Proteomic data analysis of glioma cancer stem-cell lines based on novel nonlinear dimensional data reduction techniques Journal Article
| Authors: | Lespinats, S.; Pinker-Domenig, K.; Wengert, G.; Houben, I.; Lobbes, M.; Stadlbauer, A.; Meyer-Bäse, A.; Meyer-Base, A. D.; Dai, L.; Zheng, Y.; Chu, H. |
| Article Title: | Proteomic data analysis of glioma cancer stem-cell lines based on novel nonlinear dimensional data reduction techniques |
| Title Series: | Sensing and Analysis Technologies for Biomedical and Cognitive Applications 2016 |
| Abstract: | Glioma-derived cancer stem cells (GSCs) are tumor-initiating cells and may be refractory to radiation and chemotherapy and thus have important implications for tumor biology and therapeutics. The analysis and interpretation of large proteomic data sets requires the development of new data mining and visualization approaches. Traditional techniques are insufficient to interpret and visualize these resulting experimental data. The emphasis of this paper lies in the application of novel approaches for the visualization, clustering and projection representation to unveil hidden data structures relevant for the accurate interpretation of biological experiments. These qualitative and quantitative methods are applied to the proteomic analysis of data sets derived from the GSCs. The achieved clustering and visualization results provide a more detailed insight into the protein-level fold changes and putative upstream regulators for the GSCs. However the extracted molecular information is insufficient in classifying GSCs and paving the pathway to an improved therapeutics of the heterogeneous glioma. © 2016 SPIE. |
| Keywords: | chemotherapy; cytology; proteomics; cell culture; tumors; stem cells; molecular biology; information analysis; visualization; diseases; cells; reduction; data visualization; cancer stem cells; classification (of information); data reduction; data mining; biological experiments; flow visualization; nonlinear dimensional data reduction; glioma-derived cancer stem cells; antenna lobes; quantitative method; reduction techniques; traditional techniques; visualization results; molecular information |
| Journal Title: | Proceedings of SPIE |
| Volume: | 9871 |
| ISSN: | 0277-786X |
| Publisher: | SPIE |
| Date Published: | 2016-04-16 |
| Start Page: | 98710T-1 |
| End Page: | 98710T-8 |
| Language: | English |
| DOI: | 10.1117/12.2229133 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Conference Paper -- Conference code: 124026 -- Export Date: 2 November 2016 -- The Society of Photo-Optical Instrumentation Engineers (SPIE) -- 17 April 2016 through 18 April 2016 -- Source: Scopus |
