Daniel J. Klionsky

129.3k citations
519 papers · 81.9k indexed · 53 hit papers · h-index 133
Topics
Autophagy in Disease and Therapy (381 papers)Endoplasmic Reticulum Stress and Disease (155 papers)Cellular transport and secretion (111 papers)
Partner nations
United StatesChinaFrance

In The Last Decade

Daniel J. Klionsky

507 papers receiving 81.2k citations

Hit Papers

Autophagy fights disease through cellula...19882026200020132008200420002009200410002.0k3.0k4.0k5.0k

Peers

Daniel J. Klionsky
Comparison fields: 5 of 191
  • Epidemiology 51.1k
  • Molecular Biology 42.5k
  • Cell Biology 21.3k
  • Cancer Research 7.7k
  • Physiology 6.5k
Replace Beth Levine with:
Beth Levine United States
Noboru Mizushima Japan
Yoshinori Ohsumi Japan
Tamotsu Yoshimori Japan
Ana María Cuervo United States
Masaaki Komatsu Japan
Keiji Tanaka Japan
Douglas R. Green United States
Kun‐Liang Guan United States
Steven P. Gygi United States
Daniel J. Klionsky relative to Beth Levine United States Beth Levine's profile →
Citations per field
00.5×1.5×2.2×
Beth Levine · 1×
Citations per year

Countries citing papers authored by Daniel J. Klionsky

Since Specialization
Citations

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

Fields of papers citing papers by Daniel J. Klionsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel J. Klionsky. 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 Daniel J. Klionsky. The network helps show where Daniel J. Klionsky may publish in the future.

Co-authorship network of co-authors of Daniel J. Klionsky

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 3
3 9
4 5
5 22
6 1
7 25
8 20
9 18
10 80
11 58
12 35
13 78
14 88
15 211
16 147
17 52
18 151
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Guidelines for the use and interpretation of assays for monitoring autophagy in higher eukaryotesbreakdown →
1846
20 117

About Daniel J. Klionsky

Daniel J. Klionsky is a scholar working on Cell Biology, Epidemiology and Physiology, having authored 519 papers that have together received 81.9k indexed citations. Recurring topics across this work include Autophagy in Disease and Therapy (381 papers), Endoplasmic Reticulum Stress and Disease (155 papers) and Cellular transport and secretion (111 papers). The work is most often cited by research in Epidemiology (51.1k citations), Physiology (6.5k citations) and Cell Biology (21.3k citations). Daniel J. Klionsky has collaborated with scholars based in United States, China and France. Frequent co-authors include Beth Levine, Scott D. Emr, Zhifen Yang, Noboru Mizushima, Congcong He, Ana María Cuervo, Takahiro Shintani, Tomohiro Yorimitsu, Zhiping Xie and Daolin Tang. 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.

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