MixALime is a tool for the identification of allele-specific variants (ASVs or allele-specific events, ASEs) in high-throughput sequencing data. It works by modelling counts data as a mixture of two ...

A deep count autoencoder network to denoise scRNA-seq data and remove the dropout effect by taking the count structure, overdispersed nature and sparsity of the data into account using a deep ...

Modern, large-scale scientific datasets with tens of thousands of variables and millions of samples can accelerate scientific discovery by revealing underlying structure in data based on dependence ...

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Monte Carlo simulation is a method used to analyze the uncertainty and risk associated with a project, such as an oil and gas project. I have developed a basic version of the Monte Carlo Simulation ...

Tensor decomposition- and principal component analysis-based unsupervised feature extraction were proposed almost 5 and 10 years ago, respectively; although these methods have been successfully ...

Negative regulatory elements (NREs) down-regulate gene expression by inhibiting the activities of promoters or enhancers. The repressing activity of NREs can be measured globally by massively parallel ...

A major challenge in studying intention reading is high motor variability. Analyses conducted across trials provide insights into what happens on average; however, they may obscure how individual ...

Predictive microbiology models explain bacterial number variations over time and how growth/inactivation rates are affected by environmental conditions (Lammerding and Fazil, 2000). In the development ...

Binomial trees are used to price many options, including European options, American options, and also exotics such as barrier options, digital options, and Asian options, to name a few. They make this ...