(photo credit: Rachel Marquez)
My name is Brendan, a Post-doctoral Research Fellow working with Prof. Jean Fan in the Department of Biomedical Engineering and Center for Computational Biology at Johns Hopkins University (JHU). Here, I have been developing open-source computational pipelines and statistical software to characterize and visualize cell type spatial organizational patterns in tissues. Two of my projects are now published and available as downloadable software (MERINGUE and STdeconvolve), which you can check out below in my Featured Projects. I have worked with a LOT of different types of Spatial Transcriptomics datasets and technologies, as well as single-cell data to help annotate and characterize different spatial patterns in tissues.
I earned my PhD from Johns Hopkins University in March 2020 where I was part of the Cellular, Molecular, Developmental Biology and Biophysics Department and a member of the Graduate Partnership Program between the National Institutes of Health (NIH) and JHU. This meant that I had the opportunity to receive part of my training at JHU and also perform my thesis work at the NIH. This was done under the guidance of Dr. Laura Elnitski in the National Human Genome Research Institute.
During my PhD I developed cancer detection assays based on patterns of DNA methylation in circulating cell-free DNA from blood plasma samples (aka liquid biopsies). During this time, I optimized a single molecule detection assay to quantify rare fragments of methylated cell-free DNA in patient plasma. I further developed computational machine learning algorithms leveraging heterogeneous methylation patterns to optimize liquid biopsy cancer diagnostics.
My foundational training has been in Molecular Biology and Biochemistry but during the last 10 years I have been learning to leverage this knowledge through code. Looking forward, I'm excited to integrate my foundational training as a wet lab biologist with computational strategies to help solve fundamental problems in health and disease!
