Victor Neduva

4.8k total citations · 1 hit paper
9 papers, 1.6k citations indexed

About

Victor Neduva is a scholar working on Molecular Biology, Computational Theory and Mathematics and Pharmacology. According to data from OpenAlex, Victor Neduva has authored 9 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 2 papers in Computational Theory and Mathematics and 1 paper in Pharmacology. Recurrent topics in Victor Neduva's work include Protein Structure and Dynamics (4 papers), Machine Learning in Bioinformatics (2 papers) and Ubiquitin and proteasome pathways (2 papers). Victor Neduva is often cited by papers focused on Protein Structure and Dynamics (4 papers), Machine Learning in Bioinformatics (2 papers) and Ubiquitin and proteasome pathways (2 papers). Victor Neduva collaborates with scholars based in Germany, United Kingdom and Canada. Victor Neduva's co-authors include Robert B. Russell, Xiaojing Tang, Mike Tyers, Shoshi Hazvi, Yadin Dudai, Diego E. Berman, Luís Serrano, Joe Lewis, Federico De Masi and Alexander Stark and has published in prestigious journals such as Science, Nucleic Acids Research and Journal of Neuroscience.

In The Last Decade

Victor Neduva

9 papers receiving 1.5k citations

Hit Papers

A Global Protein Kinase and Phosphatase Interaction Netwo... 2010 2026 2015 2020 2010 100 200 300 400 500
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.

  1. A Global Protein Kinase and Phosphatase Interaction Network in Yeast
    2010 512 citations Ashton Breitkreutz, Hyungwon Choi et al. Science profile →

Peers

Victor Neduva
Onur Dağliyan United States
Jing‐Song Fan Singapore
Emmanuel Lacroix Germany
Véronique Albanèse United States
Javier García‐Nafría United Kingdom
Yuichi Morohashi Japan
Orna Man Israel
Bryce T. Bajar United States
Changwook Lee South Korea
Takashi Shinkawa Japan
Onur Dağliyan United States
Victor Neduva
Citations per year, relative to Victor Neduva Victor Neduva (= 1×) peers Onur Dağliyan

Countries citing papers authored by Victor Neduva

Since Specialization
Citations

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

Fields of papers citing papers by Victor Neduva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Victor Neduva

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

All Works

9 of 9 papers shown
1.
Cabrera, Claudia, et al.. (2024). AI approaches for the discovery and validation of drug targets. SHILAP Revista de lepidopterología. 2. e7–e7. 8 indexed citations
2.
Breitkreutz, Ashton, Hyungwon Choi, Jeffrey R. Sharom, et al.. (2010). A Global Protein Kinase and Phosphatase Interaction Network in Yeast. Science. 328(5981). 1043–1046. 512 indexed citations breakdown →
3.
Orlicky, Stephen, Xiaojing Tang, Victor Neduva, et al.. (2010). An allosteric inhibitor of substrate recognition by the SCFCdc4 ubiquitin ligase. Nature Biotechnology. 28(7). 733–737. 124 indexed citations
4.
Neduva, Victor & Robert B. Russell. (2007). Proline-Rich Regions in Transcriptional Complexes: Heading in Many Directions. Science s STKE. 2007(369). pe1–pe1. 8 indexed citations
5.
Neduva, Victor & Robert B. Russell. (2006). DILIMOT: discovery of linear motifs in proteins. Nucleic Acids Research. 34(Web Server). W350–W355. 90 indexed citations
6.
Neduva, Victor & Robert B. Russell. (2006). Peptides mediating interaction networks: new leads at last. Current Opinion in Biotechnology. 17(5). 465–471. 157 indexed citations
7.
Neduva, Victor, Rune Linding, Alexander Stark, et al.. (2005). Systematic Discovery of New Recognition Peptides Mediating Protein Interaction Networks. PLoS Biology. 3(12). e405–e405. 254 indexed citations
8.
Neduva, Victor & Robert B. Russell. (2005). Linear motifs: Evolutionary interaction switches. FEBS Letters. 579(15). 3342–3345. 258 indexed citations
9.
Berman, Diego E., Shoshi Hazvi, Victor Neduva, & Yadin Dudai. (2000). The Role of Identified Neurotransmitter Systems in the Response of Insular Cortex to Unfamiliar Taste: Activation of ERK1–2 and Formation of a Memory Trace. Journal of Neuroscience. 20(18). 7017–7023. 143 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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