Steven De Munck

894 total citations · 1 hit paper
7 papers, 274 citations indexed

About

Steven De Munck is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Steven De Munck has authored 7 papers receiving a total of 274 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 3 papers in Immunology and 2 papers in Oncology. Recurrent topics in Steven De Munck's work include Glycosylation and Glycoproteins Research (2 papers), Biochemical and Molecular Research (2 papers) and Immune Cell Function and Interaction (2 papers). Steven De Munck is often cited by papers focused on Glycosylation and Glycoproteins Research (2 papers), Biochemical and Molecular Research (2 papers) and Immune Cell Function and Interaction (2 papers). Steven De Munck collaborates with scholars based in Belgium, United States and France. Steven De Munck's co-authors include Savvas N. Savvides, Buwei Huang, Brian Coventry, Aza Allen, Frank DiMaio, Minkyung Baek, Justas Dauparas, Dionne Vafeados, Lance Stewart and Inna Goreshnik and has published in prestigious journals such as Nature, Nature Communications and Structure.

In The Last Decade

Steven De Munck

7 papers receiving 270 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Improving de novo protein binder design with deep learning

2023 158 citations Nathaniel R. Bennett, Brian Coventry et al. Nature Communications profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Steven De Munck Belgium	7	184	51	29	25	22	7	274
Tomer Tsaban Israel	6	278 1.5×	42 0.8×	32 1.1×	37 1.5×	61 2.8×	7	357
Anshul Sukhwal India	7	170 0.9×	33 0.6×	18 0.6×	38 1.5×	11 0.5×	7	214
Yashavantha L. Vishweshwaraiah United States	8	222 1.2×	86 1.7×	20 0.7×	9 0.4×	40 1.8×	14	281
Mileidy W. Gonzalez United States	6	324 1.8×	34 0.7×	13 0.4×	64 2.6×	35 1.6×	8	408
Sau-Mei Leung United States	6	324 1.8×	42 0.8×	21 0.7×	11 0.4×	13 0.6×	8	408
Tjaša Plaper Slovenia	7	244 1.3×	35 0.7×	24 0.8×	7 0.3×	21 1.0×	10	346
Ariel Erijman Israel	9	392 2.1×	20 0.4×	44 1.5×	19 0.8×	51 2.3×	11	465
Philip Matharu United Kingdom	7	204 1.1×	87 1.7×	37 1.3×	14 0.6×	34 1.5×	9	361
Alan J. Situ United States	14	405 2.2×	51 1.0×	11 0.4×	9 0.4×	24 1.1×	20	488

Countries citing papers authored by Steven De Munck

Since Specialization

Citations

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

Fields of papers citing papers by Steven De Munck

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Steven De Munck. 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 Steven De Munck. The network helps show where Steven De Munck may publish in the future.

Co-authorship network of co-authors of Steven De Munck

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

All Works

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7 of 7 papers shown

1.

Bennett, Nathaniel R., Brian Coventry, Inna Goreshnik, et al.. (2023). Improving de novo protein binder design with deep learning. Nature Communications. 14(1). 2625–2625. 158 indexed citations breakdown →

2.

Yperman, Klaas, Romain Merceron, Steven De Munck, et al.. (2021). Distinct EH domains of the endocytic TPLATE complex confer lipid and protein binding. Nature Communications. 12(1). 3050–3050. 26 indexed citations

3.

Munck, Steven De, Ikuko Omori, Jan Félix, et al.. (2021). Structural basis of cytokine-mediated activation of ALK family receptors. Nature. 600(7887). 143–147. 25 indexed citations

4.

Jian, Yanlin, Romain Merceron, Steven De Munck, et al.. (2020). Endeavors towards transformation of M. tuberculosis thymidylate kinase (MtbTMPK) inhibitors into potential antimycobacterial agents. European Journal of Medicinal Chemistry. 206. 112659–112659. 11 indexed citations

5.

Bloch, Yehudi, et al.. (2020). HomogeneouslyN-glycosylated proteins derived from the GlycoDelete HEK293 cell line enable diffraction-quality crystallogenesis. Acta Crystallographica Section D Structural Biology. 76(12). 1244–1255. 8 indexed citations

6.

Félix, Jan, Eaazhisai Kandiah, Steven De Munck, et al.. (2016). Structural basis of GM-CSF and IL-2 sequestration by the viral decoy receptor GIF. Nature Communications. 7(1). 13228–13228. 14 indexed citations

7.

Félix, Jan, Steven De Munck, Kenneth Verstraete, et al.. (2015). Structure and Assembly Mechanism of the Signaling Complex Mediated by Human CSF-1. Structure. 23(9). 1621–1631. 32 indexed citations

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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