has occupied ecologists for decades. Theoretically, for mechanistic models such as...
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A three-dimensional model of terrain-induced updrafts for movement ecology studies
BackgroundSpatially explicit simulation models of animal movements through the atmosphere necessarily require a representation of the spatial and...
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The therapeutic potential of Camel Wharton jelly mesenchymal stem cells (CWJ-MSCs) in canine chronic kidney disease model
BackgroundChronic kidney disease (CKD) is a worldwide health problem that its incidence increases nowadays with the increase in the risk of...
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The teaching of evolutionary theory and the Cosmos–Evidence–Ideas model
Evolutionary theory (ET), as many researchers have pointed out, is one of the cornerstones of Biology, whose understanding facilitates the study of...
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On a population model with density dependence and Allee effect
We study the dynamics of a discrete model with two different stages of the population, the pre-adult stage governed by a Beverton–Holt-type map and...
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A model of conceptual bootstrap** in human cognition
To tackle a hard problem, it is often wise to reuse and recombine existing knowledge. Such an ability to bootstrap enables us to grow rich mental...
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Robust variable selection with exponential squared loss for the partially linear varying coefficient spatial autoregressive model
The partially linear varying coefficient spatial autoregressive model is a semi-parametric spatial autoregressive model in which the coefficients of...
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StackDPP: a stacking ensemble based DNA-binding protein prediction model
BackgroundDNA-binding proteins (DNA-BPs) are the proteins that bind and interact with DNA. DNA-BPs regulate and affect numerous biological processes,...
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A mathematical model with uncertainty quantification for allelopathy with applications to real-world data
We revisit a deterministic model for studying the dynamics of allelopathy. The model is formulated in terms of a non-homogeneous linear system of...
