Investigation of Genes and Their Interactions in Liver Diseases Using Bioinformatics Algorithms

In this study, we considered progression of liver diseases. Particularly Hepatocellular Carcinoma Cancer, HCC, whose patients have low survival rates. For purpose, researched molecular structures and protein interactions involved in the initiation HCC. We exploited microarray data samples their gene expression profiles from literature. During analysis, implemented statistical analysis techniques looked for Differentially Expressed Genes during As a result found 12 hub genes, where 3 them (ANLN, TOP2A ASPM) were upregulated others (CXCL14, LINC01093, OIT3, CLEC4G, THRSP, APOF, CLTRN FCN3) downregulated. By performing Gene Ontology Analysis, classified genes with increased or decreased expressions terms cellular component, biological process, function. Subsequently, executed protein-protein interaction network important between genes. Results concluded that these play key role significant diseases can be used as potential biomarker disease progression. Furthermore, feature showed it is becoming more difficult to compensate functional deficiencies proteins encoded by processes. particular, Analysis denoted associates many pathways change cause decent problems functions.