About Me

Hi there! I am a postdoctoral researcher in Fiehn Lab at the University of California, Davis.

Mass spectrometry (MS)-based metabolomics is essential for uncovering the fundamental biochemical mechanisms of biology, clinical medicine, and environmental science.

To achieve this goal, metabolomics data have to be reliable, reproducible and comparable.

My long-term research goal is to integrate analytical chemistry, instrumentation, computer science, and bioinformatics to develop innovative tools that can (1) produce high-quality MS data and (2) transform raw data into meaningful biological insights.

I have published 24 peer-reviewed papers, including 8 first-author papers. I'm excited to share that one of my latest first-author works is currently under revision at Nature Communications!

I am also the developer and maintainer of two Python packages and three R packages for metabolomics raw data processing (MassCube), experimental design (BAGO, with graphic user interface), statistical analysis (ABCstats), normalization (MAFFIN) and data visualization (tools4st).

Scientific Training

University of California, Davis, United States (2023.5 - present)

Postdoctoral researcher

Research supervisor: Prof. Oliver Fiehn

University of British Columbia, Canada (2019.5 - 2023.4)

Ph.D. in Chemistry

Research supervisor: Prof. Tao Huan

Zhejiang University, China (2014.9 - 2018.6)

B.Sc. in Chemistry (Qiushi Honors Program, Chu Kochen Honors College)

Research supervisor: Prof. Hao Li, Prof. Feihe Huang

University of Utah, United States (2017.3 - 2017.9)

Visiting scholar

Research supervisor: Prof. Peter J. Stang

Featured publications

1. MassCube

PyPI version Downloads

[In revision in Nature Communications] MassCube: a Python framework for end-to-end metabolomics data processing from raw files to phenotype classifiers.

Huaxu Yu, Jun Ding, Tong Shen, Min Liu, Yuanyue Li, Oliver Fiehn*

MassCube

2. BAGO

[Preprint] Bayesian optimization of separation gradients to maximize the performance of untargeted LC-MS.

Huaxu Yu, Puja Biswas, Elizabeth Rideout, Yankai Cao, Tao Huan*

BAGO

3. MAFFIN normalization

[Bioinformaitcs] MAFFIN: metabolomics sample normalization using maximal density fold change with high-quality metabolic features and corrected signal intensities.

Huaxu Yu, Tao Huan*

MAFFIN

4. Correction of fold change bias in nontargeted metabolomics

[Analytical Chemistry] Fold-change compression: an unexplored but correctable quantitative bias caused by nonlinear electrospray ionization responses in untargeted metabolomics.

Huaxu Yu, Shipei Xing, Lorenz Nierves, Philipp F Lange, Tao Huan*

MAFFIN

Latest News

  • MassCube has been selected for an oral presentation at the upcoming ASMS Annual Conference

    Title: MassCube: a Python framework for end-to-end metabolomics data processing from raw files to phenotype classifiers

    Conference: 73rd Conference on Mass Spectrometry and Allied Topics

    Date: 2025-06-04

  • MassCube version 1.2.1 has been released

    Meet our new version of MassCube for more accurate metabolite annotation.

    Source code: GitHub