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{"references": ["Soumya Banerjee, Jeremie Guedj, Ruy Ribeiro, Melanie Moses, Alan Perelson (2016). Estimating biologically relevant parameters under uncertainty for experimental within-host murine West Nile virus infection. Journal of the Royal Society Interface, 13(117), 20160130-. http://doi.org/10.1098/rsif.2016.0130", "Soumya Banerjee. Optimal strategies for virus propagation. arXiv preprint arXiv:1512.00844, 2015", "Soumya Banerjee, A Roadmap for a Computational Theory of the Value of Information in Origin of Life Questions, Interdisciplinary Description of Complex Systems, 2016", "Banerjee, S., Guedj, J., Ribeiro, R. M., Moses, M., & Perelson, A. S. 2016. Estimating biologically relevant parameters under uncertainty for experimental within-host murine West Nile virus infection. Journal of the Royal Society Interface, 13(117), 20160130-.http://doi.org/10.1098/rsif.2016.0130", "Soumya Banerjee. Analysis of a Planetary Scale Scientific Collaboration Dataset Reveals Novel Patterns. arXiv preprint arXiv:1509.07313, 2015", "Soumya Banerjee and Joshua Hecker. A Multi-Agent System Approach to Load-Balancing and Resource Allocation for Distributed Computing, arXiv preprint arXiv:1509.06420, 2015", "Soumya Banerjee. 2009. An Immune System Inspired Approach to Automated Program Verification, arXiv preprint arXiv:0905.2649, 2009", "Soumya Banerjee and Melanie Moses. Scale Invariance of Immune System Response Rates and Times: Perspectives on Immune System Architecture and Implications for Artificial Immune Systems. Swarm Intelligence 4, 301\u2013318 (2010). URL http://www.springerlink.com/content/w67714j72448633l/", "Soumya Banerjee. 2013. Scaling in the immune system, PhD Thesis, University of New Mexico (2013)", "Soumya Banerjee. An Immune System Inspired Theory for Crime and Violence in Cities. Interdisciplinary Description of Complex Systems, 15(2):133-143, 2017", "Soumya Banerjee and Melanie Moses. Immune System Inspired Strategies for Distributed Systems. arXiv preprint arXiv:1008.2799, 2010", "Soumya Banerjee. A Biologically Inspired Model of Distributed Online Communication Supporting Efficient Search and Diffusion of Innovation. Interdisciplinary Description of Complex Systems 14 (1), 10-22", "Soumya Banerjee. An artificial immune system approach to automated program verification: Towards a theory of undecidability in biological computing. PeerJ Preprints 5 (e2690v1) 2017", "A spatial model of the efficiency of T cell search in the influenza-infected lung L Drew, F Stephanie, B Soumya, C Candice, C Judy, M Melanie. Journal of Theoretical Biology 398 (7), 52-63", "Soumya Banerjee. An artificial immune system approach to automated program verification: Towards a theory of undecidability in biological computing. PeerJ Preprints 5 (e2690v1) 2017", "Soumya Banerjee. A computational technique to estimate within-host productively infected cell lifetimes in emerging viral infections. PeerJ Preprints 4 (e2621v2) 2017", "Science and technology consortia in US biomedical research: A paradigm shift in response to unsustainable academic growth TWC Curt Balch, Hugo Arias-Pulido, Soumya Banerjee, Alex K. Lancaster. BioEssays 37 (2), 119-122"]}
The immune system protects a host from foreign pathogens. In rare cases, the immune system can attack the cells of the host organism causing autoimmune diseases. We outline a computational framework that combines bioinformatics and network analysis with an emerging targets platform. The computational framework presented here can be used to find drug targets for autoimmune diseases. It can also be used to find existing drugs that can be repurposed to treat autoimmune diseases based on networks of interactions or similarities between different diseases. Information on which gene regions are associated with the disease (single nucleotide polymorphisms) can be used in gene therapy when that technique becomes viable. Our analysis also revealed immune cell subtypes that are implicated in these diseases. These immune cell subtypes can be selected for immunotherapy experiments. Finally, our analysis also reveals intra-cellular and protein-protein interaction networks and pathways that can be targeted with small molecule inhibitors. The downstream off-target effects of these inhibitors can also be determined from such a network analysis. In summary, our computational framework can be used to find novel therapeutics for autoimmune diseases and potentially even other dysfunctions.
autoimmune diseases,bioinformatics, network analysis, immune system modelling
autoimmune diseases,bioinformatics, network analysis, immune system modelling
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