Martin - Manon

: An R package designed for the linear modeling of high-dimensional designed data based on the ASCA/APCA family.

Manon Martin, PhD Primary Institution: UCLouvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA) 1. Core Research Objective

Below is a structured "paper" summarizing the core pillars of her scientific contributions and research focus. manon martin

Manon Martin is a prominent researcher at the , specializing in biostatistics and the analysis of high-dimensional "omics" data. Her work primarily focuses on developing statistical frameworks and software to interpret complex experimental designs in fields like metabolomics and peptidomics.

: In the field of single-cell proteomics, she contributed to scplainer , a tool using linear models to understand variation in mass spectrometry-generated peptidomics data. 3. Software Development : An R package designed for the linear

While her focus is statistical, her work is applied across diverse scientific areas:

The primary goal of Martin’s research is to bridge the gap between complex experimental designs (e.g., multifactorial, longitudinal, or unbalanced designs) and the analysis of high-dimensional data, such as NMR spectra or mass spectrometry. She develops methods that allow scientists to extract meaningful biological insights from data that would otherwise be confounded by noise or complex variables. Manon Martin is a prominent researcher at the

: She has authored accessible guides on Linear Regression, ANOVA, and Linear Mixed Models tailored specifically for chemists and life-science researchers. 4. Application Domains