Julia Ablaeva
Impact in
- Aging top 1%
- Genetics, Aging, and Longevity in Model Organisms
- Cell Biology top 5%
- Proteoglycans and glycosaminoglycans research
Papers in
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- Epigenetics and DNA Methylation 4
- Glycosylation and Glycoproteins Research 3
- Genomics and Phylogenetic Studies 2
- Mitochondrial Function and Pathology 2
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- Proteoglycans and glycosaminoglycans research 4
- Co-authors
- Vera Gorbunova (14 shared papers)Andrei Seluanov (14 shared papers)Xiao Tian (6 shared papers)Eviatar Nevo (2 shared papers)Christopher Hine (2 shared papers)Amita Vaidya (1 shared paper)Max Myakishev-Rempel (1 shared paper)Zhiyong Mao (1 shared paper)
- Journals
- Nature Communications (3 papers)Cell Metabolism (2 papers)Nature (2 papers)Nature Aging (1 paper)Cell Reports (1 paper)
- Partner nations
- United StatesIsraelChina
In The Last Decade
Julia Ablaeva
14 papers receiving 1.4k citations
Julia Ablaeva's Hit Papers
Peers
Comparison fields: 5 of 116
- Aging 253
- Cell Biology 295
- Molecular Biology 859
- Cancer Research 159
- Geriatrics and Gerontology 39
Countries citing papers authored by Julia Ablaeva
This map shows the geographic impact of Julia Ablaeva'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 Julia Ablaeva with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julia Ablaeva more than expected).
Fields of papers citing papers by Julia Ablaeva
This network shows the impact of papers produced by Julia Ablaeva. 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 Julia Ablaeva. The network helps show where Julia Ablaeva may publish in the future.
Co-authors
The 25 scholars most cited alongside Julia Ablaeva, 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 | High-molecular-mass hyaluronan mediates the cancer resistance of the naked mole rat Hit paper breakdown → | 2013 | 558 |
| 2 | LINE1 Derepression in Aged Wild-Type and SIRT6-Deficient Mice Drives Inflammation Hit paper breakdown → | 2019 | 305 |
| 3 | 2012 | 116 | |
| 4 | 2020 | 79 | |
| 5 | 2023 | 76 | |
| 6 | 2017 | 57 | |
| 7 | 2021 | 54 | |
| 8 | 2022 | 50 | |
| 9 | 2021 | 47 | |
| 10 | 2021 | 31 | |
| 11 | 2022 | 28 | |
| 12 | 2023 | 16 | |
| 13 | 2021 | 14 | |
| 14 | 2022 | 1 |
About Julia Ablaeva
Julia Ablaeva is a scholar working on Molecular Biology, Cell Biology, Rheumatology, Aging and Physiology, having authored 14 papers that have together received 1.4k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (4 papers), Proteoglycans and glycosaminoglycans research (4 papers), Bone and Dental Protein Studies (3 papers), Glycosylation and Glycoproteins Research (3 papers), Genetics, Aging, and Longevity in Model Organisms (3 papers), interferon and immune responses (2 papers), Genomics and Phylogenetic Studies (2 papers) and Mitochondrial Function and Pathology (2 papers). The work is most often cited by research in Aging (253 citations), Cell Biology (295 citations), Molecular Biology (859 citations), Cancer Research (159 citations) and Geriatrics and Gerontology (39 citations). Julia Ablaeva has collaborated with scholars based in United States, Israel and China. Frequent co-authors include Vera Gorbunova, Andrei Seluanov, Xiao Tian, Eviatar Nevo, Christopher Hine, Amita Vaidya, Max Myakishev-Rempel, Zhiyong Mao, Jorge Azpurua and Andrei V. Gudkov. Their work appears in journals such as Nature Communications, Cell Metabolism, Nature, Nature Aging and Cell Reports.
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.