Author

I. Rajcan

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Plant Biology· 2

Signature Assays, Organisms & Methods

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Research Focus:GWAS / association mapping· 2 Organism:plant (other)· 2 Research Focus:fine-mapping· 1 Assay:GWAS summary statistics· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1 Research Focus:variant calling· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

D. Torkamaneh· 2 shared A. Sreedasyam· 1 shared B. Valliyodan· 1 shared D. Tulpan· 1 shared E. Cober· 1 shared F. Belzile· 1 shared H. T. Nguyen· 1 shared J. Laroche· 1 shared

Activity by Year

2019-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersPlant Biology

D. Torkamaneh

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2 papers

Recent·Most cited

Machine Learning based Genome-Wide Association Studies for Uncovering QTL Underlying Soybean Yield and its Components

M. Yoosefzadeh Najafabadi, S. Torabi, D. Torkamaneh, D. Tulpan, I. Rajcan, M. Eskandari

This study uses machine learning algorithms in GWAS to identify QTL associated with soybean yield components, finding SVR outperforms conventional methods.

bioRxiv · Jun 24, 2021Plant Biology

Soybean Haplotype Map (GmHapMap): A Universal Resource for Soybean Translational and Functional Genomics

D. Torkamaneh, J. Laroche, B. Valliyodan, L. O'Donoughue, E. Cober, I. Rajcan, R. Vilela Abdelnoor, A. Sreedasyam, J. Schmutz, H. T. Nguyen, F. Belzile

The paper constructs a soybean haplotype map (GmHapMap) using whole-genome sequences, identifies a causal SNP for seed oil content, and predicts LOF mutations to aid in soybean genomics and breeding.

bioRxiv · Jan 29, 2019 · PreprintPlant Biology