Author

D. Grattapaglia

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· 3

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:gene regulatory network inference· 2 Organism:plant (other)· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Research Focus:genome assembly· 1

Frequent Co-Authors

A. A. Carrell· 1 shared A. Lipzen· 1 shared A. Medlin· 1 shared A. Muchlinski· 1 shared A. Sreedasyam· 1 shared B. Weers· 1 shared C. A. P. Pacheco· 1 shared C. Daum· 1 shared

Activity by Year

2019-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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1 shared paperPlant Biology

A. A. Carrell

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3 papers

Recent·Most cited

High density linkage to physical mapping in a unique Tall x Dwarf Coconut (Cocos nucifera L.) outbred F2 uncovers a major QTL for flowering time colocalized with the FLOWERING LOCUS T (FT)

D. Grattapaglia, W. B. d. S. Alves, C. A. P. Pacheco

This study identifies a major QTL for flowering time in coconut, colocalized with the FT gene, and shows its association with precocity traits.

bioRxiv · Jan 31, 2024 · PreprintPlant Biology

JGI Plant Gene Atlas: An updateable transcriptome resource to improve structural annotations and functional gene descriptions across the plant kingdom

A. Sreedasyam, C. Plott, M. S. Hossain, J. T. Lovell, J. Grimwood, J. W. Jenkins, C. Daum, K. Barry, J. Carlson, S. Shu, J. Phillips, M. Amirebrahimi, M. Zane, M. Wang, D. Goodstein, , E Cooper

The paper introduces the JGI Plant Gene Atlas, a resource that improves gene function annotations by analyzing transcript abundance across 18 species and 604 tissues, identifying 64,620 genes with unknown functions.

bioRxiv · Sep 30, 2022 · PreprintPlant Biology

Enviromics in breeding: applications and perspectives on envirotypic-assisted selection

R. T. Resende, H.-P. Piepho, O. B. Silva-Junior, F. F. Silva, M. D. V. Resende, D. Grattapaglia

This paper introduces Enviromics and the GIS-GE method to improve breeding by predicting genotype performance across environments using environmental markers.

bioRxiv · Aug 6, 2019Plant Biology