Mark Berjanskii

8.3k total citations
39 papers, 1.8k citations indexed

About

Mark Berjanskii is a scholar working on Molecular Biology, Materials Chemistry and Spectroscopy. According to data from OpenAlex, Mark Berjanskii has authored 39 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Molecular Biology, 16 papers in Materials Chemistry and 6 papers in Spectroscopy. Recurrent topics in Mark Berjanskii's work include Protein Structure and Dynamics (18 papers), Enzyme Structure and Function (16 papers) and Metabolomics and Mass Spectrometry Studies (11 papers). Mark Berjanskii is often cited by papers focused on Protein Structure and Dynamics (18 papers), Enzyme Structure and Function (16 papers) and Metabolomics and Mass Spectrometry Studies (11 papers). Mark Berjanskii collaborates with scholars based in Canada, United States and Mexico. Mark Berjanskii's co-authors include David S. Wishart, D. Arndt, Patrick Tang, Jianmin Zhou, Guo Lin, Maria Stepanova, Guohui Lin, J. A. Cruz, Steven R. Van Doren and Jianjun Zhou and has published in prestigious journals such as Journal of the American Chemical Society, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Mark Berjanskii

38 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark Berjanskii Canada 22 1.4k 458 344 138 120 39 1.8k
Ian Walsh Singapore 25 2.2k 1.6× 510 1.1× 211 0.6× 166 1.2× 144 1.2× 57 2.5k
Philipp Neudecker Germany 26 1.6k 1.2× 555 1.2× 459 1.3× 94 0.7× 68 0.6× 48 2.3k
Woonghee Lee United States 18 1.9k 1.4× 370 0.8× 320 0.9× 136 1.0× 56 0.5× 62 2.4k
Dmitrij Frishman Germany 11 2.5k 1.8× 764 1.7× 237 0.7× 161 1.2× 202 1.7× 17 2.9k
Michał J. Gajda Germany 12 2.0k 1.5× 732 1.6× 191 0.6× 223 1.6× 116 1.0× 21 2.7k
Andrew Campen United States 5 2.1k 1.5× 651 1.4× 230 0.7× 207 1.5× 67 0.6× 6 2.5k
Riccardo Pellarin France 32 2.4k 1.8× 584 1.3× 407 1.2× 181 1.3× 225 1.9× 57 3.2k
Ulrich Weininger Germany 25 1.2k 0.9× 377 0.8× 270 0.8× 104 0.8× 71 0.6× 74 1.6k
Robert Grothe United States 10 2.4k 1.7× 457 1.0× 459 1.3× 94 0.7× 105 0.9× 13 3.1k
Evgeniy V. Petrotchenko Canada 30 1.7k 1.2× 290 0.6× 818 2.4× 183 1.3× 54 0.5× 60 2.5k

