Kasper Lamberth

6.4k total citations · 3 hit papers
41 papers, 4.7k citations indexed

About

Kasper Lamberth is a scholar working on Molecular Biology, Immunology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Kasper Lamberth has authored 41 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 27 papers in Immunology and 8 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Kasper Lamberth's work include vaccines and immunoinformatics approaches (26 papers), Immunotherapy and Immune Responses (20 papers) and T-cell and B-cell Immunology (10 papers). Kasper Lamberth is often cited by papers focused on vaccines and immunoinformatics approaches (26 papers), Immunotherapy and Immune Responses (20 papers) and T-cell and B-cell Immunology (10 papers). Kasper Lamberth collaborates with scholars based in Denmark, United States and Germany. Kasper Lamberth's co-authors include Søren Buus, Morten Nielsen, Ole Lund, Claus Lundegaard, Mikkel Harndahl, Søren Brunak, Mette Voldby Larsen, Peder Worning, Sanne Lise Lauemøller and Sune Justesen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Immunology.

In The Last Decade

Kasper Lamberth

41 papers receiving 4.6k citations

Hit Papers

align trajectories

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.

Reliable prediction of T‐cell epitopes using neural networks with novel sequence representations

2003 832 citations Morten Nielsen, Claus Lundegaard et al. Protein Science profile →
Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction

2007 721 citations Mette Voldby Larsen, Claus Lundegaard et al. profile →
NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8–11

2008 591 citations Claus Lundegaard, Kasper Lamberth et al. Nucleic Acids Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kasper Lamberth Denmark	26	3.4k	2.7k	1.3k	731	627	41	4.7k
Sinu Paul United States	25	3.0k 0.9×	2.2k 0.8×	1.1k 0.8×	619 0.8×	1.2k 2.0×	42	4.5k
Paolo Marcatili Denmark	31	4.0k 1.2×	1.8k 0.7×	1.6k 1.3×	474 0.6×	761 1.2×	78	5.3k
Can Keşmir Netherlands	33	3.0k 0.9×	3.1k 1.1×	916 0.7×	673 0.9×	706 1.1×	84	5.5k
Julia Ponomarenko Spain	31	4.1k 1.2×	1.7k 0.6×	1.2k 1.0×	975 1.3×	794 1.3×	74	5.5k
Jeff Alexander United States	42	1.7k 0.5×	3.6k 1.3×	668 0.5×	1.2k 1.6×	660 1.1×	89	5.5k
Carla Oseroff United States	39	2.4k 0.7×	4.2k 1.6×	986 0.8×	1.7k 2.3×	615 1.0×	60	6.0k
Randi Vita United States	23	2.8k 0.8×	1.9k 0.7×	1000 0.8×	760 1.0×	904 1.4×	45	4.3k
Claus Lundegaard Denmark	33	6.4k 1.9×	4.0k 1.5×	2.3k 1.8×	1.0k 1.4×	1.1k 1.7×	46	8.1k
Robert G. Urban United States	22	2.0k 0.6×	5.1k 1.9×	1.4k 1.1×	855 1.2×	482 0.8×	33	7.0k
Joshy Jacob United States	33	1.3k 0.4×	4.3k 1.6×	909 0.7×	1.1k 1.6×	533 0.9×	60	5.9k

Countries citing papers authored by Kasper Lamberth

Since Specialization

Citations

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

Fields of papers citing papers by Kasper Lamberth

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kasper Lamberth

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Hach, Morten, Kim F. Haselmann, Kasper Lamberth, et al.. (2024). Impact of Manufacturing Process and Compounding on Properties and Quality of Follow-On GLP-1 Polypeptide Drugs. Pharmaceutical Research. 41(10). 1991–2014. 5 indexed citations

Schultz, Heidi S., Søren Østergaard, John Sidney, Kasper Lamberth, & Alessandro Sette. (2018). The effect of acylation with fatty acids and other modifications on HLA class II:peptide binding and T cell stimulation for three model peptides. PLoS ONE. 13(5). e0197407–e0197407. 12 indexed citations

Schultz, Heidi S., et al.. (2017). Quantitative analysis of the CD4+ T cell response to therapeutic antibodies in healthy donors using a novel T cell:PBMC assay. PLoS ONE. 12(5). e0178544–e0178544. 33 indexed citations

Cox, Jennifer H., Henrik Søndergaard, Kirstine Roepstorff, et al.. (2013). Antibody-Mediated Targeting of the Orai1 Calcium Channel Inhibits T Cell Function. PLoS ONE. 8(12). e82944–e82944. 48 indexed citations

