Daniel Gianola
- Genetics top 0.01%
- Genetic and phenotypic traits in livestock 296
- Genetic Mapping and Diversity in Plants and Animals 177
- Agronomy and Crop Science top 0.05%
- Milk Quality and Mastitis in Dairy Cows 45
- Reproductive Physiology in Livestock 45
- Animal Science and Zoology top 0.05%
- Animal Nutrition and Physiology 30
- Effects of Environmental Stressors on Livestock 21
- Small Animals top 0.05%
- Animal Behavior and Welfare Studies 33
- Plant Science top 0.1%
- Genetics and Plant Breeding 121
Daniel Gianola
346 papers receiving 15.9k citations
Hit Papers
Peers
Comparison fields: 5 of 177
- Genetics 13.8k
- Agronomy and Crop Science 3.7k
- Animal Science and Zoology 2.5k
- Small Animals 1.6k
- Plant Science 7.1k
Countries citing papers authored by Daniel Gianola
This map shows the geographic impact of Daniel Gianola'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 Daniel Gianola with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Gianola more than expected).
Fields of papers citing papers by Daniel Gianola
This network shows the impact of papers produced by Daniel Gianola. 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 Daniel Gianola. The network helps show where Daniel Gianola may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Daniel Gianola, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 25 | |
| 2 | 2019 | 19 | |
| 3 | 2019 | 1 | |
| 4 | Bayesian inference of genomic similarity among individuals from mark- ers and phenotypes | 2018 | 1 |
| 5 | 2015 | 14 | |
| 6 | Genome-enabled Prediction of Complex Traits with Kernel Methods: What Have We Learned? | 2014 | 14 |
| 7 | 2013 | 32 | |
| 8 | 2009 | 98 | |
| 9 | 2008 | 55 | |
| 10 | 2007 | 44 | |
| 11 | 2006 | 67 | |
| 12 | 2006 | 56 | |
| 13 | 2005 | 16 | |
| 14 | 2003 | 61 | |
| 15 | 2003 | 30 | |
| 16 | 2003 | 16 | |
| 17 | Preliminary report on international dairy sire evaluation using individual performance records | 2000 | 2 |
| 18 | 1994 | 48 | |
| 19 | 1987 | 2 | |
| 20 | 1985 | 122 |
About Daniel Gianola
Daniel Gianola is a scholar working on Genetics, Agronomy and Crop Science and Animal Science and Zoology, having authored 353 papers that have together received 16.6k indexed citations. Recurring topics across this work include Genetic and phenotypic traits in livestock (296 papers), Genetic Mapping and Diversity in Plants and Animals (177 papers), Genetics and Plant Breeding (121 papers), Milk Quality and Mastitis in Dairy Cows (45 papers), Reproductive Physiology in Livestock (45 papers), Animal Behavior and Welfare Studies (33 papers), Animal Nutrition and Physiology (30 papers) and Effects of Environmental Stressors on Livestock (21 papers). The work is most often cited by research in Genetics (13.8k citations), Agronomy and Crop Science (3.7k citations) and Animal Science and Zoology (2.5k citations). Daniel Gianola has collaborated with scholars based in United States, Norway and Germany. Frequent co-authors include K.A. Weigel, Guilherme J. M. Rosa, Daniel Sørensen, Rohan L. Fernando, Gustavo de los Campos, José Crossa, JL Foulley, B. Heringstad, Paulino Pérez‐Rodríguez and I. Misztal. Their work appears in journals such as Journal of Dairy Science, Genetics Selection Evolution, Genetics, Journal of Animal Science and Theoretical and Applied Genetics.
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.