Countries citing papers authored by Mark Berjanskii

Since Specialization
Citations

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

Fields of papers citing papers by Mark Berjanskii

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Berjanskii

This figure shows the co-authorship network connecting the top 25 collaborators of Mark Berjanskii. A scholar is included among the top collaborators of Mark Berjanskii 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 Mark Berjanskii. Mark Berjanskii 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.
López‐Hernández, Yamilé, Joel Monárrez‐Espino, Jiamin Zheng, et al.. (2023). The plasma metabolome of long COVID patients two years after infection. Scientific Reports. 13(1). 12420–12420. 54 indexed citations
2.
Rout, Manoj Kumar, Matthias Lipfert, Brian L. Lee, et al.. (2023). MagMet: A fully automated web server for targeted nuclear magnetic resonance metabolomics of plasma and serum. Magnetic Resonance in Chemistry. 61(12). 681–704. 15 indexed citations
3.
Wishart, David S., et al.. (2022). Practical Aspects of NMR-Based Metabolomics. Handbook of experimental pharmacology. 277. 1–41. 5 indexed citations
4.
Lipfert, Matthias, Manoj Kumar Rout, Mark Berjanskii, & David S. Wishart. (2019). Automated Tools for the Analysis of 1D-NMR and 2D-NMR Spectra. Methods in molecular biology. 2037. 429–449. 14 indexed citations
5.
Hafsa, Noor E., Mark Berjanskii, David Arndt, & David S. Wishart. (2017). Rapid and reliable protein structure determination via chemical shift threading. Journal of Biomolecular NMR. 70(1). 33–51. 5 indexed citations
6.
Berjanskii, Mark & David S. Wishart. (2017). Unraveling the meaning of chemical shifts in protein NMR. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics. 1865(11). 1564–1576. 24 indexed citations
7.
Berjanskii, Mark, David Arndt, Yongjie Liang, & David S. Wishart. (2015). A robust algorithm for optimizing protein structures with NMR chemical shifts. Journal of Biomolecular NMR. 63(3). 255–264. 7 indexed citations
8.
Berjanskii, Mark, et al.. (2012). Exploring the essential collective dynamics of interacting proteins: Application to prion protein dimers. Proteins Structure Function and Bioinformatics. 80(7). 1847–1865. 17 indexed citations
9.
Berjanskii, Mark, Jianjun Zhou, Yongjie Liang, Guohui Lin, & David S. Wishart. (2012). Resolution-by-proxy: a simple measure for assessing and comparing the overall quality of NMR protein structures. Journal of Biomolecular NMR. 53(3). 167–180. 58 indexed citations
10.
Santo, Kolattukudy P., Mark Berjanskii, David S. Wishart, & Maria Stepanova. (2011). Comparative analysis of essential collective dynamics and NMR-derived flexibility profiles in evolutionarily diverse prion proteins. Prion. 5(3). 188–200. 19 indexed citations
11.
Pérez, Rolando, Trent C. Bjorndahl, Mark Berjanskii, et al.. (2011). The prion protein binds thiamine. FEBS Journal. 278(21). 4002–4014. 26 indexed citations
12.
Berjanskii, Mark, Yu‐He Liang, Jianmin Zhou, et al.. (2010). PROSESS: a protein structure evaluation suite and server. Nucleic Acids Research. 38(Web Server). W633–W640. 67 indexed citations
13.
Cruz, J. A., et al.. (2008). PROTEUS2: a web server for comprehensive protein structure prediction and structure-based annotation. Nucleic Acids Research. 36(Web Server). W202–W209. 78 indexed citations
14.
Wishart, David S., D. Arndt, Mark Berjanskii, et al.. (2008). CS23D: a web server for rapid protein structure generation using NMR chemical shifts and sequence data. Nucleic Acids Research. 36(Web Server). W496–W502. 170 indexed citations
15.
Berjanskii, Mark & David S. Wishart. (2007). The RCI server: rapid and accurate calculation of protein flexibility using chemical shifts. Nucleic Acids Research. 35(Web Server). W531–W537. 55 indexed citations
16.
Berjanskii, Mark & David S. Wishart. (2007). Application of the random coil index to studying protein flexibility. Journal of Biomolecular NMR. 40(1). 31–48. 100 indexed citations
17.
Wishart, David S., D. Arndt, Mark Berjanskii, et al.. (2007). PPT-DB: the protein property prediction and testing database. Nucleic Acids Research. 36(Database). D222–D229. 18 indexed citations
18.
Berjanskii, Mark, et al.. (2006). PREDITOR: a web server for predicting protein torsion angle restraints. Nucleic Acids Research. 34(Web Server). W63–W69. 161 indexed citations
19.
Berjanskii, Mark & David S. Wishart. (2006). NMR: prediction of protein flexibility. Nature Protocols. 1(2). 683–688. 70 indexed citations
20.
Berjanskii, Mark, M I Riley, Anyong Xie, et al.. (2000). NMR Structure of the N-terminal J Domain of Murine Polyomavirus T Antigens. Journal of Biological Chemistry. 275(46). 36094–36103. 35 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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