Michael Grow
- Hematology top 10%
- Iron Metabolism and Disorders 2
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- Genetic Associations and Epidemiology 5
- Clinical Biochemistry top 10%
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- Lipoproteins and Cardiovascular Health 4
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- Apelin-related biomedical research 3
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- Bioinformatics and Genomic Networks 2
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- Brazilian History and Foreign Policy 2
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- Brazilian cultural history and politics 2
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- Nuclear Receptors and Signaling 2
- Co-authors
- Suzanne ChengWilliam KlitzGérard SiestCéline PallaudClive R. PullingerMary J. MalloyJohn P. KaneLori Steiner
- Journals
- The American Historical Review (5 papers)Clinical Chemistry and Laboratory Medicine (CCLM) (2 papers)European Journal of Human Genetics (2 papers)
- Partner nations
- United StatesFranceSwitzerland
In The Last Decade
Michael Grow
22 papers receiving 699 citations
Peers
Comparison fields: 5 of 95
- Endocrinology, Diabetes and Metabolism 174
- Hematology 104
- Cardiology and Cardiovascular Medicine 158
- Genetics 68
- Clinical Biochemistry 43
Countries citing papers authored by Michael Grow
This map shows the geographic impact of Michael Grow'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 Michael Grow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Grow more than expected).
Fields of papers citing papers by Michael Grow
This network shows the impact of papers produced by Michael Grow. 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 Michael Grow. The network helps show where Michael Grow may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Michael Grow, 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 | 2010 | 20 | |
| 2 | Candidate gene polymorphism in cardiovascular disease: the BIP cohort. | 2006 | 3 |
| 3 | 2005 | 62 | |
| 4 | 2005 | 20 | |
| 5 | 2004 | 21 | |
| 6 | 2002 | 58 | |
| 7 | 2002 | 53 | |
| 8 | 2002 | 47 | |
| 9 | 2001 | 24 | |
| 10 | 2000 | 16 | |
| 11 | 1999 | 189 | |
| 12 | 1999 | 7 | |
| 13 | 1998 | 43 | |
| 14 | 1996 | 2 | |
| 15 | 1994 | 0 | |
| 16 | 1991 | 3 | |
| 17 | 1989 | 21 | |
| 18 | 1986 | 3 | |
| 19 | 1982 | 5 | |
| 20 | 1982 | 4 |
About Michael Grow
Michael Grow is a scholar working on Clinical Biochemistry, Development, Biochemistry, Pharmacology and Genetics, having authored 23 papers that have together received 726 indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (5 papers), Lipoproteins and Cardiovascular Health (4 papers), Apelin-related biomedical research (3 papers), Bioinformatics and Genomic Networks (2 papers), Iron Metabolism and Disorders (2 papers), Brazilian History and Foreign Policy (2 papers), Brazilian cultural history and politics (2 papers) and Nuclear Receptors and Signaling (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (174 citations), Hematology (104 citations), Cardiology and Cardiovascular Medicine (158 citations), Genetics (68 citations) and Clinical Biochemistry (43 citations). Michael Grow has collaborated with scholars based in United States, France and Switzerland. Frequent co-authors include Suzanne Cheng, William Klitz, Gérard Siest, Céline Pallaud, Clive R. Pullinger, Mary J. Malloy, John P. Kane, Lori Steiner, John J. Chen and Sophia Visvikis. Their work appears in journals such as The American Historical Review, Clinical Chemistry and Laboratory Medicine (CCLM), European Journal of Human Genetics, Journal of Lipid Research and British Journal of Haematology.
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.