Unlocking the potential of personalized medicine - A review

Abstract

Bioinformatics is a multidisciplinary field that evolves techniques and software tools for understanding the data in biology, when there are large data sets in particular. This field includes computer science, biology, physics, chemistry, mathematics, and statistics. Recent advancements in high-throughout technologies have been made possible by the emergence of systems biology as a comprehensive science, allowing for a more precise modeling of complicated disorders. A general definition of personalized medicine is a participatory, preventative, personalized, and predictive healthcare strategy. One of the biggest challenges in personalized medicine is the translation of scientific findings into more effective therapeutic results. Translational bioinformatics is a potent technique for bridging the gaps between systems biology research and clinical practice. The objective is to give scientists the appropriate tools for explaining normal biological processes, dysfunctions of these systems that result in disease, and strategies that enable the development of novel therapeutics. Recently, sequencing platforms and the vast amount of genomes and transcriptomes have presented significant problems for genomics in general and bioinformatics in particular. These methods are essential for comprehending disorders and using personalized medicine at systemic levels. The goal of this article is to assemble a list of resources and methods used by scientists to handle data from recent platforms’ large sequencing to new generations and the uses of this data in various fields of the life sciences, including medicine.