James R. Wagner

TL;DR: This work developed PSORTb version 3.0 with improved recall, higher proteome-scale prediction coverage, and new refined localization subcategories, and evaluated the most accurate SCL predictors using 5-fold cross validation plus an independent proteomics analysis.

TL;DR: In this article, the authors report the joint analysis of sequence variants, gene expression and DNA methylation in primary fibroblast samples derived from a set of 62 unrelated individuals, with considerable involvement of chromatin features and some discernible involvement of sequence variation.

TL;DR: In this article, the authors investigate computational approaches to analyze genomic data and identify genomic regions with AI in an unbiased and robust statistical manner, and propose two families of approaches: (i) a statistical approach based on z-score computations, and (ii) a family of machine learning approaches based on Hidden Markov Models.

TL;DR: A new algorithm called Trajectory Clustering for Desire Lines (TraClus-DL), which can identify corridors from Origin-Destination information with simple parameters, such as spatial location, angles between lines, and sampling weights, is proposed.

TL;DR: A framework called Trajectory Clustering for Desire Lines (TraClus-DL) inspired by TraClus but more specialized for the identification of demand corridors from origin-destination information, using characteristics such as spatial location, angles between lines and sampling weights is proposed.