Computational Methods for Gene Expression-Based Tumor Classification
نویسندگان
چکیده
منابع مشابه
Computational methods for gene expression-based tumor classification.
Gene expression profiles may offer more or additional information than classic morphologic- and histologic-based tumor classification systems. Because the number of tissue samples examined is usually much smaller than the number of genes examined, efficient data reduction and analysis methods are critical. In this report, we propose a principal component and discriminant analysis method of tumo...
متن کاملClassification and Computational Methods in Gene Expression Data Analysis
We compared the power of gene expression measurements with that of conventional prognostic markers, i.e., clinical, histo-pathological, and cell biological parameters, for predicting distant metastases in breast cancer patients using both establishedprognostic indices (e.g., the Nottingham Prognostic Index (NPI)) and novel combinations of conventional markers. We usedpublicly availa...
متن کاملDiagonal Discriminant Analysis for Gene- Expression Based Tumor Classification
A reliable and accurate tumor classification is crucial for successful diagnosis and treatment of cancer diseases. With the recent advances in molecular genetics, it is possible to measure the expression levels of thousands of genes simultaneously. Thus, it is feasible to have a complete understanding the molecular markers among tumors and make a more successful and accurate diagnosis. A common...
متن کاملFeature (gene) selection in gene expression-based tumor classification.
There is increasing interest in changing the emphasis of tumor classification from morphologic to molecular. Gene expression profiles may offer more information than morphology and provide an alternative to morphology-based tumor classification systems. Gene selection involves a search for gene subsets that are able to discriminate tumor tissue from normal tissue, and may have either clear biol...
متن کاملIdentifying tumor origin using a gene expression-based classification map.
Identifying the primary site in cases of metastatic carcinoma of unknown origin has profound clinical importance in managing cancer patients. Although transcriptional profiling promises molecular solutions to this clinical challenge, simpler and more reliable methods for this purpose are needed. A training set of 11 serial analysis of gene expression (SAGE) libraries was analyzed using a combin...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: BioTechniques
سال: 2000
ISSN: 0736-6205,1940-9818
DOI: 10.2144/00296bc02