Distributed and Multiphase Inference in Theory and Practice
Subtitle: Principles, Modeling, and Computation for High-Throughput Science
Contributors: Meng, Xiao-Li; Airoldi, Edoardo M.; Liu, Jun S.
Published: 2013
Language: eng
Description: The rise of high-throughput scientific experimentation and data collection has introduced new classes of statistical and computational challenges. The technologies driving this data explosion are subject to complex new forms of measurement error, requiring sophisticated statistical approaches. Simultaneously, statistical computing must adapt to larger volumes of data and new computational environments, particularly parallel and distributed settings. This dissertation presents several computational and theoretical contributions to these challenges.
Notes: Keywords: High-throughput biology, Massive data, Nucleosomes, Preprocessing, Proteomics, Statistical principles.

Thesis Ph.D. Harvard University 2013