Jeffrey W. Miller

TL;DR: Using an integrated multidisciplinary biopsy program, it is demonstrated that real-time genomic characterization of advanced PDAC can identify clinically relevant alterations that inform management of this difficult disease.

TL;DR: This work introduces a novel approach to Bayesian inference that improves robustness to small departures from the model: rather than conditioning on the event that the observed data are generated by the model, one conditions on theevent that the model generates data close to the observedData, in a distributional sense.

TL;DR: The most commonly used method of inference for MFMs is reversible jump Markov chain Monte Carlo, but it can be nontrivial to design good reversible jump moves, especially in high-dimensional spaces as discussed by the authors.

TL;DR: It turns out that many of the essential properties of DPMs are also exhibited by MFMs, and the MFM analogues are simple enough that they can be used much like the corresponding DPM properties; this simplifies the implementation of MFMs and can substantially improve mixing.

TL;DR: The CSER consortium is exploring analytic and clinical validity and utility, as well as the ethical, legal, and social implications of sequencing via multidisciplinary approaches; it has recruited 5,577 participants across a spectrum of symptomatic and healthy children and adults by utilizing both germline and cancer sequencing.