Jesper Salomon

742 total citations
11 papers, 479 citations indexed

About

Jesper Salomon is a scholar working on Molecular Biology, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Jesper Salomon has authored 11 papers receiving a total of 479 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 3 papers in Artificial Intelligence and 2 papers in Signal Processing. Recurrent topics in Jesper Salomon's work include vaccines and immunoinformatics approaches (2 papers), Machine Learning in Bioinformatics (2 papers) and Protein Structure and Dynamics (2 papers). Jesper Salomon is often cited by papers focused on vaccines and immunoinformatics approaches (2 papers), Machine Learning in Bioinformatics (2 papers) and Protein Structure and Dynamics (2 papers). Jesper Salomon collaborates with scholars based in Denmark, United Kingdom and United States. Jesper Salomon's co-authors include Darren R. Flower, Simon King, Thomas Litman, Finn Cilius Nielsen, Thomas N. Hansen, Hanni Willenbrock, Rolf Søkilde, Søren Møller, Kim Bundvig Barken and Peter Mouritzen and has published in prestigious journals such as Bioinformatics, PLoS ONE and Scientific Reports.

In The Last Decade

Jesper Salomon

11 papers receiving 463 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jesper Salomon Denmark	9	350	144	59	54	40	11	479
Huiming Peng China	13	304 0.9×	54 0.4×	10 0.2×	98 1.8×	23 0.6×	33	540
Yuhua Yao China	20	791 2.3×	107 0.7×	60 1.0×	16 0.3×	46 1.1×	65	982
German Tischler United Kingdom	11	271 0.8×	48 0.3×	79 1.3×	21 0.4×	12 0.3×	21	486
Quanzhong Liu China	11	473 1.4×	92 0.6×	53 0.9×	23 0.4×	13 0.3×	23	629
Paweł P. Łabaj Poland	15	413 1.2×	100 0.7×	21 0.4×	64 1.2×	25 0.6×	38	857
Jie Tan United States	11	498 1.4×	67 0.5×	93 1.6×	20 0.4×	26 0.7×	23	742
Raphaël Mourad France	13	507 1.4×	37 0.3×	45 0.8×	20 0.4×	15 0.4×	29	669
Ehsaneddin Asgari United States	10	715 2.0×	28 0.2×	105 1.8×	31 0.6×	48 1.2×	25	917
Huai‐Kuang Tsai Taiwan	17	530 1.5×	72 0.5×	172 2.9×	30 0.6×	7 0.2×	58	801

Countries citing papers authored by Jesper Salomon

Since Specialization

Citations

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

Fields of papers citing papers by Jesper Salomon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jesper Salomon

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

All Works

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11 of 11 papers shown

Bartels, Simon, et al.. (2024). A systematic analysis of regression models for protein engineering. PLoS Computational Biology. 20(5). e1012061–e1012061. 3 indexed citations

Han, Yuchen, Fabian Blombach, Pablo Pérez-García, et al.. (2022). A novel metagenome-derived viral RNA polymerase and its application in a cell-free expression system for metagenome screening. Scientific Reports. 12(1). 17882–17882. 4 indexed citations

Armenteros, José Juan Almagro, et al.. (2021). NetSolP: predicting protein solubility in Escherichia coli using language models. Bioinformatics. 38(4). 941–946. 45 indexed citations

Armenteros, José Juan Almagro, et al.. (2021). Deep protein representations enable recombinant protein expression prediction. Computational Biology and Chemistry. 95. 107596–107596. 11 indexed citations

Ilmberger, Nele, Simon Güllert, Bernd Wemheuer, et al.. (2014). A Comparative Metagenome Survey of the Fecal Microbiota of a Breast- and a Plant-Fed Asian Elephant Reveals an Unexpectedly High Diversity of Glycoside Hydrolase Family Enzymes. PLoS ONE. 9(9). e106707–e106707. 72 indexed citations

Andreasen, Ditte, Jacob U. Fog, William Biggs, et al.. (2010). Improved microRNA quantification in total RNA from clinical samples. Methods. 50(4). S6–S9. 85 indexed citations

Willenbrock, Hanni, Jesper Salomon, Rolf Søkilde, et al.. (2009). Quantitative miRNA expression analysis: Comparing microarrays with next-generation sequencing. RNA. 15(11). 2028–2034. 122 indexed citations

Davies, Matthew N., Pingping Guan, Martin Blythe, et al.. (2007). Using databases and data mining in vaccinology. Expert Opinion on Drug Discovery. 2(1). 19–35. 10 indexed citations

Salomon, Jesper & Darren R. Flower. (2006). Predicting Class II MHC-Peptide binding: a kernel based approach using similarity scores. BMC Bioinformatics. 7(1). 501–501. 56 indexed citations

10.

Salomon, Jesper, Simon King, & Jesper Salomon. (2002). Framewise phone classification using support vector machines. 2645–2648. 48 indexed citations

11.

Salomon, Jesper. (2001). Support Vector Machines for Phoneme Classification. 23 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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