Gota Morota
- Genetics top 2%
- Plant Science top 5%
- Animal Science and Zoology top 2%
- Molecular Biology
- Agronomy and Crop Science top 5%
- Co-authors
- Daniel GianolaHarkamal WaliaMalachy T. CampbellGuilherme J. M. RosaMehdi MomenMasanori KoyamaRostam Abdollahi-ArpanahiRicardo Vieira Ventura
- Topics
- Genetic Mapping and Diversity in Plants and Animals (56 papers)Genetic and phenotypic traits in livestock (54 papers)Genetics and Plant Breeding (29 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEPLANT PHYSIOLOGY
- Partner nations
- United StatesBrazilUnited Kingdom
In The Last Decade
Gota Morota
89 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 127
- Genetics 931
- Plant Science 708
- Animal Science and Zoology 269
- Molecular Biology 182
- Agronomy and Crop Science 172
Countries citing papers authored by Gota Morota
This map shows the geographic impact of Gota Morota's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Gota Morota with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gota Morota more than expected).
Fields of papers citing papers by Gota Morota
This network shows the impact of papers produced by Gota Morota. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gota Morota. The network helps show where Gota Morota may publish in the future.
Co-authorship network of co-authors of Gota Morota
This figure shows the co-authorship network connecting the top 25 collaborators of Gota Morota. A scholar is included among the top collaborators of Gota Morota based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gota Morota. Gota Morota is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 4 | |
| 6 | 5 | |
| 7 | 2 | |
| 8 | 11 | |
| 9 | 6 | |
| 10 | 16 | |
| 11 | 15 | |
| 12 | 9 | |
| 13 | 25 | |
| 14 | 23 | |
| 15 | 21 | |
| 16 | Stronger measures of genomic connectedness enhance prediction accuracies across management units | 1 |
| 17 | 8 | |
| 18 | 14 | |
| 19 | MeSH ORA framework: R/Bioconductor\npackages to support MeSH over-representation\nanalysis | 34 |
| 20 | Genome-enabled Prediction of Complex Traits with Kernel Methods: What Have We Learned? | 14 |
About Gota Morota
Gota Morota is a scholar working on Genetics, Animal Science and Zoology and Small Animals, having authored 99 papers that have together received 1.5k indexed citations. Recurring topics across this work include Genetic Mapping and Diversity in Plants and Animals (56 papers), Genetic and phenotypic traits in livestock (54 papers) and Genetics and Plant Breeding (29 papers). The work is most often cited by research in Genetics (931 citations), Animal Science and Zoology (269 citations) and Small Animals (143 citations). Gota Morota has collaborated with scholars based in United States, Brazil and United Kingdom. Frequent co-authors include Daniel Gianola, Harkamal Walia, Malachy T. Campbell, Guilherme J. M. Rosa, Mehdi Momen, Masanori Koyama, Rostam Abdollahi-Arpanahi, Ricardo Vieira Ventura, Samodha C. Fernando and Fabyano Fonseca e Silva. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and PLANT PHYSIOLOGY.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.