Mona Puggal
Impact in
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- Hemoglobinopathies and Related Disorders
- BRCA gene mutations in cancer
- Genetic Associations and Epidemiology
- Genomics and Rare Diseases
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- Iron Metabolism and Disorders
Papers in
- Genetics 2
- Hemoglobinopathies and Related Disorders 1
- BRCA gene mutations in cancer 1
- Genomics and Rare Diseases 1
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- Kruppel-like factors research 1
- Co-authors
- George Papanicolaou (3 shared papers)Cheryl Nelson (2 shared papers)Antonio Guasch (1 shared paper)Allison E. Ashley‐Koch (1 shared paper)Cashell E. Jaquish (2 shared papers)Guillaume Lettre (1 shared paper)Karen Soldano (1 shared paper)Marilyn J. Telen (1 shared paper)
- Journals
- Blood (1 paper)Circulation Cardiovascular Genetics (1 paper)Circulation Research (1 paper)Research Evaluation (1 paper)PubMed (1 paper)
- Partner nations
- United StatesCanada
In The Last Decade
Mona Puggal
5 papers receiving 75 citations
Peers
Comparison fields: 5 of 49
- Genetics 23
- Hematology 22
- Genetics 26
- Health Informatics 1
- Public Health, Environmental and Occupational Health 18
Countries citing papers authored by Mona Puggal
This map shows the geographic impact of Mona Puggal'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 Mona Puggal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mona Puggal more than expected).
Fields of papers citing papers by Mona Puggal
This network shows the impact of papers produced by Mona Puggal. 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 Mona Puggal. The network helps show where Mona Puggal may publish in the future.
Co-authors
The 25 scholars most cited alongside Mona Puggal, 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 | 2013 | 25 | |
| 2 | 2019 | 24 | |
| 3 | Research participants' opinions on genetic research and reasons for participation: a Jackson Heart Study focus group analysis. | 2014 | 16 |
| 4 | 2012 | 10 | |
| 5 | 2013 | 6 |
About Mona Puggal
Mona Puggal is a scholar working on Genetics, Molecular Biology, Genetics, Statistical and Nonlinear Physics and Public Health, Environmental and Occupational Health, having authored 5 papers that have together received 81 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (1 paper), Kruppel-like factors research (1 paper), Cancer Genomics and Diagnostics (1 paper), Hemoglobinopathies and Related Disorders (1 paper), BRCA gene mutations in cancer (1 paper), Genomics and Rare Diseases (1 paper), scientometrics and bibliometrics research (1 paper) and Ethics in Clinical Research (1 paper). The work is most often cited by research in Genetics (23 citations), Hematology (22 citations), Genetics (26 citations), Health Informatics (1 citation) and Public Health, Environmental and Occupational Health (18 citations). Mona Puggal has collaborated with scholars based in United States and Canada. Frequent co-authors include George Papanicolaou, Cheryl Nelson, Antonio Guasch, Allison E. Ashley‐Koch, Cashell E. Jaquish, Guillaume Lettre, Karen Soldano, Marilyn J. Telen, Melanie E. Garrett and Donna Antoine‐LaVigne. Their work appears in journals such as Blood, Circulation Cardiovascular Genetics, Circulation Research, Research Evaluation and PubMed.
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.