Danielle Rasooly
Impact in
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- Genetic Associations and Epidemiology
Papers in
- Genetics 7
- Genetic Associations and Epidemiology 7
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- Bioinformatics and Genomic Networks 2
- Co-authors
- Chirag J. Patel (5 shared papers)Gina M. Peloso (2 shared papers)Arjun K. Manrai (1 shared paper)Ioanna Tzoulaki (1 shared paper)Yixuan He (1 shared paper)Claudia Giambartolomei (1 shared paper)Muin J. Khoury (6 shared papers)John P. A. Ioannidis (1 shared paper)
- Journals
- Current Protocols (2 papers)Arthritis Care & Research (1 paper)Diabetes Care (1 paper)American Journal of Obstetrics and Gynecology (1 paper)CPT Pharmacometrics & Systems Pharmacology (1 paper)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Danielle Rasooly
13 papers receiving 227 citations
Peers
Comparison fields: 5 of 64
- Genetics 61
- Periodontics 5
- Cancer Research 16
- Health, Toxicology and Mutagenesis 14
- Gastroenterology 5
Countries citing papers authored by Danielle Rasooly
This map shows the geographic impact of Danielle Rasooly'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 Danielle Rasooly with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danielle Rasooly more than expected).
Fields of papers citing papers by Danielle Rasooly
This network shows the impact of papers produced by Danielle Rasooly. 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 Danielle Rasooly. The network helps show where Danielle Rasooly may publish in the future.
Co-authors
The 25 scholars most cited alongside Danielle Rasooly, 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 | 2019 | 58 | |
| 2 | 2021 | 51 | |
| 3 | 2021 | 48 | |
| 4 | 2022 | 20 | |
| 5 | 2019 | 10 | |
| 6 | 2023 | 9 | |
| 7 | 2012 | 9 | |
| 8 | 2025 | 7 | |
| 9 | 2023 | 6 | |
| 10 | 2017 | 4 | |
| 11 | 2024 | 3 | |
| 12 | 2024 | 1 | |
| 13 | 2024 | 1 | |
| 14 | 2025 | 0 | |
| 15 | 2022 | 0 |
About Danielle Rasooly
Danielle Rasooly is a scholar working on Genetics, Molecular Biology, Obstetrics and Gynecology, Electrical and Electronic Engineering and Statistics and Probability, having authored 15 papers that have together received 227 indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (7 papers), Advanced Causal Inference Techniques (2 papers), Uterine Myomas and Treatments (2 papers), Bioinformatics and Genomic Networks (2 papers), Pharmacogenetics and Drug Metabolism (1 paper), Advanced Optical Network Technologies (1 paper), Endometriosis Research and Treatment (1 paper) and Cloud Computing and Resource Management (1 paper). The work is most often cited by research in Genetics (61 citations), Periodontics (5 citations), Cancer Research (16 citations), Health, Toxicology and Mutagenesis (14 citations) and Gastroenterology (5 citations). Danielle Rasooly has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Chirag J. Patel, Gina M. Peloso, Arjun K. Manrai, Ioanna Tzoulaki, Yixuan He, Claudia Giambartolomei, Muin J. Khoury, John P. A. Ioannidis, Henggang Cui and Ramal Moonesinghe. Their work appears in journals such as Current Protocols, Arthritis Care & Research, Diabetes Care, American Journal of Obstetrics and Gynecology and CPT Pharmacometrics & Systems Pharmacology.
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.