Author

Gota Morota

Primary ORCID profile (0000-0002-3567-6911 · 30 papers)Unclaimed ORCID profile · follow to get notified of new preprints

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Same name, identified by ORCID

Gota MorotaiD30 papers · Virginia Tech

Biology Disciplines

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Genomics· 2 Genetics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:benchmarking· 1 Research Focus:cancer & tumor microenvironment· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:multiple species· 1 Organism:plant (other)· 1

Frequent Co-Authors

Bruno D Valente· 1 shared Daniel Gianola· 1 shared Francisco Peñagaricano· 1 shared Guilherme JM Rosa· 1 shared Kent Weigel· 1 shared Timothy Beissinger· 1 shared Timothy Mathes Beissinger· 1 shared

Activity by Year

2013-2016 · peak 2/yr

Co-Author Collaboration Network

7 top collaborators · 7 mutual co-author links

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1 shared paperGenomics

Bruno D Valente

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3 papers

Recent·Most cited

Medical subject heading (MeSH) annotations illuminate maize genetics and evolution

Timothy Beissinger, Gota Morota

The paper uses MeSH terms to provide biological insights into maize genetics and evolution by analyzing five maize datasets.

bioRxiv · Jul 13, 2016Genomics

MeSH-informed enrichment analysis and MeSH-guided semantic similarity among functional terms and gene products in chicken

Gota Morota, Timothy Mathes Beissinger, Francisco Peñagaricano

The paper develops MeSH-based tools for chicken gene analysis, showing MeSH improves enrichment and semantic similarity compared to GO.

bioRxiv · May 10, 2016Genetics

The causal meaning of genomic predictors and how it affects the construction and comparison of genome-enabled selection models

Bruno D Valente, Gota Morota, Guilherme JM Rosa, Daniel Gianola, Kent Weigel

This paper examines whether genomic predictors must represent causal effects to be useful for selection, showing that predictive ability alone is insufficient for causal learning in genomic selection models.

bioRxiv · Dec 21, 2013Genomics