Miklós Békés

4.8k citations
23 papers · 3.3k indexed · 2 hit papers · h-index 19
Topics
Ubiquitin and proteasome pathways (15 papers)Peptidase Inhibition and Analysis (10 papers)Protein Degradation and Inhibitors (6 papers)

In The Last Decade

Miklós Békés

22 papers receiving 3.2k citations

Hit Papers

PROTAC targeted protein degraders: the past is prologue20202026202220242022202050010001.5k

Peers

Miklós Békés
Comparison fields: 5 of 101
  • Molecular Biology 2.7k
  • Oncology 1.1k
  • Infectious Diseases 347
  • Hematology 302
  • Immunology 282
Replace Brian D. Marsden with:
Brian D. Marsden United Kingdom
Jolanta Grembecka United States
Sara J. Buhrlage United States
Radosław P. Nowak United States
David H. Drewry United States
Djordje Müsil Germany
Yves Collette France
Mary E. McGrath United States
Thilo Werner Germany
Jennifer L. Meagher United States
Miklós Békés relative to Brian D. Marsden United Kingdom Brian D. Marsden's profile →
Citations per field
00.5×9.3×
Brian D. Marsden · 1×
Citations per year

Countries citing papers authored by Miklós Békés

Since Specialization
Citations

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

Fields of papers citing papers by Miklós Békés

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Miklós Békés

This figure shows the co-authorship network connecting the top 25 collaborators of Miklós Békés. A scholar is included among the top collaborators of Miklós Békés 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 Miklós Békés. Miklós Békés 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 29
2 2
3
PROTAC targeted protein degraders: the past is prologuebreakdown →
1872
4 35
5
Activity profiling and crystal structures of inhibitor-bound SARS-CoV-2 papain-like protease: A framework for anti–COVID-19 drug designbreakdown →
353
6 4
7 33
8 103
9 52
10 38
11 59
12 10
13 133
14 60
15 40
16 47
17 62
18 129
19 30
20 110

About Miklós Békés

Miklós Békés is a scholar working on Oncology, Molecular Biology and Parasitology, having authored 23 papers that have together received 3.3k indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (15 papers), Peptidase Inhibition and Analysis (10 papers) and Protein Degradation and Inhibitors (6 papers). The work is most often cited by research in Oncology (1.1k citations), Molecular Biology (2.7k citations) and Hematology (302 citations). Miklós Békés has collaborated with scholars based in United States, Poland and Netherlands. Frequent co-authors include David R. Langley, Craig M. Crews, Tony T. Huang, Marcin Drąg, Guy S. Salvesen, Wioletta Rut, Shaun K. Olsen, Stephanie Patchett, Zongyang Lv and Scott J. Snipas. Their work appears in journals such as Journal of Biological Chemistry, 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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