Igor B. Kuznetsov

994 total citations
24 papers, 643 citations indexed

About

Igor B. Kuznetsov is a scholar working on Molecular Biology, Materials Chemistry and Neurology. According to data from OpenAlex, Igor B. Kuznetsov has authored 24 papers receiving a total of 643 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 8 papers in Materials Chemistry and 2 papers in Neurology. Recurrent topics in Igor B. Kuznetsov's work include Protein Structure and Dynamics (11 papers), RNA and protein synthesis mechanisms (11 papers) and Enzyme Structure and Function (8 papers). Igor B. Kuznetsov is often cited by papers focused on Protein Structure and Dynamics (11 papers), RNA and protein synthesis mechanisms (11 papers) and Enzyme Structure and Function (8 papers). Igor B. Kuznetsov collaborates with scholars based in United States, Russia and Australia. Igor B. Kuznetsov's co-authors include Seungwoo Hwang, S. Rackovsky, Run Li, Roxana Moslehi, Sivasish Sindiri, Paul M. Sondel, Young Song, Jun S. Wei, Daniela S. Gerhard and Shile Zhang and has published in prestigious journals such as Bioinformatics, Cancer Research and Clinical Cancer Research.

In The Last Decade

Igor B. Kuznetsov

23 papers receiving 632 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Igor B. Kuznetsov United States 12 507 97 69 59 58 24 643
Michael F. Bailey Australia 16 534 1.1× 114 1.2× 83 1.2× 25 0.4× 19 0.3× 23 679
Gergő Gógl Hungary 17 663 1.3× 57 0.6× 61 0.9× 13 0.2× 90 1.6× 42 821
J.-P. Marquette France 9 358 0.7× 71 0.7× 47 0.7× 7 0.1× 49 0.8× 9 644
Lisandra M. Gava Brazil 13 430 0.8× 45 0.5× 126 1.8× 10 0.2× 35 0.6× 25 540
M. Blaesse Germany 9 443 0.9× 75 0.8× 74 1.1× 9 0.2× 38 0.7× 12 546
T. Shaw United Kingdom 6 458 0.9× 35 0.4× 27 0.4× 15 0.3× 66 1.1× 7 551
Yen-Wei Chu Taiwan 10 387 0.8× 31 0.3× 36 0.5× 16 0.3× 30 0.5× 41 525
Peter Vanhee Spain 8 616 1.2× 91 0.9× 57 0.8× 7 0.1× 104 1.8× 10 710
Fred Wittinghofer Germany 8 465 0.9× 82 0.8× 55 0.8× 11 0.2× 28 0.5× 8 533
T. Kotenyova Sweden 9 485 1.0× 49 0.5× 47 0.7× 6 0.1× 29 0.5× 9 616

Countries citing papers authored by Igor B. Kuznetsov

Since Specialization
Citations

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

Fields of papers citing papers by Igor B. Kuznetsov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Igor B. Kuznetsov. 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 Igor B. Kuznetsov. The network helps show where Igor B. Kuznetsov may publish in the future.

