Michael T. Judge

About Me:

I am developing hardware and software tools to enable benchtop NMR as a process analytical technology in biomanufacturing. My background is in molecular biology (Appalachian State University), genetics (University of Georgia, Athens), and computational biology (Imperial College London). I am funded under the National Research Council Post-Doctoral Fellowship. 

Recent Publications:

Yan, Y., Judge, M.T., Athersuch, T., Xiang, Y., Liu, Z., Jimenez, B., Ebbels, T.M. 2024. Resolution Enhancement of Metabolomic J-Res NMR Spectra Using Deep Learning. Anal. Chem. https://pubs.acs.org/doi/10.1021/acs.analchem.4c00563 

Judge, M.T. and Ebbels, T.M.D. 2022. Problems, principles and progress in computational annotation of NMR metabolomics data. Metabolomics 18, 102 (2022). https://doi.org/10.1007/s11306-022-01962-z *invited review

Wu, Y., Judge, M.T., Edison, A.S., Arnold, J. 2022. Uncovering in vivo biochemical networks from time-series metabolic dynamics. PLOS ONE 17(5): e0268394. https://doi.org/10.1371/journal.pone.0268394 

Edison, A.S., Colonna, M; Gouveia, G.J., Holderman, N.R., Judge, M.T., Shen, X., Zhang, S. 2020. NMR: Unique Strengths That Enhance Modern Metabolomics Research. Anal. Chem. Article ASAP. https://pubs.acs.org/doi/10.1021/acs.analchem.0c04414 

Wu, Y., Judge, M.T., Arnold, J., Bhandarkar, S., Edison, A.S. 2020. RTExtract: Time-series NMR spectra quantification based on 3D surface ridge tracking. Bioinformatics, Vol 36 20:5068–5075. https://doi.org/10.1093/bioinformatics/btaa631

Sheikh M.O., Tayyari F., Zhang S., Judge M.T., Weatherly D.B., Ponce F.V., Wells L., Edison A.S. 2019. Correlations Between LC-MS/MS-Detected Glycomics and NMR-Detected Metabolomics in Caenorhabditis elegans Development. Front. Mol. Biosci. 6:xx-xx. https://www.frontiersin.org/article/10.3389/fmolb.2019.00049 

Judge, M.T., Wu, Y., Tayyari, F., Hattori, A., Glushka, J., Ito, T., Arnold, J., & Edison, A.S. 2019. Continuous in vivo metabolism by NMR. Front. Mol. Biosci. 6:xx-xx. https://www.frontiersin.org/articles/10.3389/fmolb.2019.00026/full