Li Ker-Chau, Palotie Aarno, Yuan Shinsheng, Bronnikov Denis, Chen Daniel, Wei Xuelian, Choi Oi-Wa, Saarela Janna, Peltonen Leena
Department of Statistics, UCLA, 8125 Math Sciences Bldg, Los Angeles, California 90095-1554, USA.
Genome Biol. 2007;8(10):R205. doi: 10.1186/gb-2007-8-10-r205.
A novel approach to finding candidate genes by using gene expression data through liquid association is developed and used to identify multiple sclerosis susceptibility candidate genes.
一种通过液体关联利用基因表达数据寻找候选基因的新方法被开发出来,并用于识别多发性硬化症易感性候选基因。