Experienced informatics researcher and doctor-in-training with a demonstrated history of working in research. Skilled in Python, Computer Programming, Algorithm Design and Optimization, Machine Learning, Metabolomics and Biochemistry. Strong academic background with a PhD in Biochemistry / Bioinformatics and over 10 years of experience working in a successful bioinformatics lab as a software developer and researcher.
University of Kentucky
PhD Molecular and Cellular Biochemistry (May 2019)
Dissertation: “Computational Tools for the Untargeted Assignment of FT-MS Metabolomics Datasets”
Advisor: Dr. Hunter N.B. Moseley
University of Louisville
I develop computational tools to aid in the analysis of large metabolomics datasets gathered on ultra-high resolution mass spectrometers. These instruments generate large datasets that are difficult to utilize in a meaningful and unbiased manner, especially on a large scale. Sometimes these datasets are collected using techniques such as stable-isotope tracing or chemoselective derivatization further complicating this problem.
I developed algorithms to aid in the assignment of these datasets (i.e. mapping spectral features to molecular formulas) that is compatible with stable isotope tracing as well as tools to remove artifacts from this data. I also utilized machine learning algorithms to classify my assignments into metabolite classes with which differential abundance analysis can be performed.
I also am interested in applying graph-theory to the modeling of chemical structures.
• Mitchell JM, Flight RM, Moseley HN 2019. “Clinical Implication of Differential Lipid Expression in NSCLC” In Preparation
• Mitchell JM, Moseley HN 2019. “Deriving Accurate Lipid Classification based on Molecular Formula” Bioarxiv (preprint) doi: https://doi.org/10.1101/572883, submitted to Metabolites (2020)
• Mitchell JM, Flight RM, Moseley HN 2019. “Small Molecular Isotope Resolved Formula Enumerator (SMIRFE): a tool for truly untargeted metabolomics analysis of metabolites detected by Fourier transform mass spectrometry” Analytical Chemistry doi: https://doi.org/10.1021/acs.analchem.9b00748
• Trainor PJ, Mitchell JM, Carlisle SM, Moseley HN, DeFilippis AP, Rai SN 2018. “Inferring metabolite interactomes via molecular structure informed Bayesian graphical model selection with an application to coronary artery disease” Bioarxiv (preprint) doi: http://dx.doi.org/10.1101/386409
• Mitchell JM, Flight RM, Wang QJ, Higashi RM, Fan TW, Lane AN, Moseley HN 2018. “New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis”. Metabolomics 14: 125 doi: https://doi.org/10.1007/s1136-018-1426-9
• Mitchell JM, Fan TW, Lane AN, Moseley HN 2014. “Development and in silico Evaluation of Large-Scale Metabolite Identification Methods using Functional Group Detection for Metabolomics”. Frontier in Genetics 5:237. Doi: 10.3389/fgene2014.00237
• Jones James, Suraj Kannan and Joshua Mitchell 2013. “Dynamic Scheduling of White Water Rafting”. Harvard College Mathematics Review 6.1: 96-112 Web 13 July 2013
• Moseley HN, Carreer WJ, Mitchell JM, Flight RM 2016 “Method and System for Identication of Metabolites” U.S. Provisional No. 62/187,901. Published Jan 2018