The intensely data-driven and integrative nature of research in genomic medicine in the post-genomic era presents significant challenges in formulating and testing important translational hypotheses. Advances in high-throughput experimental technologies continue to drive the exponential growth in publicly available genomic data, and the integration and interpretation of these immense volumes of data towards direct, measurable improvements in patient health and clinical outcomes is a grand challenge in genomic medicine. Consequently, genomic medicine has become rooted in and enabled by bioinformatics, engendering the notion of translational bioinformatics. Translational bioinformatics is characterized by the challenge of integrating molecular and clinical data to enable novel translational hypotheses bi-directionally between the domains of biology and medicine. This information can be published in our peer-reviewed journal with impact factors and are calculated using citations not only from research articles but also review articles (which tend to receive more citations), editorials, letters, meeting abstracts, short communications, and case reports. The inclusion of these publications provides the opportunity for editors and publishers to manipulate the ratio used to calculate the impact factor and try to increase their number rapidly. Impact factor plays a major role for the particular journal. Journal with higher impact factor is considered to be more important than other ones.