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.
Eosinophilic Inflammation in Asthma
19902.1k citationsI. Enander, Per Venge et al.profile →
Markers of Myocardial Damage and Inflammation in Relation to Long-Term Mortality in Unstable Coronary Artery Disease
2000968 citationsBertil Lindahl, Per Venge et al.profile →
Bronchoalveolar eosinophilia during allergen-induced late asthmatic reactions.
This map shows the geographic impact of Per Venge'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 Per Venge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Per Venge more than expected).
This network shows the impact of papers produced by Per Venge. 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 Per Venge. The network helps show where Per Venge may publish in the future.
Co-authorship network of co-authors of Per Venge
This figure shows the co-authorship network connecting the top 25 collaborators of Per Venge.
A scholar is included among the top collaborators of Per Venge 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 Per Venge. Per Venge is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Nordenskjöld, Anna M., Håkan Åhlström, Tomas Bjerner, et al.. (2014). Cardiac troponin I, NT-proBNP and galactin-3 are elevated in patients with unrecognized myocardial infarction detected by cardiac magnetic resonance imaging. European Heart Journal. 35. 1002–1003.4 indexed citations
Bafadhel, Mona, Susan McKenna, Sarah Terry, et al.. (2012). Blood Eosinophils to Direct Corticosteroid Treatment of Exacerbations of Chronic Obstructive Pulmonary Disease: A Randomized Placebo-Controlled Trial. American Journal of Respiratory and Critical Care Medicine. 186(1). 48–55.422 indexed citations breakdown →
6.
Thygesen, Kristian, Johannes Mair, Hugo A. Katus, et al.. (2010). Recommendations for the use of cardiac troponin measurement in acute cardiac care. European Heart Journal. 31(18). 2197–2204.457 indexed citations breakdown →
Lagerqvist, Bo, Erik Diderholm, Bertil Lindahl, et al.. (2000). Coronary angiography in relation to troponin T level in patients with unstable coronary artery disease a FRISC-II substudy.. Circulation. 102(18). 2860.2 indexed citations
Lagerqvist, Bo, Erik Diderholm, Bertil Lindahl, et al.. (2000). Coronary angiography in relation to troponin T level in patients with unstable coronary artery disease (UCAD) - a FRISC-2 substudy. European Heart Journal. 21. 2530.1 indexed citations
Venge, Per, et al.. (1985). Inflammation : basic mechanisms, tissue injuring principles, and clinical models.19 indexed citations
18.
Venge, Per, et al.. (1981). The inflammatory process : an introduction to the study of cellular and humoral mechanisms.3 indexed citations
19.
Dahl, Rolf & Per Venge. (1978). Blood eosinophil leucocyte and eosinophil cationic protein. In vivo study of the influence of beta-2-adrenergic drugs and steroid medication.. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 59(6). 319–22.19 indexed citations
20.
Hällgren, Roger, Linda Jansson, & Per Venge. (1977). Kinetic studies of phagocytosis of IgG-coated latex particles with a thrombocyte counter.. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 90(5). 786–95.28 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.