Hello, my name is Mialy (my-lee), I’m a Floridian by birth, a Californian at heart, Seattle based.
I am one of those whose career trajectory follows more of a zig-zag than a straight line. I did my bachelors (in Microbiology) at the University of Florida (Go Gators!) before moving to upstate NY to do my masters in biology at the University of Rochester (Go ??? — lol I don’t think they’re known for their sports). I then moved out to the Bay Area and began working at Stanford University (Go Trees, lol) as a research assistant. After working for a couple years, I decided to go back for my Ph.D. in Bioengineering and graduated in March 2021, with a truly ironic number of references to trees in my defense.
Throughout my time in research, I adapted from being a pure experimentalist, to spending the majority of my time doing modeling and data analysis. My work has challenged me in amazing and unexpected ways — to learn how to solder together an LED board to stimulate my optogenetic cells, learning to code (Matlab then Python) to analyze my imaging data, to using version control (git) for larger group projects (the E. coli whole cell project), and learning how to make and image on microfluidic devices (hello mother machine!).
I am currently Tech Lead on FAIR Data (Findable, Accessible, Interoperable, Reusable) front and back end products (Schematic, Data Curator App, and Data Flow Apps) at Sage Bionetworks. The mission of Sage is “to drive a new age of discovery through truly open science and radical collaboration”. To this end, our tools from FAIR Data, enable data sharing and collaboration among large research projects by allowing easy data modeling (using a CSV interface), metadata validation and ingress. Our goal is to make products that are scalable, reusable, and generalizable to be used across many projects.
I am particularly passionate about making our products easy to understand and use for non-technical users. To this end, we have created a schema visualization tool (used by a stakeholder here), to help users understand the underlying structure of their model, and help aid data model development and communication. Additionally, I also love working directly with stakeholders, to capture their user stories and develop solutions that will address their unique needs.
Education
2015- 2021
Ph.D. Bioengineering, Stanford University, Stanford, California
My thesis work, in Markus Covert's lab, was an experimental and computational exploration of the role of operon structure in ensuring the co-expression of sub-generationally expressed genes. I worked with both the the whole-cell modeling and live-cell imaging teams in the lab.
2009-2012
M.S. in Biology, University of Rochester, Rochester, New York
My research within the Culver lab consisted of determining the roles of cis- and trans- acting factors involved in 30S small subunit biogenesis. To study the role of the externally and internally transcribed regions of 16S rRNA I developed a screen and selection system, to easily determine nucleotides within these regions that can affect 30S formation. In addition, I studied the role that RimP, a ribosome biogenesis factor, plays in the formation of a mature ribosomal particle.
2005-2008
B.S. in Microbiology and Cell Science, University of Florida, Gainesville, Florida
Work Experience
Feb 2024-Present
Senior Research Software Engineer, Sage Bionetworks
Jun 2021 - Feb 2024
Research Software Engineer, Sage Bionetworks
At Sage Bionetworks I work as Tech Lead on FAIR data front and back end products (Schematic, Data Curator App, and Data Flow Apps). Our tools enable data sharing and collaboration among large research projects by allowing easy data modeling (using a CSV interface), metadata validation and ingress. Our goal is to make products that are scalable, reusable, and generalizable to be used across many projects.
April 2020-Nov 2021
Mathematical Modeling Extern, BridgeBio
Worked to make computational models of drug target pathways, for portfolio drugs.
Nov 2019-Aug 2021
Consultant, Evil Genius Llc.
Probe IBM Watson Treatment Pathways data sets to discover insights and provide interactive and animated data visualizations for communication with investors.
2013-2015
Research Assistant, Stanford University, Covert Lab
My project focused on understanding the role of NF-kB dynamics in single cells in response to stimuli.
