Author

Nicholas S. Kaczmar

Cornell University

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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Genetics· 3 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 4 Organism:zebrafish· 3 Research Focus:GWAS / association mapping· 2 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Research Focus:genome assembly· 1 Assay:GWAS summary statistics· 1

Frequent Co-Authors

Michael A. GoreiD· 4 shared C. Robin BuelliD· 2 shared Di WuiD· 2 shared Edward S. BuckleriD· 2 shared James Chamness· 2 shared John P. HamiltoniD· 2 shared Matheus BaseggioiD· 2 shared Dean DellaPennaiD· 1 shared

Activity by Year

2020-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

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4 shared papersGenetics

Michael A. GoreORCID

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Author profile →

4 papers

Recent·Most cited

Spatio-temporal modeling of high-throughput multi-spectral aerial images improves agronomic trait genomic prediction in hybrid maize

Nicolás Morales, Mahlet Teka Anche, Nicholas S. Kaczmar, Nicholas K. Lepak, Pengzun Ni, M. Cinta Romay, Nicholas Santantonio, Edward S. Buckler, Michael A. Gore, Lukas A. Mueller, Kelly R. Robbins

The paper improves genomic prediction of agronomic traits in maize by integrating spatio-temporal modeling of multi-spectral aerial images with genetic data.

Genetics · Mar 12, 2024Peer-reviewedGenetics

Transcriptome-wide association and prediction for carotenoids and tocochromanols in fresh sweet corn kernels

Jenna L. Hershberger, Ryokei Tanaka, Joshua C. Wood, Nicholas S. Kaczmar, Di Wu, John P. Hamilton, Dean DellaPenna, C. Robin Buell, Michael A. Gore

This study uses transcriptome-wide association and prediction to identify genes related to carotenoid and tocochromanol levels in sweet corn and shows transcriptomic data improve predictive models.

The Plant Genome · Mar 8, 2022Peer-reviewedGenomics

Genome-wide association study suggests an independent genetic basis of zinc and cadmium concentrations in fresh sweet corn kernels

Matheus Baseggio, Matthew Murray, Di Wu, Greg Ziegler, Nicholas S. Kaczmar, James Chamness, John P. Hamilton, C. Robin Buell, Olena K. Vatamaniuk, Edward S. Buckler, Margaret Elizabeth Smith, Ivan R. Baxter, William F. Tracy, Michael A. Gore

This study identifies genetic factors influencing zinc and cadmium concentrations in sweet corn kernels through genome-wide association analysis.

G3 Genes Genomes Genetics · May 28, 2021Peer-reviewedGenetics

Genome-wide association study for maize leaf cuticular conductance identifies candidate genes involved in the regulation of cuticle development

Meng Lin, Susanne Matschi, Miguel F. Vasquez, James Chamness, Nicholas S. Kaczmar, Matheus Baseggio, Michael Miller, Ethan L. Stewart, Pengfei Qiao, Michael J. Scanlon, Isabel Molina, Laurie G. Smith, Michael A. Gore

This study identifies candidate genes associated with maize leaf cuticular conductance through genome-wide association and provides insights for improving drought-tolerant maize breeding.

G3 Genes Genomes Genetics · Mar 17, 2020Peer-reviewedGenetics