ABSTRACT
In the current scenario, a big challenge is to use continuously increasing biological and clinical data for better understanding and also to clarify the co-relation of the biological system and disease progression through the use of numerous computational analytical techniques. For the study of biological science and the mechanisms associated, molecular and cellular level computational approaches are used. They employ innovative computational analysis methods incorporating mathematical and computational approaches to answer all theoretical and experimental questions in biology and also for a systems-based understanding of various disease progressions. They can be used to analyze large collections of biological data, such as genetic sequences, cell populations, or protein samples in different biochemical tests. Computational biology study includes the science of genomics, systems biology, imaging, proteomics, metabolomics, ecology, and phylogeny. Both computational biology and bioinformatics are interdisciplinary fields that together can be used to elaborate the phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. This study helps scientists reach more accurate conclusions more quickly and reliably. The authors present theories, methods, and applications of computational biology science that may inspire the development of new algorithms and computational methods that utilize both molecular and clinical data for diagnosis, prognosis, and therapy in disease progression.
