Background LASSO is a penalized regression method that facilitates model fitting in
situations where there are as many, or even more explanatory variables than observations …

The continuous advancement in genotyping technology has not been accompanied by the
application of innovative statistical methods, such as multi-marker methods (MMM), to …

Black blooms are a serious and complex problem for lake bays, with far-reaching
implications for water quality and drinking safety. While Fe (II) and S (− II) have been …

Ecological communities are shaped by a complex interplay between abiotic forcing, biotic
regulation and demographic stochasticity. However, community dynamics modelers tend to …

The North Atlantic Ocean has large seasonal blooms rich in diatoms and dinoflagellates
which can contribute disproportionately relative to other primary producers to export …

Background In quantitative trait mapping and genomic prediction, Bayesian variable
selection methods have gained popularity in conjunction with the increase in marker data …

Genome-wide association studies (GWAS) have identified a large amount of single-
nucleotide polymorphisms (SNPs) associated with complex traits. A recently developed …

In this work, we investigated the prognosis of three medical data specifically, breast cancer,
heart disease, and prostate cancer by using 10 machine learning models. We applied all 10 …

We review the use of Bayesian methods for analysing gene expression data, from
microarrays and bulk RNA sequencing, focusing on methods which select groups of genes …

Modeling financial returns is challenging because the correlations and variance of returns
are time-varying and the covariance matrices can be quite high-dimensional. In this paper …