Table 1a. Surface antigen gene expression  from a list of top 20 highly expressed genes encoding for putative membrane proteins in either hESCMSCs or hESCs: (Highly expressed membrane proteins in hESC-derived MSC over hESC)

Table 1b. Surface antigen gene expression  from a list of top 20 highly expressed genes encoding for putative membrane proteins in either hESCMSCs or hESCs: (Highly expressed membrane proteins in hESC over hESC-derived MSC)

Table 1. Eosinophil- and CCR3-dependent allgergen-induced genes

Table 3 Genes differentially expressed in CD4+CD56+HN versus c-AML

Table 2. List of 35 genes able to discriminate between all DCIS and all invasive samples

Table 4. List of 43 genes able to discriminate between well- and poorly differentiated DCIS

List of 78 genes able to discriminate between well/well-intermediately and intermediately-poorly/poorly differentiated DCIS

Table 3. List of 80 genes able to discriminate between poorly differentiated DCIS and invasive grade 3 breast tumours

SuppTable3. An Excel file containing the expression data for the hypoxia genes for all patients (validation)

SuppTable2. An Excel file containing the expression data for the 70 genes for all patients (validation)

Table 1. Genes elevated in cisplatin-resistant cells

Table 2. Genes decreased in cisplatin-resistant cells

Table 1. List of genes differentially expressed in YB-1 siRNA-transfected SKOV-3 cells

Figure 3. Expression Profiles of Classifying Genes: 62 genes that were present in more than 20% of the 500 repeated assessments with 34 patients in the training set of the classifier

Additional Data File-3 - The optimal 52-gene molecular classi er in ER+ breast cancer Top ranked 52 prognostic genes in ER+ breast cancer as determined by a meta-analysis of three major breast cancer data sets. We give the sign of their global average Cox

Supplementary Table II. 111-gene classifier for lung SCC recurrence. U133A indicates corresponding Affymetrix probe  if present  in the test set. P value and Hazards Ratio (HR) in relation to time to recurrence (Recurrence) analysis and time to cancer-rel