Catherine M. Nolan
- Molecular Biology top 10%
- Genetics top 5%
- Endocrinology, Diabetes and Metabolism top 5%
- Pediatrics, Perinatology and Child Health top 5%
- Cancer Research top 10%
- Co-authors
- Eileen R. GibneyWilliam S. SlyJohn W. KyleRandy L. JirtleAkihiko OshimaJeffrey H. GrubbLucy ByrnesJ. Keith Killian
- Topics
- Genetic Syndromes and Imprinting (11 papers)Epigenetics and DNA Methylation (10 papers)Prenatal Screening and Diagnostics (7 papers)
- Partner nations
- IrelandUnited StatesAustralia
In The Last Decade
Catherine M. Nolan
38 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 112
- Molecular Biology 1.3k
- Genetics 551
- Endocrinology, Diabetes and Metabolism 320
- Pediatrics, Perinatology and Child Health 261
- Cancer Research 193
Countries citing papers authored by Catherine M. Nolan
This map shows the geographic impact of Catherine M. Nolan'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 Catherine M. Nolan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Catherine M. Nolan more than expected).
Fields of papers citing papers by Catherine M. Nolan
This network shows the impact of papers produced by Catherine M. Nolan. 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 Catherine M. Nolan. The network helps show where Catherine M. Nolan may publish in the future.
Co-authorship network of co-authors of Catherine M. Nolan
This figure shows the co-authorship network connecting the top 25 collaborators of Catherine M. Nolan. A scholar is included among the top collaborators of Catherine M. Nolan 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 Catherine M. Nolan. Catherine M. Nolan 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 | 3 | |
| 4 | Epigenetics and gene expressionbreakdown → | 725 |
| 5 | 3 | |
| 6 | 39 | |
| 7 | 37 | |
| 8 | 17 | |
| 9 | 19 | |
| 10 | 35 | |
| 11 | 32 | |
| 12 | 72 | |
| 13 | 50 | |
| 14 | 28 | |
| 15 | 52 | |
| 16 | 107 | |
| 17 | 1 | |
| 18 | 61 | |
| 19 | 23 | |
| 20 | 34 |
About Catherine M. Nolan
Catherine M. Nolan is a scholar working on Genetics, Endocrinology, Diabetes and Metabolism and Pediatrics, Perinatology and Child Health, having authored 39 papers that have together received 1.9k indexed citations. Recurring topics across this work include Genetic Syndromes and Imprinting (11 papers), Epigenetics and DNA Methylation (10 papers) and Prenatal Screening and Diagnostics (7 papers). The work is most often cited by research in Genetics (551 citations), Endocrinology, Diabetes and Metabolism (320 citations) and Molecular Biology (1.3k citations). Catherine M. Nolan has collaborated with scholars based in Ireland, United States and Australia. Frequent co-authors include Eileen R. Gibney, William S. Sly, John W. Kyle, Randy L. Jirtle, Akihiko Oshima, Jeffrey H. Grubb, Lucy Byrnes, J. Keith Killian, Curtis Chubb and Edward Eivers. Their work appears in journals such as Science, Journal of Biological Chemistry and Hepatology.
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.