56 skills found · Page 1 of 2
xuanxu / NimbusNimbus is a Ruby gem to implement Random Forest algorithms in a genomic selection context
YinLiLin / KAML:bicyclist: Kinship Adjusted Multi-Loci Best Linear Unbiased Prediction
MarcooLopez / Genomic SelectionNo description available
xiaolei-lab / Hiblup:surfer: HIBLUP is an Integration of Statistical Methods Under BLUP Framework for Genomic Selection and Prediction
jendelman / StageWisetwo-stage analysis of multi-environment trials for genomic selection and GWAS
ChenHuaLab / CEGAInferring natural selection by comparative population genomic analysis across species
FJingxian / JanusXA high-performance, ALL-in-ONE suite for quantitative genetics that unifies genome-wide association studies (GWAS) and genomic selection (GS).
RenqiChen / Genomic Selection[IJCAI 2024] An Embarrassingly Simple Approach to Enhance Transformer Performance in Genomic Selection for Crop Breeding
frahik / BMTMEBayesian Multi-Trait Multi-Environment for genomic selection[R package] [Dev version]
perpdgo / Lme4GSlme4 for Genomic Selection
cma2015 / G2PG2P is an integrated genomic selection (GS) package for predicting phenotypes from genotypes. It includes 15 GS algorithms and 13 evaluation measurements.
wodanaz / AdaptiPhyThis computational method has been published in BMC genomics as: "Identifying branch-specific positive selection throughout the regulatory genome using an appropriate proxy neutral"
vangiangtran / BWGS2024 BreedWheat Genomic Selection pipeline
grimmlab / EasyPhenoeasyPheno: a model agnostic phenotype prediction framework
cran / RrBLUP:exclamation: This is a read-only mirror of the CRAN R package repository. rrBLUP — Ridge Regression and Other Kernels for Genomic Selection. Homepage: <https://potatobreeding.cals.wisc.edu/software/>
azodichr / GenomicPrediction 2018Influence of algorithms, parameter choice, and feature selection on genomic prediction accuracy
jingwanglab / Widespread Linked SelectionScripts for Wang et al (2020) Evidence for widespread selection in shaping the genomic landscape during speciation of Populus.
dyneth02 / Genome Based Disorder Prediction SystemMachine learning system for predicting genetic disorders using genomic, clinical, and demographic data. Implements robust preprocessing, feature selection, and multi-model classification (RF, XGBoost, LightGBM, CatBoost) with cross-validation to support early, data-driven genetic risk assessment.
wolfemd / GenomicMateSelectRGenomic Mate Selection
azodichr / TF GenomicSelectionGenomic Selection using Neural Networks implemented in TensorFlow
