Avital Eisenberg‐Lerner

8.2k citations
21 papers · 1.7k indexed · 1 hit paper · h-index 12
Topics
Autophagy in Disease and Therapy (7 papers)Ubiquitin and proteasome pathways (7 papers)Endoplasmic Reticulum Stress and Disease (4 papers)

In The Last Decade

Avital Eisenberg‐Lerner

21 papers receiving 1.7k citations

Hit Papers

Life and death partners: apoptosis, autophagy and the cro...200920262014202020092505007501000

Peers

Avital Eisenberg‐Lerner
Comparison fields: 5 of 98
  • Molecular Biology 985
  • Epidemiology 901
  • Cell Biology 268
  • Cancer Research 194
  • Oncology 148
Replace Tsuyoshi Kawabata with:
Tsuyoshi Kawabata Japan
Elsje G. Otten United Kingdom
Raquel García-Medina United States
Muriel Priault France
Tom G. Keulers Netherlands
Binyun Ma China
Damián Gatica United States
Shoshana Paglin United States
Daniel Meley France
Avital Eisenberg‐Lerner relative to Tsuyoshi Kawabata Japan Tsuyoshi Kawabata's profile →
Citations per field
00.5×4.2×
Tsuyoshi Kawabata · 1×
Citations per year

Countries citing papers authored by Avital Eisenberg‐Lerner

Since Specialization
Citations

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

Fields of papers citing papers by Avital Eisenberg‐Lerner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Avital Eisenberg‐Lerner. 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 Avital Eisenberg‐Lerner. The network helps show where Avital Eisenberg‐Lerner may publish in the future.

Co-authorship network of co-authors of Avital Eisenberg‐Lerner

This figure shows the co-authorship network connecting the top 25 collaborators of Avital Eisenberg‐Lerner. A scholar is included among the top collaborators of Avital Eisenberg‐Lerner 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 Avital Eisenberg‐Lerner. Avital Eisenberg‐Lerner 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 4
2 3
3 5
4 6
5 7
6 13
7 11
8 5
9 15
10 9
11 45
12 2
13 33
14 3
15 15
16 101
17 97
18 188
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Life and death partners: apoptosis, autophagy and the cross-talk between thembreakdown →
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About Avital Eisenberg‐Lerner

Avital Eisenberg‐Lerner is a scholar working on Bioengineering, Physiology and Cell Biology, having authored 21 papers that have together received 1.7k indexed citations. Recurring topics across this work include Autophagy in Disease and Therapy (7 papers), Ubiquitin and proteasome pathways (7 papers) and Endoplasmic Reticulum Stress and Disease (4 papers). The work is most often cited by research in Epidemiology (901 citations), Physiology (96 citations) and Geriatrics and Gerontology (78 citations). Avital Eisenberg‐Lerner has collaborated with scholars based in Israel, United States and Hong Kong. Frequent co-authors include Adi Kimchi, Hans‐Uwe Simon, Shani Bialik, Yifat Merbl, Michal Eisenberg‐Bord, Ronit Sagi‐Eisenberg, Aaron Ciechanover, Agnès Bernet, Catherine Guix and Céline Delloye‐Bourgeois. Their work appears in journals such as Nature Biotechnology, Molecular Cell and Journal of Molecular Biology.

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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