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SF3B1ness score: screening SF3B1 mutation status from over 60,000 transcriptomes based on a machine learning approach
View ORCID ProfileYuichi Shiraishi, Kenichi Chiba, Ai Okada
doi: https://doi.org/10.1101/572834
Yuichi Shiraishi
1National Cancer Center Research Institute
2National Cancer Center Center for Cancer Genomics and Advanced Therapeutics
3RIKEN Center for Advanced Intelligence Project
Kenichi Chiba
1National Cancer Center Research Institute
2National Cancer Center Center for Cancer Genomics and Advanced Therapeutics
Ai Okada
1National Cancer Center Research Institute
2National Cancer Center Center for Cancer Genomics and Advanced Therapeutics
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Posted March 09, 2019.
SF3B1ness score: screening SF3B1 mutation status from over 60,000 transcriptomes based on a machine learning approach
Yuichi Shiraishi, Kenichi Chiba, Ai Okada
bioRxiv 572834; doi: https://doi.org/10.1101/572834
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