Philip Johnson
Philip Johnson
Graduate Program Affiliations
- Biological Sciences (BISI): Behavior, Ecology, Evolution, and Systematics (BEES)
- Biological Sciences (BISI): Computational Biology, Bioinformatics, and Genomics (CBBG)
- Biological Sciences (BISI): Molecular and Cell Biology (MOCB)
Research Interests
We develop statistical and mathematical models to make sense of large-scale population genomic data at multiple levels. New types of data from collaborators inspire new types of theory and vice versa. Population genetics provides an incredible tool to uncover the past to infer the key times and places at which natural selection acted or demography changed.
Specific research projects involve:
- Interrogating the dynamics of the adaptive immune system through the lens of evolution, whereby the diversity of T cell repertoire in a single individual evolves on both short timescales (during and shortly after infections/vaccinations) and long timescales (during aging).
- Inferring the presence of contamination and damage in ancient DNA.
- Understanding mutation rate evolution, particularly in the hominid phylogeny.
Education
- Ph.D., Biophysics with a Designated Emphasis in Computational & Genomic Biology, UC Berkeley, 2009
- A.B., Harvard College, 2001
All Publications
Latest Papers
Retention of a female-specific growth hormone receptor gene correlates with reverse sexual size dimorphism in birds
Author(s): Shauna Ann Rasband, Michael J. Braun, Philip L F Johnson
UMD Author(s): Philip Johnson, Michael Braun
Ecological drivers of CRISPR immune systems
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mSystems
UMD Author(s): Philip Johnson
Population structure, intergroup interaction, and human contact govern infectious disease impacts in mountain gorilla populations
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American Journal of Primatology
UMD Author(s): Philip Johnson
Dynamics and turnover of memory CD8 T cell responses following yellow fever vaccination
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PLOS Computational Biology
UMD Author(s): Philip Johnson
Selection influences naive CD8+ TCR‐β repertoire sharing
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Immunology
Author(s): Hao H. Yiu, Louis N. Schoettle, Marlene Garcia‐Neuer, et. al
UMD Author(s): Philip Johnson
Avoidance of Self during CRISPR Immunization
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Trends in Microbiology
UMD Author(s): Philip Johnson
Network-Based Prediction of Novel CRISPR-Associated Genes in Metagenomes
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mSystems
UMD Author(s): Philip Johnson
Linking high GC content to the repair of double strand breaks in prokaryotic genomes
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Plos Genetics
UMD Author(s): Philip Johnson
Visualization and prediction of CRISPR incidence in microbial trait-space to identify drivers of antiviral immune strategy
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The ISME Journal
UMD Author(s): Philip Johnson
