• Computational and research strategies in Covid-19
  • Niloofar Agharezaee,1 Flora Forouzesh,2,*
    1. PhD student, Department of Bioinformatics, Kish International Campus, University of Tehran, Kish, Iran.
    2. Assistant Professor, Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.


  • Introduction: SARS-CoV-2 was the first severe epidemic of the digital age. Computational approaches have been widely used in the effort to deal promptly and effectively with the resulting global health crisis. Bioinformatics and computational biology are important in understanding and analyzing protein dynamics, primarily in relation to sequence, structure, and evolution-based analysis (which tracks changes in protein composition over time). We need to constantly learn more about viruses and their variants. Therefore, the need for rapid and effective computational analysis of the disease and its mutations is essential to reduce its potentially harmful effects.
  • Methods: The present study is a review study that has been compiled using electronic resources in reputable databases such as PubMed, Scopus, Google Scholar, ISI, Science Direct related from 2019 to 2022.
  • Results: A variety of computational approaches have been explored and are underway in the hope of better understanding how Covid-19 works to develop effective diagnosis and treatment. Investigate the importance of active signaling pathways, for example, using a set of randomly generated signaling pathways to identify the most important signaling pathways for drug prediction and drug composition. A fast and cost-effective computational method has been developed for the initial prediction of the impact of emerging viral species at the molecular level. With this early prediction, there will be a great opportunity for the scientific community to do more research. On the other hand, we know that one of the best diagnostic strategies for Covid-19 disease is lung imaging. To reduce the burden on radiologists of interpreting these images, "artificial intelligence diagnosis" can be very effective and useful. These images can be easily entered into the artificial intelligence system and receive diagnostic results in a few seconds.
  • Conclusion: The field of bioinformatics and computational biology is wide in terms of coverage. It can be limited to protein at the molecular scale to analyze specific protein interactions or extended to study the global progression of the disease. The significant assistance provided by computing programs during the epidemic is believed to motivate redoubled efforts to further develop and adopt them, with the aim of increasing preparedness and critical response to current and future emergencies.
  • Keywords: Coronavirus 2019 (Covid-19), Bioinformatics, Computational tools, Public health.