Noah Legall

Biography

I am a computational microbiologist that works at the intersection of dry and wet lab methodologies in studying microalgae and microbial interactions. Through targeted co-culture and microbiome experimentation, I hope to understand the molecular and metabolic signatures associated with mutualistic, commensal, and antagonistic interactions between members of a microbial community. The ultimate goal of this research is to develop predictive models and methods to assist in the development of microalgae synthetic microbiomes that provide cost saving and biological enhancement to cultivation. I started my scientific career doing molecular biology bioinformatic research while obtaining my Bachelor of Science in Quantitative Biology at the University of North Carolina, Chapel Hill and then continued onwards to the University of Georgia to receive my PhD in Bioinformatics studying bacterial pathogenic livestock diseases. 

Work Experience

• January 2023 Intelligence Community Postdoctoral Fellowship
  University of South Florida – Tampa, Florida
  Project: Merging multi-omics and bacterial genomics to predict antagonistic microbiome interactions
  
  
• June 2022 – September 2022 Bioinformatics Intern
  Illumina, Inc. – San Diego, California
  Project: Investigation of Infinium BeadChip efficiency as Males Age (aka Old Man Syndrome).
  Skills Learned: Snowflake, Statistical Inference, Machine Learning, Genome Wide Association Studies
  
  
• June 2018 – Mar 2023 Graduate Research Assistant
  Institute of Bioinformatics, University of Georgia, Georgia
  Project: Genomic factors leading to host range in Mycobacterium bovis
  Skills Learned: Bioconda, HPC computing, Github, NGS Big Data, Nextflow
• Fall 2014 – Spring 2018  Undergraduate Researcher
  School of Medicine Biochemistry and Biophysics, University North Carolina - Chapel Hill, North Carolina
  Project: Bioinformatics analysis of non-coding circRNA intronic regions.
  Skills Learned: Perl, Python, R. 

Publications

• Legall N and Salvador LCM (2022) Selective sweep sites and SNP dense regions differentiate Mycobacterium bovis isolates across scales. Front. Microbiol. 13:787856. doi: 10.3389/fmicb.2022.787856
• Duan, N., Bai, Y., Sun, H., Wang, N., Ma, Y., Li, M., Legall, N., … Chen, X. (2017). Genome re-sequencing reveals the history of apple and supports a two-stage model for fruit enlargement. Nature Communications, 8(1), 249. https://doi.org/10.1038/s41467-017-00336-7. Contributions included SNP identification and phylogenetic comparison of the Ma1 gene locus of domesticated apple genome.