⚛️

Shunyang Wang

Machine Learning and Computational Chemistry Scientist

Genentech

👋 Hi, there! I’m Shunyang, a computational scientist at Genentech.

Check out my resumé and portfolio below

Recent Posts

Run a Free Local LLM and Share It with Your Family and Friends in 4 Hours

This tutorial guides you through setting up a local DeepSeek-R1 model with Open WebUI, ZeroTier, and Docker on Windows using an NVIDIA RTX 3090.

Last updated on Jan 30, 2025

Dissertation: Theoretical and experimental explorations on compound identification in metabolomics

Chapter 1-4 describes computational studies, using molecular dynamics, on in-silico mass spectra of small molecules generation. Chapter 5 provides another routine from experimental side to help unknown metabolites identification with methane chemical ionization and quadrupole-time of flight mass spectrometry.

Dissertation: Theoretical and experimental explorations on compound identification in metabolomics

Gas chromatography with methane chemical ionization and quadrupole-time of flight mass spectrometry obtains molecular ion species to automatically assign elemental formulas

We tested methane chemical ionization on 367 trimethylsilylated (TMS) derivatized metabolites using quadrupole time-of-flight detector (QTOF). We developed an algorithm to automatically detect molecular ion species and tested SIRIUS software on how accurate the determination of molecular formulas.

Gas chromatography with methane chemical ionization and quadrupole-time of flight mass spectrometry obtains molecular ion species to automatically assign elemental formulas

Predicting Electron Ionization Mass Spectra Using Excited-State Molecular Dynamics

We provide an algorithm that introduces excited states into the molecular dynamics prediction of the 70 eV electron ionization mass spectra. We recommend adding excited-state calculations for predicting the electron ionization mass spectra of small molecules in metabolomics.

Quantum Chemical Prediction of Electron Ionization Mass Spectra of Trimethylsilylated Metabolites

We chose 816 trimethylsilyl derivatives of organic acids, alcohols, amides, amines, and thiols to compare in silico-generated spectra against the experimental EI mass spectra from the NIST17 library, suggesting that QCEIMS methods can be extended to compounds that are not present in experimental databases.

Quantum Chemical Prediction of Electron Ionization Mass Spectra of Trimethylsilylated Metabolites

Quantum Chemistry Calculations for Metabolomics

We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.

Quantum Chemistry Calculations for Metabolomics

Predicting in silico electron ionization mass spectra using quantum chemistry

We test quantum chemistry methods to generate in silico EI mass spectra by combining molecular dynamics with statistical methods.

Predicting in silico electron ionization mass spectra using quantum chemistry