Cagdas Tazearslan

987 citations
13 papers · 623 indexed · h-index 10
Topics
Genetics, Aging, and Longevity in Model Organisms (4 papers)Genomics and Chromatin Dynamics (3 papers)Epigenetics and DNA Methylation (2 papers)

In The Last Decade

Cagdas Tazearslan

12 papers receiving 615 citations

Peers

Cagdas Tazearslan
Comparison fields: 5 of 81
  • Molecular Biology 375
  • Aging 187
  • Physiology 168
  • Genetics 83
  • Endocrine and Autonomic Systems 57
Replace Evgeniy R. Galimov with:
Evgeniy R. Galimov United Kingdom
Lara S. Shamieh United States
Lei Hou China
Diána Papp Hungary
Monika Oláhová United Kingdom
Wilson C. Fok United States
Tobias Nespital Germany
Yayi Chang United States
Michele D. Allen United States
Johanna H.K. Kauppila Germany
Cagdas Tazearslan relative to Evgeniy R. Galimov United Kingdom Evgeniy R. Galimov's profile →
Citations per field
00.5×1.5×2.1×
Evgeniy R. Galimov · 1×
Citations per year

Countries citing papers authored by Cagdas Tazearslan

Since Specialization
Citations

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

Fields of papers citing papers by Cagdas Tazearslan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cagdas Tazearslan

This figure shows the co-authorship network connecting the top 25 collaborators of Cagdas Tazearslan. A scholar is included among the top collaborators of Cagdas Tazearslan 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 Cagdas Tazearslan. Cagdas Tazearslan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
#WorkIndexed citations
1 0
2 2
3 1
4 9
5 92
6 39
7 120
8 34
9 56
10 24
11 80
12 146
13 20

About Cagdas Tazearslan

Cagdas Tazearslan is a scholar working on Aging, Neuropsychology and Physiological Psychology and Physiology, having authored 13 papers that have together received 623 indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (4 papers), Genomics and Chromatin Dynamics (3 papers) and Epigenetics and DNA Methylation (2 papers). The work is most often cited by research in Aging (187 citations), Endocrine and Autonomic Systems (57 citations) and Physiology (168 citations). Cagdas Tazearslan has collaborated with scholars based in United States, China and Hungary. Frequent co-authors include Yousin Suh, Jing Huang, Nir Barzilai, Robert J. Shmookler Reis, Puneet Bharill, Srinivas Ayyadevara, Archana Tare, Adam D. Hudgins, Derek M. Huffman and Lulu Xu. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Neuroscience and PLoS ONE.

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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2026