Published May 9, 2018
| Version v1
Dataset
Open
Tools for prediction of tumor heterogeneity by a machine learning approach
Authors/Creators
- 1. Samsung Advanced Institute for Health Sciences & Technology, , Sungkyunkwan University
- 2. Samsung Genome Institute
Description
The package includes R codes and datasets. We applied three classification algorithms: Support Vector Machine, Random Forest, and Naïve Bayes. Datasets include tab-delimited files of mutation and gene expression profile for stomach cancer.
Files
Files
(32.5 MB)
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md5:a4326234ece890755d8442d2b43d3ba7
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md5:6611b6d044630c5ac00a8d3da4026bf0
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md5:c4a2d4df4476198d60ac1464638cec2b
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256.6 kB | Download |
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md5:a6f089ee96347d1550aaa1d2a4990652
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336.1 kB | Download |
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md5:a339130024fa9f0a4a234476279b7580
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1.5 kB | Download |
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md5:0f3b4a782ff3d8b5b62d7cc30988c787
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443 Bytes | Download |
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md5:0a0b02946cfbf4b4d40d8158e960bd88
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12.8 MB | Download |
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md5:1ea48b15b615e8b3ad7270361c363756
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19.1 MB | Download |