Oncogenes and Subtypes of Diffuse Large B-Cell Lymphoma Discoveries from Microarray Database
- Ching-Hao Lai 0, Jun-Dong Chang, Meng-Hsiun Tsai
- Corresponding Author
- Ching-Hao Lai
0National Chung Hsing Univ.
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- https://doi.org/10.2991/jcis.2006.224How to use a DOI?
- Microarray, Analysis of Variance (ANOVA), hierarchical clustering, Diffuse Large B-Cell Lymphoma (DLBCL), data mining.
- This paper presents an effective analysis scheme for Diffuse Large B-Cell Lymphoma (DLBCL) microarray datasets. Analysis of variable (ANOVA) is a well known statistics tools. It is useful to get the oncogenes to distinguish the normal and cancerous tissues. But, it can not further obtain the sub-types of cancerous tissues effectively. Hierarchical clustering is a well known analysis method for data mining. Therefore, it is also useful and fit to classify oncogenes to obtain some sub-types. ANOVA and hierarchical clustering both are employed to help us analyze B-cell Lymphoma datasets. In our analysis results, ANOVA can obtain 11 oncogenes of DLBCL from Stanford DLBCL microarray database successfully and accurately. Then, the 11 oncogenes are used for hierarchical clustering to identify the sub-types of cancerous tissues. In our hierarchical clustering analysis, we use 20 GC B-like DLBCL and 15 Activated B-like DLBCL actual samples used for analyzing. The analysis result shows that the hierarchical clustering can distinguish GC B-like DLBCL and Activated B-like DLBCL samples successfully.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
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TY - CONF AU - Ching-Hao Lai AU - Jun-Dong Chang AU - Meng-Hsiun Tsai PY - NaN/NaN DA - NaN/NaN TI - Oncogenes and Subtypes of Diffuse Large B-Cell Lymphoma Discoveries from Microarray Database BT - 9th Joint International Conference on Information Sciences (JCIS-06) PB - Atlantis Press UR - https://doi.org/10.2991/jcis.2006.224 DO - https://doi.org/10.2991/jcis.2006.224 ID - LaiNaN/NaN ER -