Challenges of big data analysis

J Fan, F Han, H Liu - National science review, 2014‏ - academic.oup.com
Big Data bring new opportunities to modern society and challenges to data scientists. On the
one hand, Big Data hold great promises for discovering subtle population patterns and …

A review of metabolomics approaches and their application in identifying causal pathways of childhood asthma

KN Turi, L Romick-Rosendale, KK Ryckman… - Journal of Allergy and …, 2018‏ - Elsevier
Because asthma is a disease that results from host-environment interactions, an approach
that allows assessment of the effect of the environment on the host is needed to understand …

Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer

CM Phelan, KB Kuchenbaecker, JP Tyrer, SP Kar… - Nature …, 2017‏ - nature.com
To identify common alleles associated with different histotypes of epithelial ovarian cancer
(EOC), we pooled data from multiple genome-wide genoty** projects totaling 25,509 EOC …

Process data analytics in the era of big data

SJ Qin - AIChE Journal, 2014‏ - scholars.ln.edu.hk
For engineering systems where processes, units, and equipment are designed with clear
objectives and are usually operated under well‐controlled circumstances as designed …

A Unified Framework for High-Dimensional Analysis of -Estimators with Decomposable Regularizers

SN Negahban, P Ravikumar, MJ Wainwright, B Yu - 2012‏ - projecteuclid.org
A Unified Framework for High-Dimensional Analysis of M-Estimators with Decomposable
Regularizers Page 1 Statistical Science 2012, Vol. 27, No. 4, 538–557 DOI: 10.1214/12-STS400 …

Bayesian inference for structured additive regression models for large-scale problems with applications to medical imaging

P Schmidt - 2017‏ - edoc.ub.uni-muenchen.de
In der angewandten Statistik können Regressionsmodelle mit hochdimensionalen
Koeffizienten auftreten, die sich nicht mit gewöhnlichen Computersystemen schätzen …

Statistical challenges of high-dimensional data

IM Johnstone, DM Titterington - … transactions of the …, 2009‏ - royalsocietypublishing.org
Modern applications of statistical theory and methods can involve extremely large datasets,
often with huge numbers of measurements on each of a comparatively small number of …

A unified framework for high-dimensional analysis of -estimators with decomposable regularizers

S Negahban, B Yu, MJ Wainwright… - Advances in neural …, 2009‏ - proceedings.neurips.cc
The estimation of high-dimensional parametric models requires imposing some structure on
the models, for instance that they be sparse, or that matrix structured parameters have low …

Exploring massive, genome scale datasets with the GenometriCorr package

A Favorov, L Mularoni, LM Cope… - PLoS computational …, 2012‏ - journals.plos.org
We have created a statistically grounded tool for determining the correlation of genomewide
data with other datasets or known biological features, intended to guide biological …

A new link between diabetes and cancer: enhanced WNT/β-catenin signaling by high glucose

C García-Jiménez, JM García-Martínez… - Journal of …, 2014‏ - jme.bioscientifica.com
Extensive epidemiological studies suggest that the diabetic population is at higher risk of
site-specific cancers. The diabetes–cancer link has been hypothesized to rely on various …