Future perspectives of computational biology: Demanding shifts in analytical thinking to unfold biological complexities

Abstract

With available knowledge and databases, the mining of more information has driven the last decade of computational biology. We validated the existing known information with omics data. There is need in overall shift in our approach; instead of understanding the architecture of hierarchical gene network, we should work on condition-specific shift in hierarchies or partnerships of gene to manage plasticity. We assume that there will be a great shift in metabolomics approach to understand how cell manages to perform at its minimum driving energy level. Transformation of decision-making system with systematic mathematical and multiple soft computing modeling platform will be crucial to untangle the thread of pattern with which the nature follows for the process of evolution, expression, and engineering the cellular machinery.