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Flash floods in Mediterranean catchments: a meta-model decision support system based on Bayesian networks
Natural disasters, especially those related to water—like storms and floods—have increased over the last decades both in number and intensity. Under...
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CausNet: generational orderings based search for optimal Bayesian networks via dynamic programming with parent set constraints
BackgroundFinding a globally optimal Bayesian Network using exhaustive search is a problem with super-exponential complexity, which severely...
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Bayesian networks elucidate complex genomic landscapes in cancer
Bayesian networks (BNs) are disciplined, explainable Artificial Intelligence models that can describe structured joint probability spaces. In the...
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Integration of Boolean and Bayesian Networks
One great challenge in biological study is to identify the complex gene regulation networks. For decades, scientists have developed different methods...
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Detecting social-ecological resilience thresholds of cultural landscapes along an urban–rural gradient: a methodological approach based on Bayesian Networks
ContextThe difficulty of analysing resilience and threshold responses to changing environmental drivers becomes evident in the social-ecological...
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Resampling reduces bias amplification in experimental social networks
Large-scale social networks are thought to contribute to polarization by amplifying people’s biases. However, the complexity of these technologies...
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Transcriptional differentiation driving Cucumis sativus–Botrytis cinerea interactions based on the Skellam model and Bayesian networks
Robust statistical tools such as the Skellam model and Bayesian networks can capture the count properties of transcriptome sequencing data and...
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Bayesian kinetic modeling for tracer-based metabolomic data
BackgroundStable Isotope Resolved Metabolomics (SIRM) is a new biological approach that uses stable isotope tracers such as uniformly
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VBASS enables integration of single cell gene expression data in Bayesian association analysis of rare variants
Rare or de novo variants have substantial contribution to human diseases, but the statistical power to identify risk genes by rare variants is...
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Bayesian stroke modeling details sex biases in the white matter substrates of aphasia
Ischemic cerebrovascular events often lead to aphasia. Previous work provided hints that such strokes may affect women and men in distinct ways....
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Bayesian Optimization in Drug Discovery
Drug discovery deals with the search for initial hits and their optimization toward a targeted clinical profile. Throughout the discovery pipeline,...
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Improved genomic prediction using machine learning with Variational Bayesian sparsity
BackgroundGenomic prediction has become a powerful modelling tool for assessing line performance in plant and livestock breeding programmes. Among...
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Improving the accuracy of genomic prediction in dairy cattle using the biologically annotated neural networks framework
BackgroundBiologically annotated neural networks (BANNs) are feedforward Bayesian neural network models that utilize partially connected...
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Gene regulatory network inference based on a nonhomogeneous dynamic Bayesian network model with an improved Markov Monte Carlo sampling
A nonhomogeneous dynamic Bayesian network model, which combines the dynamic Bayesian network and the multi-change point process, solves the...
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Practical application of a Bayesian network approach to poultry epigenetics and stress
BackgroundRelationships among genetic or epigenetic features can be explored by learning probabilistic networks and unravelling the dependencies...
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Boosting tissue-specific prediction of active cis-regulatory regions through deep learning and Bayesian optimization techniques
BackgroundCis-regulatory regions (CRRs) are non-coding regions of the DNA that fine control the spatio-temporal pattern of transcription; they are...
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Calibration of food and feed crop models for sweet peppers with Bayesian optimization
Crop models are tools used to analyze the interaction of crops and the environment. Since crop models can be applied to diverse research scales and...
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Inferring directional relationships in microbial communities using signed Bayesian networks
BackgroundMicrobe-microbe and host-microbe interactions in a microbiome play a vital role in both health and disease. However, the structure of the...
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SHARE-Topic: Bayesian interpretable modeling of single-cell multi-omic data
Multi-omic single-cell technologies, which simultaneously measure the transcriptional and epigenomic state of the same cell, enable understanding...
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deepGBLUP: joint deep learning networks and GBLUP framework for accurate genomic prediction of complex traits in Korean native cattle
BackgroundGenomic prediction has become widespread as a valuable tool to estimate genetic merit in animal and plant breeding. Here we develop a novel...
