Sándor Szalma

4.4k total citations
32 papers, 820 citations indexed

About

Sándor Szalma is a scholar working on Molecular Biology, Spectroscopy and Organic Chemistry. According to data from OpenAlex, Sándor Szalma has authored 32 papers receiving a total of 820 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 7 papers in Spectroscopy and 4 papers in Organic Chemistry. Recurrent topics in Sándor Szalma's work include Bioinformatics and Genomic Networks (7 papers), Protein Structure and Dynamics (4 papers) and Advanced NMR Techniques and Applications (4 papers). Sándor Szalma is often cited by papers focused on Bioinformatics and Genomic Networks (7 papers), Protein Structure and Dynamics (4 papers) and Advanced NMR Techniques and Applications (4 papers). Sándor Szalma collaborates with scholars based in United States, Hungary and Germany. Sándor Szalma's co-authors include Lisa Yan, Velin Z. Spassov, Gyan Bhanot, Eric Perakslis, Changquan Huang, Michael Seiler, Frank U. Axe, Scott D. Bembenek, Venkata Koka and István Pelczer and has published in prestigious journals such as Chemical Reviews, Journal of the American Chemical Society and Blood.

In The Last Decade

Sándor Szalma

29 papers receiving 790 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sándor Szalma United States 14 602 86 78 72 55 32 820
Jianfang Chen China 19 627 1.0× 50 0.6× 82 1.1× 159 2.2× 40 0.7× 58 1.1k
Edgar Specker Germany 16 405 0.7× 129 1.5× 63 0.8× 54 0.8× 72 1.3× 36 781
O.V. Gnedenko Russia 17 518 0.9× 75 0.9× 89 1.1× 37 0.5× 14 0.3× 77 887
Travis P. Schrank United States 15 588 1.0× 74 0.9× 32 0.4× 72 1.0× 64 1.2× 35 795
Robert H. Newman United States 18 839 1.4× 135 1.6× 43 0.6× 34 0.5× 37 0.7× 57 1.2k
Yung-Hao Wong Taiwan 11 358 0.6× 55 0.6× 69 0.9× 52 0.7× 13 0.2× 20 644
Anita Palma Italy 9 893 1.5× 64 0.7× 197 2.5× 60 0.8× 38 0.7× 11 1.1k
Setsuko Nakagawa Japan 19 512 0.9× 130 1.5× 51 0.7× 31 0.4× 37 0.7× 81 1.1k
Xingcheng Lin United States 16 645 1.1× 24 0.3× 72 0.9× 40 0.6× 32 0.6× 41 853
William W. Chen United States 13 872 1.4× 42 0.5× 120 1.5× 60 0.8× 14 0.3× 14 1.1k

Countries citing papers authored by Sándor Szalma

Since Specialization
Citations

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

Fields of papers citing papers by Sándor Szalma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sándor Szalma

This figure shows the co-authorship network connecting the top 25 collaborators of Sándor Szalma. A scholar is included among the top collaborators of Sándor Szalma 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 Sándor Szalma. Sándor Szalma 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.
Mahedy, Liam, Emma L. Anderson, Kate Tilling, et al.. (2024). Investigation of genetic determinants of cognitive change in later life. Translational Psychiatry. 14(1). 31–31. 3 indexed citations
2.
Córdova‐Palomera, Aldo, et al.. (2023). Assessing the potential of polygenic scores to strengthen medical risk prediction models of COVID-19. PLoS ONE. 18(5). e0285991–e0285991.
3.
Stroganov, Oleg V., et al.. (2022). Mapping of UK Biobank clinical codes: Challenges and possible solutions. PLoS ONE. 17(12). e0275816–e0275816. 10 indexed citations
4.
Sadaei, Hossein Javedani, Aldo Córdova‐Palomera, Jong Hun Lee, et al.. (2022). Genetically-informed prediction of short-term Parkinson’s disease progression. npj Parkinson s Disease. 8(1). 143–143. 10 indexed citations
5.
Pratt, Dexter, Jing Chen, Rudolf Pillich, et al.. (2015). NDEx, the Network Data Exchange. Cell Systems. 1(4). 302–305. 164 indexed citations
6.
Perakslis, Eric, et al.. (2010). How Informatics Can Potentiate Precompetitive Open-Source Collaboration to Jump-Start Drug Discovery and Development. Clinical Pharmacology & Therapeutics. 87(5). 614–616. 17 indexed citations
7.
Szalma, Sándor, et al.. (2010). Effective knowledge management in translational medicine. Journal of Translational Medicine. 8(1). 68–68. 63 indexed citations
8.
Zhang, Yi, et al.. (2010). Robust multi-tissue gene panel for cancer detection. BMC Cancer. 10(1). 319–319. 9 indexed citations
9.
Oláh, Zoltán, Katalin Jósvay, László Pecze, et al.. (2007). Anti-calmodulins and Tricyclic Adjuvants in Pain Therapy Block the TRPV1 Channel. PLoS ONE. 2(6). e545–e545. 25 indexed citations
10.
11.
Axe, Frank U., Scott D. Bembenek, & Sándor Szalma. (2005). Three-dimensional models of histamine H3 receptor antagonist complexes and their pharmacophore. Journal of Molecular Graphics and Modelling. 24(6). 456–464. 52 indexed citations
12.
Spassov, Velin Z., et al.. (2004). A hidden Markov model with molecular mechanics energy-scoring function for transmembrane helix prediction. Computational Biology and Chemistry. 28(4). 265–274. 11 indexed citations
13.
Unger, S. W., et al.. (2004). Automated evaluation of chemical shift perturbation spectra: New approaches to quantitative analysis of receptor-ligand interaction NMR spectra. Journal of Biomolecular NMR. 29(4). 491–504. 18 indexed citations
14.
Yan, Lisa, et al.. (2003). Assessment of putative protein targets derived from the SARS genome. FEBS Letters. 554(3). 257–263. 18 indexed citations
15.
Milik, Mariusz, Sándor Szalma, & Krzysztof Olszewski. (2003). Common Structural Cliques: a tool for protein structure and function analysis. Protein Engineering Design and Selection. 16(8). 543–552. 35 indexed citations
16.
Badger, John, Ravindra Kumar, Ping Yip, & Sándor Szalma. (1999). New features and enhancements in the X‐PLOR computer program. Proteins Structure Function and Bioinformatics. 35(1). 25–33. 1 indexed citations
17.
Szalma, Sándor, et al.. (1995). Determination of 3J(H infi supN ,C infi sup? ) coupling constants in proteins with the C?-FIDS method. Journal of Biomolecular NMR. 6(3). 237–44.
18.
Szalma, Sándor, et al.. (1995). New principle for the determination of coupling constants that largely suppresses differential relaxation effects. Journal of the American Chemical Society. 117(41). 10389–10390. 54 indexed citations
19.
Szalma, Sándor, István Pelczer, Philip N. Borer, & George C. Levy. (1991). Selective discrete fourier transformation, an alternative approach for multidimensional NMR data processing. Journal of Magnetic Resonance (1969). 91(1). 194–198. 4 indexed citations
20.
Szalma, Sándor. (1989). TRAWIATA—An efficient algorithm to decrease the transformation time of multidimensional NMR arrays. Journal of Magnetic Resonance (1969). 83(2). 400–403. 1 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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