E. Jane Albert Hubbard
- Molecular Biology top 5%
- Aging top 0.05%
- Public Health, Environmental and Occupational Health top 2%
- Endocrine and Autonomic Systems top 1%
- Cell Biology top 5%
- Co-authors
- Darrell J. KillianDavid GreensteinMarian CarlsonDorota Z. KortaTim SchedlIva GreenwaldDavid MichaelsonXiaolu Yang
- Topics
- Genetics, Aging, and Longevity in Model Organisms (52 papers)Circadian rhythm and melatonin (22 papers)Reproductive Biology and Fertility (15 papers)
- Partner nations
- United StatesIsraelUnited Kingdom
In The Last Decade
E. Jane Albert Hubbard
62 papers receiving 3.0k citations
Peers
Comparison fields: 5 of 110
- Molecular Biology 1.9k
- Aging 1.9k
- Public Health, Environmental and Occupational Health 587
- Endocrine and Autonomic Systems 582
- Cell Biology 257
Countries citing papers authored by E. Jane Albert Hubbard
This map shows the geographic impact of E. Jane Albert Hubbard'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 E. Jane Albert Hubbard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites E. Jane Albert Hubbard more than expected).
Fields of papers citing papers by E. Jane Albert Hubbard
This network shows the impact of papers produced by E. Jane Albert Hubbard. 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 E. Jane Albert Hubbard. The network helps show where E. Jane Albert Hubbard may publish in the future.
Co-authorship network of co-authors of E. Jane Albert Hubbard
This figure shows the co-authorship network connecting the top 25 collaborators of E. Jane Albert Hubbard. A scholar is included among the top collaborators of E. Jane Albert Hubbard 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 E. Jane Albert Hubbard. E. Jane Albert Hubbard 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 | 0 | |
| 3 | 4 | |
| 4 | 41 | |
| 5 | 17 | |
| 6 | 6 | |
| 7 | 31 | |
| 8 | 9 | |
| 9 | 4 | |
| 10 | 71 | |
| 11 | 110 | |
| 12 | 22 | |
| 13 | 78 | |
| 14 | 94 | |
| 15 | 46 | |
| 16 | 132 | |
| 17 | 193 | |
| 18 | 199 | |
| 19 | 16 | |
| 20 | Interactive protein modelling | 1 |
About E. Jane Albert Hubbard
E. Jane Albert Hubbard is a scholar working on Aging, Endocrine and Autonomic Systems and Neuropsychology and Physiological Psychology, having authored 65 papers that have together received 3.0k indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (52 papers), Circadian rhythm and melatonin (22 papers) and Reproductive Biology and Fertility (15 papers). The work is most often cited by research in Aging (1.9k citations), Endocrine and Autonomic Systems (582 citations) and Molecular Biology (1.9k citations). E. Jane Albert Hubbard has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Darrell J. Killian, David Greenstein, Marian Carlson, Dorota Z. Korta, Tim Schedl, Iva Greenwald, David Michaelson, Xiaolu Yang, Roumen Voutev and Guangyu Wu. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.
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.