Michael Laimighofer

757 total citations
10 papers, 292 citations indexed

About

Michael Laimighofer is a scholar working on Surgery, Genetics and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Michael Laimighofer has authored 10 papers receiving a total of 292 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Surgery, 4 papers in Genetics and 3 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Michael Laimighofer's work include Diabetes and associated disorders (4 papers), Pancreatic function and diabetes (4 papers) and Diabetes Management and Research (3 papers). Michael Laimighofer is often cited by papers focused on Diabetes and associated disorders (4 papers), Pancreatic function and diabetes (4 papers) and Diabetes Management and Research (3 papers). Michael Laimighofer collaborates with scholars based in Germany, United States and United Kingdom. Michael Laimighofer's co-authors include Fabian J. Theis, Jan Krumsiek, Simone Wahl, Jerzy Adamski, Claudia Langenberg, Kieu Trinh, Johannes Raffler, Sophie Molnos, Christian Gieger and Harald Grallert and has published in prestigious journals such as Scientific Reports, Diabetologia and Clinica Chimica Acta.

In The Last Decade

Michael Laimighofer

10 papers receiving 288 citations

Peers

Michael Laimighofer

GENET

SURGE

EDM

PHYSI

Tonia de las Heras Gala Germany

Justina Ucheojor Onwuka China

Nirja Kaka India

Yeela Talmor‐Barkan Israel

Eleftherios Panteris Greece

Xinhua Ye China

Elizabeth Brown United States

Hanna Kwiendacz Poland

Sahar Sharaf Egypt

Irina Irincheeva Switzerland

Tonia de las Heras Gala Germany

Michael Laimighofer

94 ×0.9

51 ×0.7

GENET

87 ×1.5

SURGE

119 ×2.4

EDM

97 ×2.0

PHYSI

Citations per year, relative to Michael Laimighofer Michael Laimighofer (= 1×) peers Tonia de las Heras Gala

Countries citing papers authored by Michael Laimighofer

Since Specialization

Citations

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

Fields of papers citing papers by Michael Laimighofer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Laimighofer

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

All Works

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10 of 10 papers shown

Mühlbacher, A., Caroline Tinguely, Peter Findeisen, et al.. (2021). Multicentre Performance Evaluation of the Elecsys Anti-SARS-CoV-2 Immunoassay as an Aid in Determining Previous Exposure to SARS-CoV-2. Infectious Diseases and Therapy. 10(4). 2381–2397. 13 indexed citations

Fitzgerald, Robert L., Judd E. Hollander, W. Frank Peacock, et al.. (2020). The 99th percentile upper reference limit for the 5th generation cardiac troponin T assay in the United States. Clinica Chimica Acta. 504. 172–179. 11 indexed citations

Laimighofer, Michael, Fabian J. Theis, Christiane Winkler, et al.. (2019). Common patterns of gene regulation associated with Cesarean section and the development of islet autoimmunity – indications of immune cell activation. Scientific Reports. 9(1). 6250–6250. 5 indexed citations

Fitzgerald, Robert L., Judd E. Hollander, W. Frank Peacock, et al.. (2019). Analytical performance evaluation of the Elecsys® Troponin T Gen 5 STAT assay. Clinica Chimica Acta. 495. 522–528. 25 indexed citations

Böck, Andreas, Michael Laimighofer, Fabian J. Theis, et al.. (2019). A strategy for high‐dimensional multivariable analysis classifies childhood asthma phenotypes from genetic, immunological, and environmental factors. Allergy. 74(7). 1364–1373. 25 indexed citations

Trinh, Kieu, Simone Wahl, Johannes Raffler, et al.. (2018). Characterization of missing values in untargeted MS-based metabolomics data and evaluation of missing data handling strategies. Metabolomics. 14(10). 128–128. 123 indexed citations

Kindt, Alida, Michael Laimighofer, Tanja Telieps, et al.. (2017). Allele-specific methylation of type 1 diabetes susceptibility genes. Journal of Autoimmunity. 89. 63–74. 27 indexed citations

Frohnert, Brigitte I., Michael Laimighofer, Jan Krumsiek, et al.. (2017). Prediction of type 1 diabetes using a genetic risk model in the Diabetes Autoimmunity Study in the Young. Pediatric Diabetes. 19(2). 277–283. 20 indexed citations

Toerne, Christine von, Michael Laimighofer, Peter Achenbach, et al.. (2016). Peptide serum markers in islet autoantibody-positive children. Diabetologia. 60(2). 287–295. 25 indexed citations

10.

Laimighofer, Michael, Jan Krumsiek, Florian Buettner, & Fabian J. Theis. (2016). Unbiased Prediction and Feature Selection in High-Dimensional Survival Regression. Journal of Computational Biology. 23(4). 279–290. 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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