Abstract
Infectious diseases are the primary cause of mortality worldwide. The dangers of infectious disease are compounded with antimicrobial resistance, which remains the greatest concern for human health. Although novel approaches are under investigation, the World Health Organization predicts that by 2050, septicaemia caused by antimicrobial resistant bacteria could result in 10 million deaths per year. One of the main challenges in medical microbiology is to develop novel experimental approaches, which enable a better understanding of bacterial infections and antimicrobial resistance. After the introduction of whole genome sequencing, there was a great improvement in bacterial detection and identification, which also enabled the characterization of virulence factors and antimicrobial resistance genes. Today, the use of in silico experiments jointly with computational and machine learning offer an in depth understanding of systems biology, allowing us to use this knowledge for the prevention, prediction, and control of infectious disease. Herein, the aim of this review is to discuss the latest advances in human health engineering and their applicability in the control of infectious diseases. An in-depth knowledge of host–pathogen–protein interactions, combined with a better understanding of a host’s immune response and bacterial fitness, are key determinants for halting infectious diseases and antimicrobial resistance dissemination.
Highlights
Over the last decade, theoretical and computational biology, combined with open access to biological databases, have presented new opportunities in different areas of the field, such as genomics or evolutionary biology
Other questions that modeling is trying to answer include how bacterial populations evolve under antibiotic pressure, what the function of dose-effect is in the outcome of infection, and what risk factors are associated with epidemics
The clinical and scientific literature suggest that advancements in genome sequencing technologies have made successfully rapid diagnostics available for infectious diseases and the prediction of AMR, which is beneficial for slow-growing microorganisms like Mycobacteria [133] or the small colony variant of Pseudomonas aeruginosas [134], which is usually isolated from cystic fibrosis patients or chronic obstructive lung diseases
Summary
Theoretical and computational biology, combined with open access to biological databases, have presented new opportunities in different areas of the field, such as genomics or evolutionary biology. Mesarovic [2,3], under “the understanding that the whole of functional genomics [5,6], the completion of the human genome project, and the development of is greater than the sum of the parts” [4] The increase in this field was prompted by improvements of high-throughput technologies. Functional genomics [5,6], the completion of the human genome project, and the development of Systems biology intends to unravel the interactions between components of biological systems, high-throughput technologies. 2019 Jan 14; 10(1):192© Copyright Clearance Center’s. The aim of this review is to compile the latest discoveries and advances on health computational engineering, new mathematical the applications of these models in the computational biomedical field.
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