Data/hora: 20/06/2024 23:00:12

Biblioteca(s): | Embrapa Agricultura Digital.
Data corrente: | 08/08/2002
Data da última atualização: | 30/01/2008
Autoria: | LIN, S. M.; JOHNSON, K. F. (ed.).
Afiliação: | Duke University Medical Center.
Título: | Methods of microarray data analysis: papers from CAMDA '00.
Ano de publicação: | 2002
Fonte/Imprenta: | Boston: Kluwer, 2002.
Páginas: | 189 p.
ISBN: | 0-7923-7564-5
Idioma: | Inglês
Notas: | Conference on the Critical Assessment of microarray Data Analysis (CAMDA), 2000.
Conteúdo: | Data mining and machine learning methods for microarray analysis. (Werner Dubitzky, Martin Granzow, Daniel Berrar). Evolutionary computation in microarray data analysis. ( Jason H. Moore and Joel S. Parker). Using non-parametric methods in the context of multiple testing to determine differentially expressed genes. (Gregory Grant, Elisabetta Manduchi, Christian Stoeckert, Jr.). Iterative linear regression by sector. (David B. Finkelstein, Rob Ewing, Jeremy Gollub, Frederik Sterky, Shauna Somerville, and J. Michael Cherry). A method to improve detection of disease using selectively expressed genes in microarray data. (Virgine Aris and Michael Recce). Computational analysis of leukemia microarray expression data using the GA-KNN method. (Leping Li, Lee. G. Pedersen, Thomas A. Darden and Clarice R. Weinberg). Classical statistical approaches to molecular classification of cancer from gene expression profiling. (Jun Lu, Sarah Hardy, Wen-Li Tao, Spencer Muse, Bruce Weir and Susan Spruill). Classification of acute leukemia based on DNA microarray gene expressions using partial least squares. (Danh V. Nguyen and David M. Rocke). Applying classification separability analysis to microarray data. (Zhen Zhang, Grier Page, and Hong Zhang). How many genes are needed for a discriminant microarray data analysis. (Wentian Li and Yaning Yang). Comparing symbolic and subsymbolic macjine learning approaches to classification of cancer and gene identification. (Werner Dubitzky, Martin Granzow, Daniel Berrar). Applying machine learning techniques to analysis of gene expression data: cancer diagnosis. (Kyu-Baek Hwang, Dong-Yeon Cho, Sang-Wook Park, Sung-Dong Kim, and Byoung-Tak Zhang).
Palavras-Chave: | Expressão de genes.
Thesagro: | Análise de Dados.
Thesaurus Nal: | DNA microarrays.
Categoria do assunto: | --
Registro original: | Embrapa Agricultura Digital (CNPTIA)
Exemplares: | CNPTIA - (8832-1) - ADC - LV - -- - 572.865 - LIN - 2002.00024 - DIS