Lukáš Tenora

1.2k citations
32 papers · 909 · 1 hit paper · h-index 13

Impact in

    • Cancer, Hypoxia, and Metabolism
  • Immunology top 10%
    • Immune cells in cancer
    • Immune Cell Function and Interaction

Papers in

Lukáš Tenora

31 papers receiving 899 citations

Lukáš Tenora's Hit Papers

Targeting glutamine metabolism enhances tumor-specific immunity by modulating suppressive myeloid cells 2020 · 335 citations
3350+2+4Years since publication100200300

Peers

Lukáš Tenora
Comparison fields: 5 of 78
  • Cancer Research 351
  • Immunology 259
  • Biological Psychiatry 28
  • Biotechnology 79
  • Biochemistry 62
Replace Eva Prchalová with:
Eva Prchalová United States
Steve K. Cho United States
Teresa L. Tinder United States
Emiliano Dalla Italy
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Shashank J. Patel United States
Emily N. Chin United States
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Citations per field
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Citations per year

Countries citing papers authored by Lukáš Tenora

Since Specialization
Citations

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

Fields of papers citing papers by Lukáš Tenora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Targeting glutamine metabolism enhances tumor-specific immunity by modulating suppressive myeloid cells
Hit paper breakdown →
2020335
2 2016111
3 202281
4 201756
5 201950
6 201845
7 201836
8 201627
9 201726
10 201916
11 201916
12 201612
13 202212
14 201312
15 201710
16 20239
17 20208
18 20178
19 20236
20 20235

About Lukáš Tenora

Lukáš Tenora is a scholar working on Molecular Biology, Organic Chemistry, Cancer Research, Neurology and Oncology, having authored 32 papers that have together received 909 indexed citations. Recurring topics across this work include Cancer, Hypoxia, and Metabolism (6 papers), Neuroinflammation and Neurodegeneration Mechanisms (4 papers), Sphingolipid Metabolism and Signaling (3 papers), Epigenetics and DNA Methylation (3 papers), Neuroblastoma Research and Treatments (2 papers), Immune cells in cancer (2 papers), Biochemical and Molecular Research (2 papers) and Stress Responses and Cortisol (2 papers). The work is most often cited by research in Cancer Research (351 citations), Immunology (259 citations), Biological Psychiatry (28 citations), Biotechnology (79 citations) and Biochemistry (62 citations). Lukáš Tenora has collaborated with scholars based in Czechia, United States and Poland. Frequent co-authors include Barbara S. Slusher, Rana Rais, Pavel Majer, Jesse Alt, Jonathan D. Powell, Judson M. Englert, Liang Zhao, Matthew L. Arwood, Ranjeet Prasad Dash and Ying Wu. Their work appears in journals such as Journal of Medicinal Chemistry, Molecular Pharmaceutics, European Journal of Medicinal Chemistry, Tetrahedron and Neurotherapeutics.

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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