Sean Michael Boyle

TL;DR: A model of tumor epitope immunogenicity was developed that filtered out 98% of non-immunogenic peptides with a precision above 0.70 and was validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding.

TL;DR: This work proposes an algorithm for detecting gene–disease associations based on the human protein–protein interaction network, known gene-diseases associations, protein sequence, and protein functional information at the molecular level, and provided evidence that, despite the noise/incompleteness of experimental data and unfinished ontology of diseases, identification of candidate genes can be successful even when a large number of candidate disease terms are predicted on simultaneously.

TL;DR: It is demonstrated that activity of this neuron is important for attraction to skin odor, establishing it as a key target for intervention in mosquito host-seeking behavior and identifies odors that are potentially safe, pleasant, and affordable for use in a new generation of mosquito control strategies worldwide.

TL;DR: A cheminformatics pipeline is developed that predicts receptor–odorant interactions from a large collection of chemical structures for receptors that have been tested to a smaller panel of odorants and results in identification of numerous new activators and inhibitors in the Drosophila antenna.

TL;DR: In this article, a multi-dimensional approach modeling both tumor and immune-related molecular mechanisms was proposed to predict immune checkpoint blockade (ICB) response, which significantly stratified responders and nonresponders.