Yuanyue Li

Yuanyue Li
李渊越

Bioinformatics Scientist

University of California, Davis

👋 Hello

I am Yuanyue Li, a bioinformatics scientist with a passion for understanding the molecular mechanisms of life by combining experimental and computational methods. I hope my research can help to answer those questions: 1) How many different molecules are there in a cell? 2) How do they interact with each other? 3) How do they work together to make a cell functional?

Mass spectrometry is a powerful tool for measuring molecules with high sensitivity and accuracy. Therefore, I use mass spectrometry as my primary tool to measure molecules. I have developed serval methods to maximize the capabilities of mass spectrometry in life science research. Feel free to visit my GitHub page to try out the tools I’ve developed.

I grew up and received my doctoral degree in China, then enjoyed three years of postdoctoral training in Germany, and I am currently working in the United States. In my spare time, I enjoy exploring the world with my wife and our two daughters.

Interests
  • Mass Spectrometry
  • Metabolomics
  • Proteomics
  • Molecular Biology
Education
  • Ph.D. in Biochemistry and Molecular Biology, 2014

    Xiamen University

  • B.Sc. in Life Science, 2008

    Xiamen University

Featured Projects

Spectral Entropy & Entropy Similarity
By considering an MS/MS spectrum as a probability distribution, we introduced the concept of Spectral Entropy to evaluate the information within the spectrum. Expanding on this idea, we proposed Entropy Similarity as a metric to measure the similarity between two spectra. Utilizing this approach can lead to a reduction in the false positive rate for metabolite identification by up to 40%.
A video introduction to Spectral Entropy and Entropy Similarity can be found here.
Group-DIA
Group-DIA can analyze multiple DIA data files simultaneously, notably enhancing protein identification by grouping various mass spectrometry datasets.

Recent Publications

(2021). Spectral entropy outperforms MS/MS dot product similarity for small-molecule compound identification. Nature Methods.

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(2021). Coupling proteomics and metabolomics for the unsupervised identification of protein–metabolite interactions in Chaetomium thermophilum. PLOS ONE.

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(2015). Group-DIA: analyzing multiple data-independent acquisition mass spectrometry data files. Nature Methods.

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