Our research aims at obtaining a holistic understanding of how variation in information flow affects phenotypes and fitness. We particularly focus on understanding how sequence variation- single nucleotide changes, repeats or compositional bias within intrinsically disordered proteins/regions influence the function(s), regulation and evolution of biomolecules, with special emphasis on health and disease. To address this, we investigate biological information flow at different scales of complexity (genome(s), systems and molecular levels) and at different time-scales (at an instant to millions of years) in diverse organisms ranging from yeast to humans. Our research work involves computational investigations integrating and analyzing large-scale datasets, coupled with experimental investigations, primarily using budding yeast as a model system.