Chad M. Schafer

TL;DR: Using exome sequencing, it is shown that analysis of rare coding variation in 3,871 autism cases and 9,937 ancestry-matched or parental controls implicates 22 autosomal genes at a false discovery rate of < 0.05, plus a set of 107 genes strongly enriched for those likely to affect risk (FDR < 0.30).

TL;DR: Results from de novo events and a large parallel case–control study provide strong evidence in favour of CHD8 and KATNAL2 as genuine autism risk factors and support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5- to 20-fold.

TL;DR: Approximate Bayesian computation (ABC) methods are presented and discussed in the context of supernova cosmology using data from the SDSS-II Supernova Survey and it is demonstrated that ABC can recover an accurate posterior distribution.

TL;DR: FOAM's coupling strategy was chosen for high throughput (simulated years per day) and a new coupler was written for FOAM and some modifications were required of the component models.

TL;DR: In this article, a semi-supervised method for photometric supernova typing was proposed, which used the nonlinear dimension reduction technique diffusion map to detect structure in a data base of supernova light curves and subsequently employed random forest classification on a spectroscopically confirmed training set to learn a model that can predict the type of each newly observed supernova.