Marker Density Optimization
Marker Density Optimization is a methodological approach in genomic prediction that determines the optimal number and distribution of genetic markers required to maximize predictive accuracy while minimizing genotyping costs and computational burden.
24
Publications
1.5K
Citations
134
Authors
68
Institutions
Publications per year
2017–2026
6
Parents
24
Selective Mapping: A Strategy for Optimizing the Construction of High-Density Linkage Maps
Todd Vision, Daniel G. Brown, David B. Shmoys et al. · Genetics · 2000 · 127 citations · Full text
An imputation platform to enhance integration of rice genetic resources
Diane Wang, Francisco Agosto-Perez, Dmytro Chebotarov et al. · Nature Communications · 2018 · 93 citations · Full text
Agriculture, Crop Sciences, Genetics +17
1–5 of 24
134
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1
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1
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International Center for Agricultural Research in the Dry Areas, Syria
1 publications · 18 citations
1
h-index
1
h-index
1–5 of 134
68
Michigan State University
East Lansing, United States
3 h-index
5 publications
764 citations

Cornell University
Ithaca, United States
2 h-index
9 publications
1K citations
Wageningen University & Research
Wageningen, The Netherlands
2 h-index
7 publications
341 citations
University of Kassel
Kassel, Germany
1 h-index
1 publications
47 citations
Isuzu Advanced Engineering Center (Japan)
Fujisawa, Japan
1 h-index
2 publications
50 citations
Institute of Plant Protection
Beijing, China
1 h-index
1 publications
50 citations
Centro Internacional de Mejoramiento de Maíz Y Trigo
Texcoco, Mexico
1 h-index
6 publications
1.4K citations
Sichuan Academy of Agricultural Sciences
Chengdu, China
1 h-index
1 publications
50 citations
1–8 of 68
4 publications · 458 citations
4
h-index
2 publications · 40 citations
2
h-index
GSE · 2 publications · 139 citations
2
h-index
1 publications · 235 citations
1
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1 publications · 10 citations
1
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1–5