Anneli Karlsson

6.3k total citations · 3 hit papers
14 papers, 3.8k citations indexed

About

Anneli Karlsson is a scholar working on Molecular Biology, Immunology and Surgery. According to data from OpenAlex, Anneli Karlsson has authored 14 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 5 papers in Immunology and 3 papers in Surgery. Recurrent topics in Anneli Karlsson's work include Computational Drug Discovery Methods (3 papers), Helicobacter pylori-related gastroenterology studies (3 papers) and Galectins and Cancer Biology (3 papers). Anneli Karlsson is often cited by papers focused on Computational Drug Discovery Methods (3 papers), Helicobacter pylori-related gastroenterology studies (3 papers) and Galectins and Cancer Biology (3 papers). Anneli Karlsson collaborates with scholars based in Sweden, United Kingdom and United States. Anneli Karlsson's co-authors include Anna Gaulton, John P. Overington, Anne Hersey, A. Patrícia Bento, Rita Santos, Bissan Al‐Lazikani, Tudor I. Oprea, Oleg Ursu, Cristian Bologa and Jon Chambers and has published in prestigious journals such as Nucleic Acids Research, Nature Reviews Drug Discovery and The FASEB Journal.

In The Last Decade

Anneli Karlsson

13 papers receiving 3.8k citations

Hit Papers

align trajectories sort by overperformance

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.

A comprehensive map of molecular drug targets

2016 1.6k citations Rita Santos, Oleg Ursu et al. Nature Reviews Drug Discovery profile →
The ChEMBL database in 2017

2016 1.6k citations Anna Gaulton, Anne Hersey et al. Nucleic Acids Research profile →
The druggable genome and support for target identification and validation in drug development

2017 494 citations Chris Finan, Anna Gaulton et al. Science Translational Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Anneli Karlsson Sweden	9	2.6k	1.5k	395	345	329	14	3.8k
Rita Santos United Kingdom	7	2.3k 0.9×	1.3k 0.8×	286 0.7×	272 0.8×	295 0.9×	10	3.3k
Claudio N. Cavasotto United States	37	2.7k 1.0×	1.8k 1.2×	431 1.1×	349 1.0×	221 0.7×	85	4.2k
Oleg Ursu United States	23	2.4k 0.9×	1.2k 0.8×	173 0.4×	295 0.9×	201 0.6×	51	3.8k
Peter Schmidtke Germany	18	2.3k 0.9×	1.1k 0.7×	398 1.0×	355 1.0×	182 0.6×	26	3.2k
Paul S. Charifson United States	29	2.9k 1.1×	1.3k 0.9×	463 1.2×	357 1.0×	196 0.6×	55	4.0k
David Michalovich United Kingdom	21	3.5k 1.4×	2.2k 1.4×	479 1.2×	503 1.5×	394 1.2×	25	6.0k
Daniel Seeliger Germany	24	2.5k 1.0×	798 0.5×	475 1.2×	241 0.7×	144 0.4×	43	3.8k
Douglas S. Auld United States	42	4.8k 1.8×	1.1k 0.7×	328 0.8×	353 1.0×	365 1.1×	120	7.1k
Gerard J. P. van Westen Netherlands	34	2.1k 0.8×	1.5k 1.0×	442 1.1×	299 0.9×	100 0.3×	130	3.2k
Steven W. Muchmore United States	26	3.3k 1.3×	761 0.5×	425 1.1×	323 0.9×	491 1.5×	49	4.6k

Countries citing papers authored by Anneli Karlsson

Since Specialization

Citations

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

Fields of papers citing papers by Anneli Karlsson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anneli Karlsson

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

All Works

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14 of 14 papers shown

Lomax, Jane, et al.. (2023). An extension of the BioAssay Ontology to include pharmacokinetic/pharmacodynamic terminology for the enrichment of scientific workflows. Journal of Biomedical Semantics. 14(1). 10–10.

Wagner, Thomas, et al.. (2021). Beetles in an urban community garden can indicate global warming. Duo Research Archive (University of Oslo). 1 indexed citations

Finan, Chris, Anna Gaulton, Felix Krüger, et al.. (2017). The druggable genome and support for target identification and validation in drug development. Science Translational Medicine. 9(383). 494 indexed citations breakdown →

Gaulton, Anna, Anne Hersey, Michał Nowotka, et al.. (2016). The ChEMBL database in 2017. Nucleic Acids Research. 45(D1). D945–D954. 1589 indexed citations breakdown →

Santos, Rita, Oleg Ursu, Anna Gaulton, et al.. (2016). A comprehensive map of molecular drug targets. Nature Reviews Drug Discovery. 16(1). 19–34. 1594 indexed citations breakdown →

Karlsson, Anneli, et al.. (2012). Association between cagA and vacA genotypes and pathogenesis in a Helicobacter pylori infected population from South-eastern Sweden. BMC Microbiology. 12(1). 129–129. 24 indexed citations

Karlsson, Anneli, et al.. (2011). Variation in number of cagA EPIYA-C phosphorylation motifs between cultured Helicobacter pylori and biopsy strain DNA. Infection Genetics and Evolution. 12(1). 175–179. 6 indexed citations

Monstein, Hans‐Jürg, et al.. (2010). Application of PCR amplicon sequencing using a single primer pair in PCR amplification to assess variations in Helicobacter pylori CagA EPIYA tyrosine phosphorylation motifs. BMC Research Notes. 3(1). 35–35. 11 indexed citations

Carlsson, Marianne, et al.. (2009). Purification of MBP‐ and Strep‐tag II proteins. The FASEB Journal. 23(S1). 1 indexed citations

10.

Karlsson, Anneli, et al.. (2008). Notch1 is a frequent mutational target in chemically induced lymphoma in mouse. International Journal of Cancer. 123(11). 2720–2724. 2 indexed citations

11.

Karlsson, Anneli, et al.. (2007). Bcl11bmutations identified in murine lymphomas increase the proliferation rate of hematopoietic progenitor cells. BMC Cancer. 7(1). 195–195. 12 indexed citations

12.

Lund, Lars H., Bartek Zuber, Anneli Karlsson, et al.. (2003). Signal sequence deletion and fusion to tetanus toxoid epitope augment antitumor immune responses to a human carcinoembryonic antigen (CEA) plasmid DNA vaccine in a murine test system. Cancer Gene Therapy. 10(5). 365–376. 30 indexed citations

13.

Karlsson, Anneli, Peter Söderkvist, & Shi‐Mei Zhuang. (2002). Point mutations and deletions in the znfn1a1/ikaros gene in chemically induced murine lymphomas.. PubMed. 62(9). 2650–3. 15 indexed citations

14.

Sunnerhagen, Per, et al.. (1986). Molecular cloning and characterization of small polydisperse circular DNA from mouse 3T6 cells. Nucleic Acids Research. 14(20). 7823–7838. 43 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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