David C. Page

TL;DR: A genome-wide catalog of coding variation in the mouse genome was developed using an extensive collection of mouse DNA sequence reads, including those recently released by Celera, data from dbSNP 2 and resequencing data generated by Perlegen Sciences for the US National Institute of Environmental Health Sciences (NIEHS).

TL;DR: The writer really shows how the simple words can maximize how the impression of this book is uttered directly for the readers.

TL;DR: It is found that mammographic findings had a higher discriminative ability than genetic variants for improving breast cancer risk prediction in terms of the area under the ROC curve.

TL;DR: In total, DAZL orchestrates a broad translational program that amplifies protein levels of key spermatogonial and gene regulatory factors to promote the expansion and differentiation of progenitor sperMatogonia.

TL;DR: This work proposes the concept of a feature relevance network, a binary Markov random field to represent the relevance of each individual feature by potentials on the nodes, and represent the correlation structure by potentialS on the edges, and shows its superior performance over common feature selection methods in terms of prediction error and recovery of the truly relevant features on real-world data and synthetic data.