Kernel approaches for differential expression analysis of mass spectrometry-based metabolomics data

Incorporating auxiliary information for improved prediction using combination of kernel machines

(2015) Xiang Zhan et al.   Statistical Methodology

Stronger findings for metabolomics through Bayesian modeling of multiple peaks and compound correlations

(2014) T. Suvitaival et al.   BIOINFORMATICS

Stronger findings from mass spectral data through multi-peak modeling

(2014) Tommi Suvitaival et al.   BMC BIOINFORMATICS

MetaboLyzer: A Novel Statistical Workflow for Analyzing Postprocessed LC–MS Metabolomics Data

(2013) Tytus D. Mak et al.   ANALYTICAL CHEMISTRY

A hybrid approach to protein differential expression in mass spectrometry-based proteomics

(2012) Xuan Wang et al.   BIOINFORMATICS

Strictly Positive-Definite Spike Train Kernels for Point-Process Divergences

(2012) Il Memming Park et al.   NEURAL COMPUTATION

Aberrant Lipid Metabolism in Hepatocellular Carcinoma Revealed by Plasma Metabolomics and Lipid Profiling

(2011) A. D. Patterson et al.   CANCER RESEARCH

Powerful SNP-Set Analysis for Case-Control Genome-wide Association Studies

(2010) Michael C. Wu et al.   AMERICAN JOURNAL OF HUMAN GENETICS

A statistical framework for protein quantitation in bottom-up MS-based proteomics

(2009) Yuliya Karpievitch et al.   BIOINFORMATICS

Two-way analysis of high-dimensional collinear data

(2009) Ilkka Huopaniemi et al.   DATA MINING AND KNOWLEDGE DISCOVERY

Estimation and testing for the effect of a genetic pathway on a disease outcome using logistic kernel machine regression via logistic mixed models

(2008) Dawei Liu et al.   BMC BIOINFORMATICS