“A Mathematical Theory of Communication”, was published in 1948 by Claude Shannon to address the problems in the field of data compression and communication over (noisy) communication channels. Since then the concepts and ideas developed in Shannon's work have formed the basis of information theory, a corenerstone of statistical learning and inference and has been playing key role in disciplines such as physics and thermodynamics, probability and statistics, computational sciences and biological sciences. In my talk, I will review the key information theory based concepts and describe examples of their applications in three major areas of research in bioinformatics and computational biology - gene regulatory network inference, disease-gene association analysis and biological sequence analysis.