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10.1007/s40139-020-00213-x http://scihub22266oqcxt.onion/10.1007/s40139-020-00213-x 32989410!7511257!32989410     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Curr+Pathobiol+Rep 2020 ; 8 (4): 149-161 Nephropedia Template TP {{tp|p=32989410|t=2020. Leveraging Computational Modeling to Understand Infectious Diseases |pdf=|usr=}}{{32989410}} gab.com Text Leveraging Computational Modeling to Understand Infectious Diseases JO: Curr Pathobiol Rep http://www.kidney.de/pget.php?&tw=1&pmid=32989410 #FOAvip PURPOSE OF REVIEW: Computational and mathematical modeling have become a critical part of understanding in-host infectious disease dynamics and predicting effective treatments. In this review, we discuss recent findings pertaining to the biological mechanisms underlying infectious diseases, including etiology, pathogenesis, and the cellular interactions with infectious agents. We present advances in modeling techniques that have led to fundamental disease discoveries and impacted clinical translation. RECENT FINDINGS: Combining mechanistic models and machine learning algorithms has led to improvements in the treatment of Shigella and tuberculosis through the development of novel compounds. Modeling of the epidemic dynamics of malaria at the within-host and between-host level has afforded the development of more effective vaccination and antimalarial therapies. Similarly, in-host and host-host models have supported the development of new HIV treatment modalities and an improved understanding of the immune involvement in influenza. In addition, large-scale transmission models of SARS-CoV-2 have furthered the understanding of coronavirus disease and allowed for rapid policy implementations on travel restrictions and contract tracing apps. SUMMARY: Computational modeling is now more than ever at the forefront of infectious disease research due to the COVID-19 pandemic. This review highlights how infectious diseases can be better understood by connecting scientists from medicine and molecular biology with those in computer science and applied mathematics. Twit Text FOAVip Leveraging Computational Modeling to Understand Infectious Diseases ????Curr Pathobiol Rep http://www.kidney.de/pget.php?&tw=1&pmid=32989410 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32989410 #FOAvip English Wikipedia <ref>{{Cite pmid|32989410}}</ref> Leveraging Computational Modeling to Understand Infectious Diseases #MMPMID32989410 Jenner AL; Aogo RA; Davis CL; Smith AM; Craig M Curr Pathobiol Rep 2020[]; 8 (4): 149-161 PMID32989410show ga PURPOSE OF REVIEW: Computational and mathematical modeling have become a critical part of understanding in-host infectious disease dynamics and predicting effective treatments. In this review, we discuss recent findings pertaining to the biological mechanisms underlying infectious diseases, including etiology, pathogenesis, and the cellular interactions with infectious agents. We present advances in modeling techniques that have led to fundamental disease discoveries and impacted clinical translation. RECENT FINDINGS: Combining mechanistic models and machine learning algorithms has led to improvements in the treatment of Shigella and tuberculosis through the development of novel compounds. Modeling of the epidemic dynamics of malaria at the within-host and between-host level has afforded the development of more effective vaccination and antimalarial therapies. Similarly, in-host and host-host models have supported the development of new HIV treatment modalities and an improved understanding of the immune involvement in influenza. In addition, large-scale transmission models of SARS-CoV-2 have furthered the understanding of coronavirus disease and allowed for rapid policy implementations on travel restrictions and contract tracing apps. SUMMARY: Computational modeling is now more than ever at the forefront of infectious disease research due to the COVID-19 pandemic. This review highlights how infectious diseases can be better understood by connecting scientists from medicine and molecular biology with those in computer science and applied mathematics. äLeveraging Computational Modeling to Understand Infectious Diseases (epmc).pdf DeepDyve Pubget Overpricing