R. A. Good
- Immunology top 1%
- Molecular Biology
- Hematology top 2%
- Genetics top 5%
- Epidemiology top 10%
- Co-authors
- Osias StutmanW.A. CainK. OGASAWARAHisashi AraseMax D. CooperR. J. PickeringKazunori OnoéNoriko Arase
- Topics
- Monoclonal and Polyclonal Antibodies Research (15 papers)Complement system in diseases (13 papers)T-cell and B-cell Immunology (13 papers)
- Cited by
- ImmunologyHematologyGenetics
- Partner nations
- United StatesJapanFrance
In The Last Decade
R. A. Good
113 papers receiving 2.8k citations
Peers
Comparison fields: 5 of 130
- Immunology 1.8k
- Molecular Biology 560
- Hematology 461
- Genetics 420
- Epidemiology 353
Countries citing papers authored by R. A. Good
This map shows the geographic impact of R. A. 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 R. A. Good with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites R. A. Good more than expected).
Fields of papers citing papers by R. A. Good
This network shows the impact of papers produced by R. A. 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 R. A. Good. The network helps show where R. A. Good may publish in the future.
Co-authorship network of co-authors of R. A. Good
This figure shows the co-authorship network connecting the top 25 collaborators of R. A. Good. A scholar is included among the top collaborators of R. A. 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 R. A. Good. R. A. Good is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 14 | |
| 3 | Circadian dependent chronoimmunological responses of T, B and natural killer cells | 2 |
| 4 | 2 | |
| 5 | Nutritional deficiency, immunologic function, and disease. | 85 |
| 6 | The five classes of immunoglobulins in normal C3H and BALB/c mice. | 20 |
| 7 | Haemolysis in chicken serum. II. Ontogenetic development. | 19 |
| 8 | 14 | |
| 9 | 99 | |
| 10 | 8 | |
| 11 | 121 | |
| 12 | 5 | |
| 13 | 24 | |
| 14 | 101 | |
| 15 | Studies of the relation of thymus-dependent lymphoid system and pituitary gland. Abstr. | 1 |
| 16 | 161 | |
| 17 | Ontogeny of circulating immunoglobulin in normal, bursectomized and irradiated chickens. | 35 |
| 18 | Decreased C'-1q protein concentration and agglutinating activity in agammaglobulinaemia syndromes: an inborn error reflected in the complement system. | 34 |
| 19 | 53 | |
| 20 | 6 |
About R. A. Good
R. A. Good is a scholar working on Immunology, Hematology and Genetics, having authored 123 papers that have together received 3.4k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (15 papers), Complement system in diseases (13 papers) and T-cell and B-cell Immunology (13 papers). The work is most often cited by research in Immunology (1.8k citations), Hematology (461 citations) and Genetics (280 citations). R. A. Good has collaborated with scholars based in United States, Japan and France. Frequent co-authors include Osias Stutman, W.A. Cain, K. OGASAWARA, Hisashi Arase, Max D. Cooper, R. J. Pickering, Kazunori Onoé, Noriko Arase, H Gewurz and N K Day. Their work appears in journals such as Nature, Science and New England Journal of Medicine.
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.