Bayesian variable selection for high-dimensional data with an ordinal response: identifying genes associated with prognostic risk group in acute myeloid leukemia is a research paper published in BMC Bioinformatics (2021). On theSindex it has a DataRank of 0. It has been cited 5 times.
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NCI NIH HHS
Grant: R03 CA245771
National Institutes of Health
Grant: 1R03CA245771-01
High-dimensional variable selection and prediction of ordinal pathological response data
FWCI
0.79
Citation Percentile
0.7%
Citation Trend
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Keywords
Sustainable Development Goals
Additional file 1 of Bayesian variable selection for high-dimensional data with an ordinal response: identifying genes associated with prognostic risk group in acute myeloid leukemia
Additional file 1 of Bayesian variable selection for high-dimensional data with an ordinal response: identifying genes associated with prognostic risk group in acute myeloid leukemia
Additional file 2 of Bayesian variable selection for high-dimensional data with an ordinal response: identifying genes associated with prognostic risk group in acute myeloid leukemia
Additional file 2 of Bayesian variable selection for high-dimensional data with an ordinal response: identifying genes associated with prognostic risk group in acute myeloid leukemia