由於乳癌發病時在臨床上會有一些不同的特徵，而且各特徵之間又彷彿存在著某些特定的關係。又，自從生物晶片問世以來，因為它的基因表現量有著高產能的特性，所以一般常被用於基因的探測或發掘上。根據以上觀點，若能將病人依臨床上發病特徵的不同分兩群，透過生物晶片的實驗，收集各病人的基因表現量，再輔以電腦的統計與分析能力，或許就能找出一些表現量上有明顯差異的基因，而這些表現量上有明顯差異的基因可能就是影響乳癌發病時，臨床特徵不同的基因。 所以我們就根據以上的結論，收集了所有跟乳癌病人相關的基因表現量和臨床特徵的資料，和一些常用的計算基因表現量的正規化和差異化的統計方法，建了一個資料庫，以便分析看是不是有某些臨床特徵和某些基因有特定的關係。 There are many clinical characteristics on breast cancer, and some of them may have relationships. Besides, microarray, key tool for high throughput genomic analysis, is the common method to find or detect genes (1). If we can divide the patients into two groups according to their clinical characteristics and collect their gene expressions, we may find some differentially expressed genes. Maybe theses differentially expressed genes are the genes that affect the breast cancer clinical characteristics. So we construct a database, GECB, collected breast cancer gene expression and clinical data, and some commonly used normalization and differential expression test methods. To further analyze differentially expressed genes on breast cancer clinical characteristics.
