Milana Frenkel-Morgenstern's Cancer Genomics and BioComputing Lab at Bar-Ilan University, Israel
Proto-oncogenes normally help cells grow. Due to mutation in a proto-oncogene mutate or becomes an oncogene, it can become permanently turned on or activated when it is not supposed to be. When this happens, the cell grows out of control, which can lead to cancer. Tumor suppressor genes are normal genes that slow down cell division, repair DNA mistakes, or causes apoptos. When tumor suppressor genes don't work properly, cells can grow out of control, which can lead to cancer. An important difference between oncogenes and tumor suppressor genes is that oncogenes result from the activation of proto-oncogenes, but tumor suppressor genes cause cancer when they are inactivated.
In Oncogene Tumor-suppressor gene resource, we use proteins network, mutation and methylation data of fusions and de-vised a novel network-based parameter called ‘preferential attachment score’ to categorize genes into oncogenes or tumor suppressors. The classification is done using a Naïve Bayes Computation approach. An ABC-MCMC method is used for selecting features for training our classification algorithm. A survey of tumor suppressors and oncogenes has also been done from the perspectives of somatic mutations and network properties.