Anthony Gitter

TL;DR: It is found that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art.

TL;DR: The basic patterns that have been observed in time-series experiments are discussed, how these patterns are combined to form expression programs, and the computational analysis, visualization and integration of these data to infer models of dynamic biological systems.

TL;DR: Together, these changes improve the ability of DREM 2.0 to accurately recover dynamic regulatory networks and make it much easier to use it for analyzing such networks in several species with varying degrees of interaction information.

TL;DR: Omics Integrator as discussed by the authors is a software package that takes a variety of 'omic' data as input and identifies putative underlying molecular pathways by applying advanced network optimization algorithms to a network of thousands of molecular interactions to find high-confidence, interpretable subnetworks that best explain the data.

TL;DR: This work formalizes the orientation problem in weighted protein interaction graphs as an optimization problem and presents three approximation algorithms based on either weighted Boolean satisfiability solvers or probabilistic assignments that are used to identify pathways in yeast.