An experiential analysis of microarray time series data of cancer metastasis using XMAS
Time series microarray analysis provides an invaluable insight into genetic progression of biological processes such as tumor metastasis. Many algorithms sustain statistical analysis which limits user interaction. We use XMAS to extract knowledge from datasets which increases human-computer synergy,...
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| creator | Samuel, Azariah A. Suresh, Xavier M. Devi, Vaishnavi M. Kumari, Radha |
| description | Time series microarray analysis provides an invaluable insight into genetic progression of biological processes such as tumor metastasis. Many algorithms sustain statistical analysis which limits user interaction. We use XMAS to extract knowledge from datasets which increases human-computer synergy, thus providing increased analysis experience. Cancer Metastasis involves complex biological pathway information. The domain knowledge to deciphering these complex data can be integrated using XMAS which offers visual interaction and interoperable operators. Thus XMAS differs from the traditional `sit back' approach of traditional systems to offer `sit forward' analysis to validate results in an unparalleled serendipitous manner. |
| doi_str_mv | 10.1109/TISC.2011.6169085 |
| format | Conference Proceeding |
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| ispartof | 3rd International Conference on Trendz in Information Sciences & Computing (TISC2011), 2011, p.61-64 |
| issn | 2325-5919 |
| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Cancer metastasis Computers Human computer interaction sit forward analysis Time series analysis Trajectory XMAS |
| title | An experiential analysis of microarray time series data of cancer metastasis using XMAS |
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