Daniel Eklund

827 total citations
30 papers, 525 citations indexed

About

Daniel Eklund is a scholar working on Molecular Biology, Immunology and Infectious Diseases. According to data from OpenAlex, Daniel Eklund has authored 30 papers receiving a total of 525 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 12 papers in Immunology and 8 papers in Infectious Diseases. Recurrent topics in Daniel Eklund's work include Inflammasome and immune disorders (9 papers), Tuberculosis Research and Epidemiology (8 papers) and Tryptophan and brain disorders (6 papers). Daniel Eklund is often cited by papers focused on Inflammasome and immune disorders (9 papers), Tuberculosis Research and Epidemiology (8 papers) and Tryptophan and brain disorders (6 papers). Daniel Eklund collaborates with scholars based in Sweden, Italy and India. Daniel Eklund's co-authors include Maria Lerm, Olle Stendahl, Amanda Welin, Johanna Raffetseder, Eva Särndahl, Henrik Andersson, Robert Blomgran, Alexander Persson, Thomas Schön and Peter Söderkvist and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Daniel Eklund

26 papers receiving 513 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Eklund Sweden 13 243 186 175 161 42 30 525
Joo‐Yong Jung United States 11 106 0.4× 204 1.1× 99 0.6× 113 0.7× 30 0.7× 12 428
Brenda Marquina‐Castillo Mexico 16 338 1.4× 201 1.1× 253 1.4× 261 1.6× 107 2.5× 44 841
Raymond Widen United States 15 129 0.5× 101 0.5× 97 0.6× 134 0.8× 39 0.9× 31 610
Zhao Jia China 13 212 0.9× 431 2.3× 184 1.1× 129 0.8× 24 0.6× 37 883
Ross McFarland United States 5 266 1.1× 174 0.9× 120 0.7× 210 1.3× 134 3.2× 6 595
Mohammed Amir India 11 158 0.7× 155 0.8× 135 0.8× 92 0.6× 35 0.8× 20 476
Carlos Guerra Spain 11 117 0.5× 92 0.5× 134 0.8× 111 0.7× 31 0.7× 28 436
Andrew J. McDermott United States 14 312 1.3× 173 0.9× 301 1.7× 221 1.4× 79 1.9× 21 760
Chidchamai Kewcharoenwong Thailand 13 97 0.4× 134 0.7× 130 0.7× 255 1.6× 51 1.2× 27 600
José Cândido Ferraz Brazil 10 357 1.5× 270 1.5× 155 0.9× 294 1.8× 93 2.2× 15 670

Countries citing papers authored by Daniel Eklund

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Eklund

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Eklund

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Eklund. A scholar is included among the top collaborators of Daniel Eklund 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 Daniel Eklund. Daniel Eklund 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
3.
Eklund, Daniel, et al.. (2023). Predicting sepsis using a combination of clinical information and molecular immune markers sampled in the ambulance. Scientific Reports. 13(1). 14917–14917. 4 indexed citations
4.
Eklund, Daniel, et al.. (2023). Altered insulin sensitivity and immune function in patients with colorectal cancer. Clinical Nutrition ESPEN. 58. 193–200.
5.
Krantz, Marcus, et al.. (2023). A detailed molecular network map and model of the NLRP3 inflammasome. Frontiers in Immunology. 14. 1233680–1233680. 9 indexed citations
6.
Cedersund, Gunnar, Daniel Eklund, Robert L. Kruse, et al.. (2023). Mathematical models disentangle the role of IL-10 feedbacks in human monocytes upon proinflammatory activation. Journal of Biological Chemistry. 299(10). 105205–105205. 2 indexed citations
7.
Henriksson, Elisabet Welin, et al.. (2022). Rituximab as an adjunctive treatment for schizophrenia spectrum disorder or obsessive-compulsive disorder: Two open-label pilot studies on treatment-resistant patients. Journal of Psychiatric Research. 158. 319–329. 13 indexed citations
8.
McGlinchey, Aidan, Matej Orešič, Mats B. Humble, et al.. (2021). Potential Transdiagnostic Lipid Mediators of Inflammatory Activity in Individuals With Serious Mental Illness. Frontiers in Psychiatry. 12. 778325–778325. 7 indexed citations
10.
Nyman, Elin, Maria Lindh, Alexander Persson, et al.. (2020). Mechanisms of a Sustained Anti‐inflammatory Drug Response in Alveolar Macrophages Unraveled with Mathematical Modeling. CPT Pharmacometrics & Systems Pharmacology. 9(12). 707–717. 3 indexed citations
11.
Eklund, Daniel, et al.. (2019). Increased inflammasome activity in markedly ill psychiatric patients: An explorative study. Journal of Neuroimmunology. 339. 577119–577119. 17 indexed citations
12.
Eklund, Daniel, et al.. (2018). Immune profile in relation to sex steroid cyclicity in healthy women and women with multiple sclerosis. Journal of Reproductive Immunology. 126. 53–59. 8 indexed citations
13.
Hellberg, Sandra, Daniel Eklund, Danuta R. Gawel, et al.. (2016). Dynamic Response Genes in CD4+ T Cells Reveal a Network of Interactive Proteins that Classifies Disease Activity in Multiple Sclerosis. Cell Reports. 16(11). 2928–2939. 38 indexed citations
14.
Raffetseder, Johanna, Elsje Pienaar, Robert Blomgran, et al.. (2014). Replication Rates of Mycobacterium tuberculosis in Human Macrophages Do Not Correlate with Mycobacterial Antibiotic Susceptibility. PLoS ONE. 9(11). e112426–e112426. 40 indexed citations
15.
Kalsum, Sadaf, Marie Larsson, Henrik Andersson, et al.. (2014). Antimycobacterial activity of selected medicinal plants traditionally used in Sudan to treat infectious diseases. Journal of Ethnopharmacology. 157. 134–139. 23 indexed citations
16.
Eklund, Daniel, Marie Larsson, Amanda Welin, et al.. (2013). Alveolar macrophages from patients with tuberculosis exhibit reduced capacity of restricting growth of Mycobacterium tuberculosis: a pilot study of vitamin D stimulation in vitro. KTH Publication Database DiVA (KTH Royal Institute of Technology). 1(1). 6–6. 2 indexed citations
17.
Eklund, Daniel, Amanda Welin, Henrik Andersson, et al.. (2013). Human Gene Variants Linked to Enhanced NLRP3 Activity Limit Intramacrophage Growth of Mycobacterium tuberculosis. The Journal of Infectious Diseases. 209(5). 749–753. 45 indexed citations
18.
Eklund, Daniel. (2013). Mycobacterium tuberculosis and the human macrophage : shifting the balance through inflammasome activation. Linköping University Electronic Press eBooks. 1 indexed citations
19.
Eklund, Daniel, Hans Lennart Persson, Marie Larsson, et al.. (2012). Vitamin D enhances IL-1β secretion and restricts growth of Mycobacterium tuberculosis in macrophages from TB patients. SHILAP Revista de lepidopterología. 2(1). 18–25. 19 indexed citations
20.
Persson, Alexander, et al.. (2009). Induction of apoptosis in human neutrophils by Mycobacterium tuberculosis is dependent on mature bacterial lipoproteins. Microbial Pathogenesis. 47(3). 143–150. 18 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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