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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Dechang Xu Jianzhong Li |
| Copyright Year | 2013 |
| Description | Author affiliation: Sch. of Food Sci. & Eng., Harbin Inst. of Technol., Harbin, China (Dechang Xu) || Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin, China (Jianzhong Li) |
| Abstract | To Model the protein sub-cellular localization pattern which responds to drugs' treatment is an important problem for medical applications named as high content screening (HCS) with bio-imaging and machine learning. Traditionally, at least, three channels' images have to be retrieved for auto-focusing and segmentation on DNA channel, background correction on auto-fluorescence channel and protein sub-cellular localization analysis on GFP channel which is a time consuming and error accumulating procedure. An automatic classification of Single-channel Protein Sub-cellular Location Fluorescence Images without segmentation is desired for speeding up the pattern analysis. But in the real world, the data imbalance often occurred and affected the classification accuracy. By now there are a variety of approaches proposed for improved the classification accuracy including the re-sampling and reweighting. This experiment engaged in comparing existed solutions for further research. |
| Sponsorship | IEEE Comput.Soc. |
| Starting Page | 68 |
| Ending Page | 70 |
| File Size | 1519756 |
| Page Count | 3 |
| File Format | |
| ISBN | 9781479913091 |
| DOI | 10.1109/BIBM.2013.6732766 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-12-18 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Decision support systems Random forest protein sub-cellular localization unbalance data classification |
| Content Type | Text |
| Resource Type | Article |
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