Philip Johnson

Philip Johnson is an Associate Professor at the University of Maryland, affiliated with the Department of Biology and graduate programs in Bioinformatics, Computational Biology, and Genomics (CBBG) and Behavior, Ecology, Evolution, and Systematics (BEES). His research bridges population genetics, computational biology, and mathematical immunology to analyze large-scale genomic data.

• Education: Ph.D. in Biophysics with a focus on Computational & Genomic Biology from UC Berkeley (2009); A.B. from Harvard College (2001)

Research spans three domains: (1) adaptive immune system evolution in vertebrates and microbes, (2) ancient DNA contamination inference, and (3) mutation rate evolution in hominids and pathogens. Key projects include modeling T cell repertoire dynamics during aging and infection, studying CRISPR-Cas system ecology, and developing statistical tools for metagenomics.

Recent publications highlight his work on CRISPR immune systems (2024), Sjögren’s disease immunology (2024), and growth hormone gene duplication in birds (2023). He has contributed to ancient human genomics through collaborations on Neanderthal and Denisovan genomes.

Current students include:

• Ridwan Bello (Animal Sciences, TCR repertoire analysis)
• Arvind Jaya Shankar (CBBG, cancer-immunology interface)
• Shauna Rasband (BEES, avian genomics)
• Hao Yiu (BEES, immune system evolution)

Notable former lab members:

• Thomas Pranzatelli (PhD 2024, UCSD postdoc)
• Wei Xiao (PhD 2024, FDA ORISE Fellow)
• Nick Rachmaninoff (PhD 2022, GSK data scientist)
• JL Weissman (PhD 2019, Stony Brook faculty)

He develops computational tools like PIIM for metagenomic analysis and adaptivetau for stochastic simulations. His lab website provides detailed project updates and software resources.