| 1. |
- Autio, Reija, et al.
(författare)
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A method for finding putative causes of gene expression variation
- 2004
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Ingår i: 2nd TICSP Workshop on Computational Systems Biology, WCSB 2004 : Silja Opera, Helsinki-St. Petersburg, June 14 - 16, 2004 - Silja Opera, Helsinki-St. Petersburg, June 14 - 16, 2004. - 1456-2774. - 9521512040 ; 24, s. 29-30
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The majority of microarray studies evaluate gene ex- pression differences between various specimens or con- ditions. However, the causes of this variability often re- main unknown. Our aim is to identify underlying causes of these patterns, a process that would eventually enable a mechanistic understanding of the deregulation of gene expression in cancer. The procedure consists of three phases: pre-processing, data integration and statistical analysis. We have applied the strategy to identify genes that are overexpressed due to amplification in breast cancer. The data were obtained from 14 breast cancer cell lines, which were subjected to cDNA microarray based copy number and expression experiments. The re- sult of the analysis was a list that consisted of 92 genes. This set includes several genes that are known to be both overexpressed and amplified in breast cancer. The com- plete study was published in Journal of the Franklin In- stitute 2004, and in this paper we focus on the main issues of the study.
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| 2. |
- Hautaniemi, Sampsa, et al.
(författare)
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A Strategy for Identifying Putative Causes of Gene Expression Variation in Human Cancer
- 2002
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Ingår i: Workshop on Genomic Signal Processing and Statistics (GENSIPS).
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Konferensbidrag (refereegranskat)abstract
- There is often a need to predict the impact of alterations in one variable on another variable. This is especially the case in cancer research, where much effort has been made to carry out large-scale gene expression screening by microarray techniques. However, the causes of this variability from one cancer to another and from one gene to another often remain unknown. In this study we present a systematic procedure for finding genes whose expression is altered by an intrinsic or extrinsic explanatory phenomenon. The procedure has three stages: preprocessing, data integration and statistical analysis. We tested and verified the utility of this approach in a study, where expression and copy number of 13,824 genes were determined in 14 breast cancer samples. The expression of 270 genes could be explained by the variability of gene copy number. These genes may represent an important set of primary, genetically “damaged” genes that drive cancer progression.
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