Aaron N. Brooks Ph.D
        
å aaron.neil.brooks@gmail.com | S www.aaronbrooks.info | E scalefreegan | D aaron-n-brooks | œ Google Scholar
Scientist and leader with a track record of transforming data into insight using machine learning. I build tools, processes and teams to
structure, integrate and distill biological data into formats for stakeholders to make eective decisions.

  Python, R
  scikit-learn, PyTorch, Hydra
  DNA/RNA-Seq, multi-omics, genome assembly
 AWS, GCP
  SQL, NoSQL (ArangoDB, MongoDB), Neo4j
  Dash, Django, Shiny
  git, Docker
  Snakemake, Nextflow
  Jira, Confluence
 German (A2), Spanish

   Boston, Massachusetts (Remote)
    Jan. 2022 -present
• Leading a team that innovates approaches to curation, characterization and communication of information about best-in-class genetic parts.
Outcome: Curated 229 DNA parts across 6 organisms yielding part sets with tunable expression and up to 30-fold increases in expression levels.
• Founded and developed a high-performing team to meet increasing business demands. Developed and implemented Agile processes and a
support service architecture (Jira) to execute on external requests and internal projects eectively.
• Prototyped AI-assisted knowledge management systems, including retrieval augmented generation (RAG) and other embedding approaches.
• Predicted DNA synthesizability using machine learning (gradient boosting, random forest, logistic regression).
• Fine-tuned a DNA foundation model (HyenaDNA) for multiple, application-specific tasks, including regression and classification.
  Boulder, Colorado (Remote)
    Dec. 2020 - Dec. 2022
• Developed statistical and analytical soware for interpretation of highly-multiplexed selection experiments with CRISPR-engineered cell li-
braries. Outcome: 3 publications and 3 patent applications.
• Designed and implemented an interactive web service for submitting deep mutational scanning data for analysis and visualization (Dash).
• Supported interpretation of pooled selection experiments for external customers. Distilled complex data into actionable insights.
• Designed DNA libraries (promoter insertion) leveraging a pre-trained convolutional neural network (CNN).
• Led implementation of ETL processes for generation and querying of Knowledge Graphs.
       Heidelberg, Germany
  Jun. 2015 - Nov. 2020
• Established a synthetic biology research subgroup, directed day-to-day research activities and secured funding. Outcome: 1.4M Euro funding,
4 publications in top journals, including Science and Cell, and 1 patent application.
• Collected and analyzed hundreds of millions of Nanopore direct RNA sequencing reads on more than 60 highly-rearranged synthetic yeast
genomes.
• Wrote a semi-automated analysis pipeline (Snakemake) to perform all steps in a sequencing workflow on HPC infrastructure, from basecalling
to transcript quantification. Used this pipeline to process terabytes of sequencing data.
• Applied machine learning (gradient boosting) to disentangle multiple factors influencing transcript start and end sites in S. cerevisiae.
     
        

Cell
            
          
            
2023
       
       
 
Cell
            
             
 
2023
         

Nature Communications
        2023
          
   
mSystems
           

2022
         Science
           2022
• ”Understanding genomes, piece by piece.” EurekAlert.
• ”Wie die Platzierung eines Gens seine Expression beeinflusst.” Nach Welt.
        
 
bioRxiv
             
     
2021
       PLoS Biol
        2019
     Cell Systems
      2016
         Front. Microbiol.
         2015
         

BMC Systems Biology
                2014
      Front. Microbiol.
        

2014
       Mol Syst Biol.
               2014
• ”New Open-Access Multiscale Model Captures Dynamic Molecular Processes in Unprecedented Detail.” ISB Molecular Me.
      Wiley Interdiscip Rev Syst Biol Med.
         2011

        2024
   
       
     
   
2023

        2022


   Seattle. WA
      Sep. 2008 - Aug. 2014
• Developed an ensemble learning approach to predict gene regulatory networks from microarray data
• Full-stack implementation of web service (Django) that enables model access and exploration: http://egrin2.systemsbiology.net
• Nominated for UW Distinguished Dissertation Award
    Albuquerque, NM
        Aug. 2002 - Aug. 2007
• Characterized interactions of cytoplasmic poly(A)binding protein with poly(A) RNA using transmission electron microscopy
• Robert B. Lofield Award for outstanding thesis in biochemistry
• Graduated summa cum laude and with general university honors
• Regents’ scholarship (highest awarded by the University)
• Minor: Philosophy
 

       
Heidelberg,
Germany

         Seattle, WA
       Seattle, WA
           Albuquerque, NM
         Albuquerque, NM
       Albuquerque, NM
      Rio Rancho, NM
 
         Ľ  Ì New York, USA
     S  Ì London, UK
          Ľ  Ì Sydney, AU
         Ľ  Ì Edinburgh, UK
  
      EMBL Heidelberg
 2019
          EMBL Heidelberg
 2018
      EMBL Heidelberg
  2015
• Teaching materials: http://scalefreegan.github.io/Teaching/DataIntegration/
       
     Washington, DC
   2014
• Designed and facilitated a hands-on activity and web-based game to understand the structure and function of networks. Over 300 students
have played the online game.
• ”Knowing Networks”. NIH NIGMS Inside Life Science.
• ”ISB at USA Science and Engineering Festival”. ISB Molecular Me.
• ”USA Science and Engineering Festival”. ISB Molecular Me.
       Seattle, WA
 2010
       