Co-authorship network of co-authors of Igor B. Kuznetsov

This figure shows the co-authorship network connecting the top 25 collaborators of Igor B. Kuznetsov. A scholar is included among the top collaborators of Igor B. Kuznetsov 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 Igor B. Kuznetsov. Igor B. Kuznetsov 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
1.
Yang, Richard K., Igor B. Kuznetsov, Erik A. Ranheim, et al.. (2020). Outcome-Related Signatures Identified by Whole Transcriptome Sequencing of Resectable Stage III/IV Melanoma Evaluated after Starting Hu14.18-IL2. Clinical Cancer Research. 26(13). 3296–3306. 17 indexed citations
2.
Wei, Jun S., Igor B. Kuznetsov, Shile Zhang, et al.. (2018). Clinically Relevant Cytotoxic Immune Cell Signatures and Clonal Expansion of T-Cell Receptors in High-Risk MYCN -Not-Amplified Human Neuroblastoma. Clinical Cancer Research. 24(22). 5673–5684. 76 indexed citations
3.
Wei, Jun S., Shile Zhang, Igor B. Kuznetsov, et al.. (2017). Abstract 1744: RNAseq identified immune signatures associated with adverse outcome in high-risk neuroblastoma. Cancer Research. 77(13_Supplement). 1744–1744. 1 indexed citations
4.
Kuznetsov, Igor B., et al.. (2015). PR2ALIGN: a stand-alone software program and a web-server for protein sequence alignment using weighted biochemical properties of amino acids. BMC Research Notes. 8(1). 187–187. 1 indexed citations
5.
Kuznetsov, Igor B.. (2011). Protein sequence alignment with family-specific amino acid similarity matrices. BMC Research Notes. 4(1). 296–296. 5 indexed citations
6.
Kuznetsov, Igor B.. (2009). Simplified Computational Methods for the Analysis of Protein Flexibility. Current Protein and Peptide Science. 10(6). 607–613. 8 indexed citations
7.
Kuznetsov, Igor B. & S. Rackovsky. (2009). CFP: a web-server for constructing sequence-based protein conformational flexibility profiles. Bioinformation. 4(5). 176–178. 1 indexed citations
8.
Kuznetsov, Igor B., et al.. (2008). On the Accuracy of Sequence-Based Computational Inference of Protein Residues Involved in Interactions with DNA. Trends in Applied Sciences Research. 3(4). 285–291. 1 indexed citations
9.
Kuznetsov, Igor B., et al.. (2008). FlexPred: a web-server for predicting residue positions involved in conformational switches in proteins. Bioinformation. 3(3). 134–136. 27 indexed citations
10.
Kuznetsov, Igor B.. (2008). Ordered conformational change in the protein backbone: Prediction of conformationally variable positions from sequence and low‐resolution structural data. Proteins Structure Function and Bioinformatics. 72(1). 74–87. 20 indexed citations
11.
Hwang, Seungwoo, et al.. (2007). DP-Bind: a web server for sequence-based prediction of DNA-binding residues in DNA-binding proteins. Bioinformatics. 23(5). 634–636. 188 indexed citations
12.
Kuznetsov, Igor B., et al.. (2006). Using evolutionary and structural information to predict DNA‐binding sites on DNA‐binding proteins. Proteins Structure Function and Bioinformatics. 64(1). 19–27. 126 indexed citations
14.
Kuznetsov, Igor B. & S. Rackovsky. (2004). Identification of nonrandom patterns in structural and mutational data: the case of prion protein. 3. 604–608. 2 indexed citations
15.
Kuznetsov, Igor B. & S. Rackovsky. (2003). Class‐specific correlations between protein folding rate, structure‐derived, and sequence‐derived descriptors. Proteins Structure Function and Bioinformatics. 54(2). 333–341. 32 indexed citations
16.
Kuznetsov, Igor B. & S. Rackovsky. (2003). On the properties and sequence context of structurally ambivalent fragments in proteins. Protein Science. 12(11). 2420–2433. 37 indexed citations
17.
Kuznetsov, Igor B. & S. Rackovsky. (2003). Similarity between the C-terminal domain of the prion protein and chimpanzee cytomegalovirus glycoprotein UL9. Protein Engineering Design and Selection. 16(12). 861–863. 2 indexed citations
18.
Kuznetsov, Igor B. & S. Rackovsky. (2002). Discriminative ability with respect to amino acid types: Assessing the performance of knowledge‐based potentials without threading. Proteins Structure Function and Bioinformatics. 49(2). 266–284. 12 indexed citations
19.
Kuznetsov, Igor B., et al.. (1997). Prion proteins: evolution and preservation of secondary structure. FEBS Letters. 412(3). 429–432. 6 indexed citations
20.
Kuznetsov, Igor B. & Pavel Morozov. (1996). GEOMETRY: a software package for nucleotide sequence analysis using statistical geometry in sequence space. Computer applications in the biosciences. 12(4). 297–301. 2 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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