Skills
Computational
Python
Pandas/Numpy
Data Modeling
Data Analysis
SQL
Networkx
Version Control (Git)
Unit Testing
Data Visualization (observable, D3, seaborn, matplolib, bokeh…)
Bash Scripting
Image Analysis
GoogleCloud
Experimental
Live single-cell microscopy (E. coli, mammalian cells)
Mother machine
Cloning (E. coli, mammalian)
Tissue Culture
RNA Sequencing
sm-RNA FISH, immuno-histo chemistry
Papers
Sun, Gwanggyu*, DeFelice, Mialy* Gillies, Taryn & Ahn-Horst, Travis & Andrews, Cecelia & Krummenacker, Markus & Karp, Peter & Morrison, Jerry & Covert, Markus. (2024). Cross-evaluation of E. coli’s operon structures via a whole-cell model suggests alternative cellular benefits for low- versus high-expressing operons. Cell Systems. 15. 10.1016/j.cels.2024.02.002.
Derek N. Macklin*, Travis A. Ahn-Horst*, Heejo Choi*, Nicholas A. Ruggero*, Javier Carrera*, John C. Mason*, Gwanggyu Sun, Eran Agmon, Mialy M. DeFelice, Inbal Maayan, Keara Lane, Ryan K. Spangler, Taryn E. Gillies, Morgan L. Paull, Sajia Akhter, Samuel R. Bray, Daniel S. Weaver, Ingrid M. Keseler, Peter D. Karp, Jerry H. Morrison, Markus W. Covert†*"Simultaneous cross-evaluation of heterogeneous E. coli datasets via mechanistic simulation"*. 24 July 2020, Science 369, eaav3751. DOI: 10.1126/science.aav3751
DeFelice, M.*, Clark, H.*, Hughey, J.*, Maayan, I., Kudo, T., Gutschow, M., Covert, M., and Regot, S. "NF-κB signaling dynamics is controlled by a dose-sensing autoregulatory loop". Science Signaling 12, April 30, 2019. eaau3568. DOI: 10.1126/scisignal.aau3568
Lane K*, Van Valen D*, DeFelice MM, Macklin DN, Kudo T, Jaimovich A, Carr A, Meyer T, Pe'er D, Boutet SC, Covert MW, "Measuring signaling and RNA-Seq in the same cell links gene expression to dynamic patterns of NF-kappa B activation". Cell Systems. April 26, 2017. doi: 10.1016/j.cels. 2017.03.010
Van Valen D, Kudo T, Lane K, Macklin DN, Quach N, DeFelice M, Maayan I, Tanouchi Y, Ashley E, Covert MW, "Deep learning automates the quantitative analysis of individual cells in live-cell imaging experiments". PLOS Computational Biology. November 4, 2016. doi: 10.1371/journal.pcbi.1005177
*Authors contributed equally
Fellowships/Awards
Sibel Scholars Fellowship Class of 2020
McKinsey Stanford Case Competition—3rd Place 2016
Presentations/Posters
April 2019 Stanford Bug Club Seminar -- Talk
“Is operon Structure required for co-expression of sub-generationally expressed genes?”
March 2019 The Paul G. Allen Frontiers Group Site Visit, Allen Discovery Center at Stanford University -- Poster session
“Why do operons persist? Making the case that operon structure enables bet-bet-heating for population survival in fluctuating environments”
January 2019 Gordon Research Conference, Ventura, CA. Stochastic Physics in Biology -- Poster Session
“Why do operons persist? Making the case that operon structure enables bet-bet-heating for population survival in fluctuating environments”
October 2018 Stanford Bioengineering Department Retreat -- Poster Session
“Why do operons persist? Making the case that operon structure enables bet-bet-heating for population survival in fluctuating environments”
May 2018 Stanford Center for Systems Biology Weekly Meeting -- Talk
“Why do operons persist? Making the case that operon structure enables bet-bet-heating for population survival in fluctuating environments”
February 2017 Stanford Bioengineering Department Retreat -- Poster Session
“Exploring the role of acute tolerance in NF-κB signaling dynamics”