Computational Analysis of PTEN Gene Mutation

Post-genomic data can be efficiently analyzed using computational tools. It has the advantage over the biochemical and biophysical methods in term of higher coverage. In this research, we adopted a computational analysis on PTEN gene mutation.  Mutation in PTEN is responsible for many human diseases. The results of this research provide insights into the protein domains of PTEN and the distribution of mutation

In Silico Analysis of Oncogenes for Renal Cancer

Computational tools and methods play a vital role in handling and analyzing a large volume of genomic data. In cancer research, in silico methods such as computational algorithm and protein databases are indispensable. In this paper, we adopted an in silico approach to analyze oncogenes that cause  renal cancer. Our objective is to identify and analyze the genes which are over expressed in the renal cancer tissues. The identification of oncogenes for renal cancer could provide directions and insights for molecular cancer treatment