About Me
Hello! I am an MD-PhD candidate at Johns Hopkins University. I am interested in systems biology and data science and how computational and mathematical methods can be used to understand complexity in disease. I have completed my PhD in Biomedical Engineering in the JEFworks lab. My PhD work focused on developing computational methods for spatial transcriptomics analysis to understand how cells are spatially organized within tissues and how this changes in disease settings. I am excited to build on this work by developing methods to combine high-dimensional molecular data with high-resolution physiologic data to understand the biological mechanisms driving clinical heterogenity in critical illness.
Projects, Publications, and Software
You can find more details about my work here. Below, are a some highlights:
- Gene count normalization in single-cell imaging-based spatially resolved transcriptomics. Genome Research 2024.
- VeloViz: RNA-velocity informed low dimensional embeddings of single cell transcriptomics data. Bioinformatics 2021. Software + tutorials.
- Computational challenges and opportunities in spatially resolved transcriptomic data analysis. Nature Communications 2021.
- Interactions between cancer cells and immune cells drive transitions to mesenchymal-like states in glioblastoma. Cancer Cell 2021.
- Soluble PD-L1 reprograms blood monocytes to prevent cerebral edema and facilitate recovery after ischemic stroke. Brain, Behavior, and Immunity 2024.
Other Interests
Outside of research and clinical training, I am interested in data science education and medical education and in my free time, I like to read, sew, go to art and history museums, and take photographs
Get in touch
Twitter 
Email: lylaatta [at] jhmi [dot] edu
