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This document provides supplementary information and details not included in the paper " Multi-class Cancer Diagnosis Using Tumor Gene Expression Signatures. " Other sources of information can be found at our web site www.genome.wi.mit.edu/MPR, and also in Yeang et al. (2001) and Rifkin et al. (2002) (to appear).
Diffuse large B-cell lymphoma (DLBCL), the most common lymphoid malignancy in adults, is curable in less than 50% of patients. Prognostic models based on pre-treatment characteristics, such as the International Prognostic Index (IPI), are currently used to predict outcome in DLBCL. However, clinical outcome models identify neither the molecular basis of(More)
Embryonal tumours of the central nervous system (CNS) represent a heterogeneous group of tumours about which little is known biologically, and whose diagnosis, on the basis of morphologic appearance alone, is controversial. Medulloblastomas, for example, are the most common malignant brain tumour of childhood, but their pathogenesis is unknown, their(More)
SUMMARY GeneCluster 2.0 is a software package for analyzing gene expression and other bioarray data, giving users a variety of methods to build and evaluate class predictors, visualize marker lists, cluster data and validate results. GeneCluster 2.0 greatly expands the data analysis capabilities of GeneCluster 1.0 by adding classification, class discovery(More)
Using gene expression data to classify tumor types is a very promising tool in cancer diagnosis. Previous works show several pairs of tumor types can be successfully distinguished by their gene expression patterns (Golub et al. 1999, Ben-Dor et al. 2000, Alizadeh et al. 2000). However, the simultaneous classification across a heterogeneous set of tumor(More)
Modern cancer treatment relies upon microscopic tissue examination to classify tumors according to anatomical site of origin. This approach is effective but subjective and variable even among experienced clinicians and pathologists. Recently, DNA microarray-generated gene expression data has been used to build molecular cancer classifiers. Previous work(More)
Immunohistochemistry (IHC) is a tool for visualizing protein expression that is employed as part of the diagnostic workup for the majority of solid tissue malignancies. Existing IHC methods use antibodies tagged with fluorophores or enzyme reporters that generate colored pigments. Because these reporters exhibit spectral and spatial overlap when used(More)
  • Michael Angelo, B Promentilla, Shermaine M Cortez, Regina Anne, Dc Papel, Bernadette M Tablada +1 other
  • 2016
Pore structure, tortuosity and permeability are considered key properties of porous materials such as cement pastes to understand their long-term durability performance. Three-dimensional image analysis techniques were used in this study to quantify pore size, effective porosity, tortuosity, and permeability from the X-ray computed tomography (CT) images of(More)