With our relatively newfound ability to perform large-scale surveys of the genomic and proteomic landscape, the principal challenge has shifted away from measurement towards interpretation of the data. Our group has been developing and using analytical approaches rooted in information theory and formal dynamic systems theory to infer biological structure and function in these large data sets. In particular, we have been using this approach to decipher the principles of operation of the immune system by mapping its internal communication network, as well as, its participation in neuro-endocrine signaling.
Our eventual goal is not only to tap into pathogenic immune conversations; but, also, more importantly, to redirect these conversations with a limited number of well-chosen and well-timed pharmaceutical messages. This research is founded on the premise that for immune therapies to be both safe and effective, the immune system must be considered as an integrated whole.
Current research efforts at the CSB lab is focused on understanding immune dysfunction and neuroinflammation from an integrated systems perspective. In particular, our group is investigating how subtle imbalances in the interplay between the immune system’s multiple components as well as its interactions with the endocrine and nervous systems may lead to complex disorders such as myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), Gulf War illness (GWI), and other neurodegenerative disorders such as Alzheimer's Disease and Parkinson's Disease. Illnesses such as these continue to defy a conventional one-piece-at-a-time approach. As none of the body’s systems function in isolation, we believe that new insight can be achieved by considering the immune, endocrine and nervous systems as part of an overarching and integrated whole. This comprehensive approach is at the very heart of systems biology: an emerging science where context and interaction are key focal points.
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Type of work: Work within the Clinical Systems Biology Group currently consists in constructing mathematical and computer models describing the neuroinflammatory cascade at the molecular, cellular and systems levels. The models are validated or applied by fitting them to experimental data obtained from the Mary Ann Fletcher Immunology Laboratory or other collaborating sources. The work performed in the Clinical Systems Biology Group does NOT perform wet lab experiment projects to gather data, rather the data used in our research is gathered elsewhere by our collaborators or is taken from the literature.
Skills required: Students and fellows should possess programming skills in python, C, Octave/Matlab or another programming language, already be familiar with or willing to learn the typesetting language LaTeX, be comfortable with a Linux operating system, and have experience in implementing and solving ordinary and partial differential equation systems or cellular automata/agent-based systems.
More info: If you meet these criteria and would like to learn more about the type of research conducted within our group, please visit the publications and research sections of the website. If you would like more information, please feel free to contact email@example.com. Note that even if the position you are looking for is not currently being advertised, if you are highly qualified and interested, you should still send your contact information.
How to apply: Send your CV (in PDF format) along with the reasons for your interest in working in this area (in PDF format or in the body of the email) via email to firstname.lastname@example.org with the subject line: Potential CSB Candidate - <Your Name>.
Specific positions currently available
DRUGPATH: The Drug Gene Pathway meta-database (https://drugpath.app)
Jaundoo R, Craddock TJA. DRUGPATH: The Drug Gene Pathway Meta-Database. Int J Mol Sci. 2020 Apr 30;21(9). doi: 10.3390/ijms21093171. PubMed PMID: 32365960; PubMed Central PMCID: PMC7246871. (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7246871/)
Jaundoo R, Bohmann J, Gutierrez GE, Klimas N, Broderick G, Craddock TJA. Towards a Treatment for Gulf War Illness: A Consensus Docking Approach. Mil Med. 2020 Jan 7;185(Suppl 1):554-561. doi: 10.1093/milmed/usz299. PubMed PMID: 32074351; PubMed Central PMCID: PMC7029833. (https://pubmed.ncbi.nlm.nih.gov/32074351/)