Digital candidate gene approach (DigiCGA) for identification of cancer genes.
The candidate gene approach is one of the most commonly used methods for identifying genes underlying disease traits. Advances in genomics have greatly contributed to the development of this approach in the past decade. More recently, with the explosion of genomic resources accessible via the public Web, digital candidate gene approach (DigiCGA) has emerged as a new development in this field. DigiCGA, an approach still in its infancy, has already achieved some primary success in cancer gene discovery. However, a detailed discussion concerning the applications of DigiCGA in cancer gene identification has not been addressed. This chapter will focus on discussing DigiCGA in a generalized sense and its applications to the identification of cancer genes, including the cancer gene resources, application status, platform and tools, challenges, and prospects.
Zhu
Meng-Jin
MJ
Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China.
Li
Xiang
X
Zhao
Shu-Hong
SH
D019295:Computational Biology / Q000379:methods*; D052138:Genes, Neoplasm; D056726:Genetic Association Studies / Q000379:methods*; D020022:Genetic Predisposition to Disease / Q000235:genetics; D006801:Humans; D009369:Neoplasms / Q000235:genetics*