Sara V. Good
- Molecular Biology
- Public Health, Environmental and Occupational Health
- Ecology, Evolution, Behavior and Systematics top 10%
- Pediatrics, Perinatology and Child Health top 10%
- Genetics
- Co-authors
- Sergey YegorovMiriam Monserrat FerrerDorin ComaniciuAnuraag ShrivastavRuey‐Chyi SuT. Blake BallJan BogerdS. Kevin Zhou
- Topics
- Pregnancy-related medical research (9 papers)Plant and animal studies (5 papers)Domain Adaptation and Few-Shot Learning (4 papers)
- Cited by
- Ecology, Evolution, Behavior and SystematicsPediatrics, Perinatology and Child HealthParasitology
- Journals
- Nature CommunicationsSHILAP Revista de lepidopterologíaPLoS ONE
- Partner nations
- CanadaUnited StatesKazakhstan
In The Last Decade
Sara V. Good
38 papers receiving 733 citations
Peers
Comparison fields: 5 of 107
- Molecular Biology 195
- Public Health, Environmental and Occupational Health 126
- Ecology, Evolution, Behavior and Systematics 116
- Pediatrics, Perinatology and Child Health 104
- Genetics 104
Countries citing papers authored by Sara V. Good
This map shows the geographic impact of Sara V. Good'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 Sara V. Good with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sara V. Good more than expected).
Fields of papers citing papers by Sara V. Good
This network shows the impact of papers produced by Sara V. Good. 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 Sara V. Good. The network helps show where Sara V. Good may publish in the future.
Co-authorship network of co-authors of Sara V. Good
This figure shows the co-authorship network connecting the top 25 collaborators of Sara V. Good. A scholar is included among the top collaborators of Sara V. Good 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 Sara V. Good. Sara V. Good is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 5 | |
| 6 | 4 | |
| 7 | 22 | |
| 8 | 7 | |
| 9 | 30 | |
| 10 | The relaxin receptor as a therapeutic target - perspectives from evolution Cheek for updates and drug targeting | 1 |
| 11 | 6 | |
| 12 | 5 | |
| 13 | 5 | |
| 14 | 26 | |
| 15 | 5 | |
| 16 | 20 | |
| 17 | 10 | |
| 18 | 43 | |
| 19 | 20 | |
| 20 | 15 |
About Sara V. Good
Sara V. Good is a scholar working on Occupational Therapy, Virology and Public Health, Environmental and Occupational Health, having authored 41 papers that have together received 741 indexed citations. Recurring topics across this work include Pregnancy-related medical research (9 papers), Plant and animal studies (5 papers) and Domain Adaptation and Few-Shot Learning (4 papers). The work is most often cited by research in Ecology, Evolution, Behavior and Systematics (116 citations), Pediatrics, Perinatology and Child Health (104 citations) and Parasitology (31 citations). Sara V. Good has collaborated with scholars based in Canada, United States and Kazakhstan. Frequent co-authors include Sergey Yegorov, Miriam Monserrat Ferrer, Dorin Comaniciu, Anuraag Shrivastav, Ruey‐Chyi Su, T. Blake Ball, Jan Bogerd, S. Kevin Zhou, Adriana Suarez‐Gonzalez and Gustavo Carneiro. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.
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.