Pedersen, Lasse Eggers, Mikkel Harndahl, Michael Rasmussen, et al.. (2011). Porcine major histocompatibility complex (MHC) class I molecules and analysis of their peptide-binding specificities. Immunogenetics. 63(12). 821–834. 40 indexed citations

Lund, Ole, Eduardo J. M. Nascimento, Milton Maciel, et al.. (2011). Human Leukocyte Antigen (HLA) Class I Restricted Epitope Discovery in Yellow Fewer and Dengue Viruses: Importance of HLA Binding Strength. PLoS ONE. 6(10). e26494–e26494. 25 indexed citations

Riedl, Petra, Andreas Wieland, Kasper Lamberth, et al.. (2009). Elimination of Immunodominant Epitopes from Multispecific DNA-Based Vaccines Allows Induction of CD8 T Cells That Have a Striking Antiviral Potential. The Journal of Immunology. 183(1). 370–380. 31 indexed citations

Tenzer, Stefan, Edmund G. Wee, Anne Burgevin, et al.. (2009). Antigen processing influences HIV-specific cytotoxic T lymphocyte immunodominance. Nature Immunology. 10(6). 636–646. 155 indexed citations

Justesen, Sune, et al.. (2009). Functional recombinant MHC class II molecules and high-throughput peptide-binding assays. PubMed. 5(1). 2–2. 46 indexed citations

10.

Justesen, Sune, et al.. (2009). Recombinant chymosin used for exact and complete removal of a prochymosin derived fusion tag releasing intact native target protein. Protein Science. 18(5). 1023–1032. 5 indexed citations

11.

Lundegaard, Claus, Kasper Lamberth, Mikkel Harndahl, et al.. (2008). NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8–11. Nucleic Acids Research. 36(suppl_2). W509–W512. 591 indexed citations breakdown →

12.

Wang, Mingjun, Kasper Lamberth, Mikkel Harndahl, et al.. (2008). Modified Human Beta 2‐Microglobulin (desLys⁵⁸) Displays Decreased Affinity for the Heavy Chain of MHC Class I and Induces Nitric Oxide Production and Apoptosis. Scandinavian Journal of Immunology. 69(3). 203–212. 3 indexed citations

13.

Nielsen, Morten, Claus Lundegaard, Thomas Blicher, et al.. (2007). NetMHCpan, a Method for Quantitative Predictions of Peptide Binding to Any HLA-A and -B Locus Protein of Known Sequence. PLoS ONE. 2(8). e796–e796. 475 indexed citations

14.

Wang, Mingjun, Kasper Lamberth, Mikkel Harndahl, et al.. (2006). CTL epitopes for influenza A including the H5N1 bird flu; genome-, pathogen-, and HLA-wide screening. Vaccine. 25(15). 2823–2831. 92 indexed citations

15.

Peters, Bjoern, Huynh‐Hoa Bui, Sune Pletscher-Frankild, et al.. (2006). A Community Resource Benchmarking Predictions of Peptide Binding to MHC-I Molecules. PLoS Computational Biology. 2(6). e65–e65. 230 indexed citations

16.

Lund, Ole, Morten Nielsen, Can Keşmir, et al.. (2004). Definition of supertypes for HLA molecules using clustering of specificity matrices. Immunogenetics. 55(12). 797–810. 221 indexed citations

17.

Sylvester‐Hvid, Christina, Morten Nielsen, Kasper Lamberth, et al.. (2004). SARS CTL vaccine candidates; HLA supertype‐, genome‐wide scanning and biochemical validation. Tissue Antigens. 63(5). 395–400. 47 indexed citations

18.

Nielsen, Morten, Claus Lundegaard, Peder Worning, et al.. (2004). Improved prediction of MHC class I and class II epitopes using a novel Gibbs sampling approach. Bioinformatics. 20(9). 1388–1397. 212 indexed citations

19.

Jinquan, Tan, Henrik H. Jacobi, Jing Chen, et al.. (2003). CCR3 Expression Induced by IL-2 and IL-4 Functioning as a Death Receptor for B Cells. The Journal of Immunology. 171(4). 1722–1731. 25 indexed citations

20.

Nielsen, Morten, Claus Lundegaard, Peder Worning, et al.. (2003). Reliable prediction of T‐cell epitopes using neural networks with novel sequence representations. Protein Science. 12(5). 1007–1017. 832 indexed citations breakdown →

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.

Explore authors with similar magnitude of impact