This is to inform that due to some circumstances beyond the organizer control, “2nd Edition of International Conference and Expo on Applied Microbiology” (ICAM 2023) Hybrid Event scheduled during June 23-24, 2023 | Rome, Italy has been postponed. The updated dates and venue will be displayed shortly.
Your registration can be transferred to the next edition, if you have already confirmed your participation at the event.
For further details, please contact us at email@example.com or call +1 (702) 988 2320.
Predictive microbiology is a field that combines microbiology, mathematics, and statistics with the goal of developing models to characterise and predict microbe growth and inactivation under a variety of situations. Predictive microbiology is based on the idea that the responses of populations of microorganisms to environmental factors are repeatable, and that by thinking about environments in terms of identifiable dominating constraints, it is possible to predict those microorganisms' responses based on previous observations. Predictive microbiology, according to proponents, has numerous advantages in the field of food microbiology, and there is growing international interest.
Microbiologists are living in an era when high-throughput smart technologies are being used to capture biological data in unprecedented volumes. Applying computational tools to find useful information from these data is becoming an increasingly important skill requirement outside laboratory and field experiments. Machine learning (ML), a subfield of artificial intelligence (AI), is a well-established approach that is gaining traction in the field of microbiology. It has so far been applied to computationally intensive problems such as predicting drug targets and vaccine candidates, diagnosing infectious disease-causing microorganisms, classifying drug resistance to antimicrobial medicines, predicting disease outbreaks, and investigating microbial interactions.