Edoardo M. Airoldi

TL;DR: In this paper, the authors present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macro-autophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.

TL;DR: In this article, the authors introduce a class of variance allocation models for pairwise measurements, called mixed membership stochastic blockmodels, which combine global parameters that instantiate dense patches of connectivity (blockmodel) with local parameters (mixed membership), and develop a general variational inference algorithm for fast approximate posterior inference.

TL;DR: The mixed membership stochastic block model as discussed by the authors extends block models for relational data to ones which capture mixed membership latent relational structure, thus providing an object-specific low-dimensional representation.

TL;DR: In this paper, a mixture-of-isoforms (MISO) model was proposed to estimate expression of alternatively spliced exons and isoforms and assesses confidence in these estimates.

TL;DR: The mixture-of-isoforms (MISO) model is developed, a statistical model that estimates expression of alternatively spliced exons and isoforms and assesses confidence in these estimates, providing a probabilistic framework for RNA-seq analysis and functional insights into pre-mRNA processing.