Practical Applications of Computational Biology and Bioinformatics, 16th International Conference (PACBB 2022)

Practical Applications of Computational Biology and Bioinformatics, 16th International Conference (PACBB 2022) Synopsis

This book is suitable for researchers and practitioners in biology, medicine and health sciences and bioinformatics. The success of bioinformatics and computational biology in recent years has been driven by research through computational tools and techniques that are essential for data analysis in modern biology and medicine. Systems biology is a related research area that has been replacing the reductionist view that dominated biology research in the last decades, requiring the coordinated efforts of biological researchers with those related to data analysis, mathematical modelling, computer simulation and optimization. The accumulation and exploitation of large-scale databases prompt new computational technology and for research into these issues. In this context, many widely successful computational models and tools used by biologists in these initiatives, such as clustering and classification methods for gene expression data, are based on computer science/ artificial intelligence (CS/AI) techniques. In fact, these methods have been helping in tasks related to knowledge discovery, modelling and optimization tasks, aiming at the development of computational models so that the response of biological complex systems to any perturbation can be predicted. This proceedings of the 16th International Conference on Practical Applications of Computational Biology and Bioinformatics (PACBB), held in L’Aquila (Italy) from July 13 to 15, 2022, contains ten original contributions of authors from many different countries (Bahrain, Canada, France, Italy, Portugal, Saudi Arabia, Spain, and UK) and different subfields in bioinformatics and computational biology. It is also suitable for artificial intelligence researchers interested in exploring applications in biology and health sciences and computational models.