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    Hello!

    My name is Gonçalo, I'm a Senior Research Associate at Cornell University in the Boyce Thompson Institue.

    Im currently working with the Schroeder and Gomes labs developing AI tools for metabolite identification.

    My research lies at the intersection of metabolomics, data science, analytical chemistry, and artificial intelligence to dissect disease, environmental factors, and eco-evolutionary pressures across species from microbes to humans.

  • Research Interests

    Chemical structure elucidation of unknown metabolites and confident spectral annotation of metabolomics data is challenging and requires the integration of multiple data streams. Yet, robust computational capabilities are still lacking. My research interests lie in developing holistic strategies that take advantage of classical biochemistry experiments, novel experimental designs, analytical platforms, biological materials, and computational methods to facilitate the discovery and identification of metabolites. This is critical for the successful translation of metabolomics outcomes and advancement of biological discovery. In addition, I am a trained Drugs and Toxicology Forensic Scientist. Prior to my graduate education, I specialized in analytical chemistry method development and the implementation of quality control and assurance practices in targeted high-throughput analysis. These much-needed practices play a critical role in metabolomics research, ensuring reproducibility and public confidence in metabolomics outputs.

  • Analytical Chemistry

    Metabolomics

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    NMR

    Both at NIST and UGA I worked with a range of NMR , from benchtop to 900MHz and high-resolution-magic angle spinning.

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    Mass spectrometry

    As a forensic scientist GC-MS was the go-to analytical platform: high-throughput, low maintence and targeted.

    For untargeted metabolomics LC-MS is the prefered technology.

    Both MS and NMR data are critical for de novo metabolite ID.

  • Computational

    Developing computational workflows and tools for metabolomics

    AI for MS: Molecular Formula assignment & predicting spectra from structure

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    Combining multiple analytical data streams into metabolite IDs

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    Real-time metabolite changes over a course of 2 days

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    Molecular Formula assignment algorithm using MS1 data

  • Experimental design

    QA/QC and Biological materials

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    Creating long-term Reference Materials for metabolomics

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    Classical Biochemistry integrated with metabolomics

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    Community led minimum standards

  • CV & Socials:

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    Email

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    LinkedIn