TY - JOUR AU - Yeung, Ka Yee AU - Medvedovic, Mario AU - Bumgarner, Roger E. PY - 2003 DA - 2003/04/25 TI - Clustering gene-expression data with repeated measurements JO - Genome Biology SP - R34 VL - 4 IS - 5 AB - Clustering is a common methodology for the analysis of array data, and many research laboratories are generating array data with repeated measurements. We evaluated several clustering algorithms that incorporate repeated measurements, and show that algorithms that take advantage of repeated measurements yield more accurate and more stable clusters. In particular, we show that the infinite mixture model-based approach with a built-in error model produces superior results. SN - 1474-760X UR - https://doi.org/10.1186/gb-2003-4-5-r34 DO - 10.1186/gb-2003-4-5-r34 ID - Yeung2003 ER -