Nathan Basisty

5.8k citations
55 papers · 3.3k · 1 hit paper · h-index 28

Impact in

Papers in

    • Mitochondrial Function and Pathology 12
    • Telomeres, Telomerase, and Senescence 16
    • Adipose Tissue and Metabolism 5

Nathan Basisty

53 papers receiving 3.2k citations

Nathan Basisty's Hit Papers

A proteomic atlas of senescence-associated secretomes for aging biomarker development 2020 · 862 citations
8620+2+4Years since publication250500750

Peers

Nathan Basisty
Comparison fields: 5 of 122
  • Aging 439
  • Geriatrics and Gerontology 191
  • Physiology 1.1k
  • Molecular Biology 1.6k
  • Biological Psychiatry 50
Replace Eun Seong Hwang with:
Eun Seong Hwang South Korea
Kotaro Shirakawa Japan
Kit‐Yi Leung United Kingdom
Graeme Hewitt United Kingdom
Francesco Vetrini United States
Chiara Di Malta Italy
Esther Wong Singapore
Maria Rita Rippo Italy
Anthony J. Covarrubias United States
Grażyna Mosieniak Poland
Nathan Basisty relative to Eun Seong Hwang South Korea Eun Seong Hwang's profile →
Citations per field
00.5×1.5×2.1×
Eun Seong Hwang · 1×
Citations per year

Countries citing papers authored by Nathan Basisty

Since Specialization
Citations

This map shows the geographic impact of Nathan Basisty'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 Nathan Basisty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nathan Basisty more than expected).

Fields of papers citing papers by Nathan Basisty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nathan Basisty. 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 Nathan Basisty. The network helps show where Nathan Basisty may publish in the future.

Co-authors

The 25 scholars most cited alongside Nathan Basisty, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nathan Basisty Line = papers co-authored together Nathan Basisty links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A proteomic atlas of senescence-associated secretomes for aging biomarker development
Hit paper breakdown →
2020862
2 2014260
3 2019137
4 2021132
5 2013122
6 2022120
7 2019119
8 2020115
9 2015112
10 2016112
11 2019104
12 202193
13 201982
14 201877
15 201562
16 201560
17 201557
18 201154
19 202053
20 202047

About Nathan Basisty

Nathan Basisty is a scholar working on Molecular Biology, Physiology, Aging, Spectroscopy and Cell Biology, having authored 55 papers that have together received 3.3k indexed citations. Recurring topics across this work include Telomeres, Telomerase, and Senescence (16 papers), Genetics, Aging, and Longevity in Model Organisms (16 papers), Mitochondrial Function and Pathology (12 papers), Advanced Proteomics Techniques and Applications (11 papers), GDF15 and Related Biomarkers (7 papers), Adipose Tissue and Metabolism (5 papers), Peptidase Inhibition and Analysis (5 papers) and Muscle metabolism and nutrition (4 papers). The work is most often cited by research in Aging (439 citations), Geriatrics and Gerontology (191 citations), Physiology (1.1k citations), Molecular Biology (1.6k citations) and Biological Psychiatry (50 citations). Nathan Basisty has collaborated with scholars based in United States, Canada and Italy. Frequent co-authors include Birgit Schilling, Luigi Ferrucci, Judith Campisi, Anja Holtz, Peter S. Rabinovitch, Abhijit Kale, Samah Shah, Chirag Rao, Chisaka Kuehnemann and Ok Hee Jeon. Their work appears in journals such as Aging Cell, Journal of Visualized Experiments, PROTEOMICS, PLoS ONE and GeroScience.

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.

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