Network approaches for identification of human genetic disease genes

The identification of genes causing a genetic disease is still an important issue in the biomedical field because list incomplete while it determines early diagnosis and treatment fatal diseases such as autism, cancer, drug resistance, secondary hypertension. Genes associated with particular or similar tend to reside same region biological network their location on can be predicted. Many analysis methods have been proposed solve this problem so far. This review first helps readers access master basic concepts networks, genes, properties. Then, main content devoted evaluation analytical recently used find two networks: protein-protein interaction (PPI) cellular signaling (CSN). We reported typical problems primary that cause modern techniques were widely for solving those problems. For each technique, we also represented key algorithms audience exactly implement them experiments. In particular, evaluated performance these prediction suggested context usage. Finally, implications are discussed some future research directions proposed. Taken together, often identified from data by approaches: network-based machine learning-based methods, approach