Background: Betel quid chewing, smoking and, alcohol consumption being the primary cause of oral cancer in India, has been driving its death rate rapidly over the years. The low five-year survival rate has been seen since oral malignant growth is commonly distinguished in advanced stages. With the advancement of medication and innovation in the clinical sciences still, the cause of OSCC is unknown at the molecular level. Aim: There is a vital need for computational biology to reconsider the helpful methodologies of oral squamous cell carcinoma (OSCC) detection to recognize the malignancy in its beginning phases and analysis at the genomic level to find the target region, furthermore to distinguish the molecular sub-classes so as a propose to personalize the treatment with an early diagnosis. Objective: This review paper principally reports on a few techniques and tools that have been applied to analyze OSCC at a molecular, structural, and functional level so that the quality of gene expression dataset of oral squamous cell carcinoma to distinguish the differentially expressed genes. Further, a few other clustering techniques that are utilized for protein-protein interaction and pathway study have been discussed. Conclusion: A series of literature has been reviewed to locate the techniques used nowadays for the computational genomic analysis to distinguish the expected cancer diagnosis, prognosis, or medication reaction at an early stage as to help oral cancer mitigation through the recognizable proof of target gene and the stage-explicit genes of OSCC with the support of bioinformatics and computational biology for an early diagnosis.