Sara V. Good

1.1k total citations
41 papers, 741 citations indexed

About

Sara V. Good is a scholar working on Public Health, Environmental and Occupational Health, Molecular Biology and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Sara V. Good has authored 41 papers receiving a total of 741 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Public Health, Environmental and Occupational Health, 6 papers in Molecular Biology and 6 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Sara V. Good's work include Pregnancy-related medical research (9 papers), Plant and animal studies (5 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Sara V. Good is often cited by papers focused on Pregnancy-related medical research (9 papers), Plant and animal studies (5 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Sara V. Good collaborates with scholars based in Canada, United States and Kazakhstan. Sara V. Good's 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 and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Sara V. Good

38 papers receiving 733 citations

Peers

Sara V. Good
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
Replace Shuang Tang with:
Shuang Tang China
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Federico Bonsembiante Italy
Nicholas J. Harding United Kingdom
Anh Dinh United States
Christophe Lefèvre Australia
Hanna Retallack United States
Paul Schliekelman United States
Joanne Berghout United States
Kirill Kryukov Japan
Shuang Tang China View profile →
Citations per field, relative to Sara V. Good
Sara V. Good · 1×
Citations per year, relative to Sara V. Good
Sara V. Good · 1×

Countries citing papers authored by Sara V. Good

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
# 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

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.

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