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An open API service providing mapping between scientific papers and software projects that are mentioned in them.

Papers: 10.1007/s00122-017-3030-1

https://doi.org/10.1007/s00122-017-3030-1

Predictive ability of genomic selection models in a multi-population perennial ryegrass training set using genotyping-by-sequencing

Cited by: 49
Author(s): Marty J. Faville, Siva Ganesh, Mingshu Cao, M. Z. Z. Jahufer, Timothy P. Bilton, H. S. Easton, Douglas L. Ryan, Jason A. K. Trethewey, M. P. Rolston, Andrew G. Griffiths, Roger Moraga, Casey Flay, Joana Schmidt, Rachel Tan, Brent Barrett
Published: over 7 years ago

Software Mentions 8

bioconductor: impute
impute: Imputation for microarray data
Papers that mentioned: 63
Very Likely Science (100)
cran: glmnet
Lasso and Elastic-Net Regularized Generalized Linear Models
Papers that mentioned: 1,607
Very Likely Science (100)
cran: ranger
A Fast Implementation of Random Forests
Papers that mentioned: 91
Very Likely Science (100)
cran: rrBLUP
Ridge Regression and Other Kernels for Genomic Selection
Papers that mentioned: 263
Very Likely Science (93)
pypi: glmnet
Python wrapper for glmnet
Papers that mentioned: 1,607
Very Likely Science (100)
pypi: impute
Gene imputation tools for founder populations.
Papers that mentioned: 63
Very Likely Science (65)
pypi: MissForest
Best imputation method.
Papers that mentioned: 52
Very Likely Science (75)
pypi: ranger
A Python package for the manipulation of Range objects
Papers that mentioned: 91
Very Likely Science (100)