Maya Gershkovitz

521 citations
7 papers · 387 · h-index 7

Impact in

  • Immunology top 10%
    • Immune cells in cancer
    • Neutrophil, Myeloperoxidase and Oxidative Mechanisms
    • Immune Response and Inflammation
    • Ion Channels and Receptors

Papers in

    • S100 Proteins and Annexins 2
    • Metabolism, Diabetes, and Cancer 1
    • Cancer Cells and Metastasis 2
    • Lung Cancer Research Studies 1

Maya Gershkovitz

7 papers receiving 383 citations

Peers

Maya Gershkovitz
Comparison fields: 5 of 59
  • Immunology 221
  • Sensory Systems 31
  • Oncology 124
  • Cancer Research 48
  • Toxicology 6
Replace Quanning Chen with:
Quanning Chen China
Xiaowei Qi China
Denis I. Trufa Germany
Jidong Shan United States
Hanqing Lin China
Corinne E. Decker United States
Jiaxiang Ye China
Pierre‐Emmanuel Stoebner France
Jason C. Hall United States
Shengcai Hou China
Maya Gershkovitz relative to Quanning Chen China Quanning Chen's profile →
Citations per field
00.5×4.5×
Quanning Chen · 1×
Citations per year

Countries citing papers authored by Maya Gershkovitz

Since Specialization
Citations

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

Fields of papers citing papers by Maya Gershkovitz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Maya Gershkovitz, 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 Maya Gershkovitz Line = papers co-authored together Maya Gershkovitz links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown
#Work
1 2018169
2 202054
3 201843
4 201742
5 201538
6 201830
7 201511

About Maya Gershkovitz

Maya Gershkovitz is a scholar working on Molecular Biology, Oncology, Sensory Systems, Immunology and Cancer Research, having authored 7 papers that have together received 387 indexed citations. Recurring topics across this work include Ion Channels and Receptors (3 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (3 papers), Cancer Cells and Metastasis (2 papers), S100 Proteins and Annexins (2 papers), Immune cells in cancer (2 papers), Cancer, Hypoxia, and Metabolism (1 paper), Metabolism, Diabetes, and Cancer (1 paper) and Lung Cancer Research Studies (1 paper). The work is most often cited by research in Immunology (221 citations), Sensory Systems (31 citations), Oncology (124 citations), Cancer Research (48 citations) and Toxicology (6 citations). Maya Gershkovitz has collaborated with scholars based in Israel, United States and Malaysia. Frequent co-authors include Ronit Vogt Sionov, Zvi Granot, Tanya Fainsod-Levi, Saleh Khawaled, Zvi G. Fridlender, Lola Polyansky, Rami I. Aqeilan, Yoav D. Shaul, Merav E. Shaul and Leonor Cohen‐Daniel. Their work appears in journals such as Cancer Research, Journal of Visualized Experiments, Cancer Immunology Immunotherapy 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.

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