SIMON, a powerful AI software accelerating discovery of human immune memory responses to viruses

Abstract

Abstract Influenza and SARS-CoV-2 are among the greatest viral threats to human health causing the 20th and 21st centuries’ most significant pandemics. These viruses have caused millions of deaths worldwide and continue to pose a significant risk to global health. To effectively fight against these viruses, it is essential to understand the complexity behind the generation of immune memory responses. The traditional analytical methods are often inadequate for capturing the complexity of the immune responses. To address this challenge, we have developed SIMON, a new AI software that can perform integrative multi-omics analysis to study human immune memory responses. With an easy-to-use graphical user interface, standardized pipelines, automated approach for machine learning testing over 180 algorithms, and other statistical analysis methods, SIMON helps to identify crucial patterns in biomedical data. We have demonstrated the accuracy, ease of use, and power of our software on various biomedical datasets, gaining valuable insights into the mechanisms underlying immunity to SARS-CoV-2 and influenza. This knowledge can be used to develop more effective vaccines and help researchers better understand the long-term impact of SARS-CoV-2 or influenza viruses on the immune system. By predicting the immune memory responses, SIMON has the potential to accelerate the development of vaccines that provide long-term protection against these pandemic viruses. Overall, SIMON is a powerful software platform for data mining that facilitates pattern recognition and knowledge extraction from high-dimensional biomedical data. It has the potential to greatly accelerate discovery in human immunology and biomedicine.