Michael J. Mann

5.5k total citations
82 papers, 3.8k citations indexed

About

Michael J. Mann is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Surgery. According to data from OpenAlex, Michael J. Mann has authored 82 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Molecular Biology, 21 papers in Pulmonary and Respiratory Medicine and 19 papers in Surgery. Recurrent topics in Michael J. Mann's work include Electrospun Nanofibers in Biomedical Applications (12 papers), Lung Cancer Treatments and Mutations (12 papers) and Lung Cancer Diagnosis and Treatment (11 papers). Michael J. Mann is often cited by papers focused on Electrospun Nanofibers in Biomedical Applications (12 papers), Lung Cancer Treatments and Mutations (12 papers) and Lung Cancer Diagnosis and Treatment (11 papers). Michael J. Mann collaborates with scholars based in United States, China and United Kingdom. Michael J. Mann's co-authors include Victor J. Dzau, Afshin Ehsan, Lunan Zhang, Gary H. Gibbons, Giorgio Dell’Acqua, Heiko E. von der Leyen, Luis G. Melo, Philip S. Tsao, John P. Cooke and Daniel P. Griese and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Lancet and JAMA.

In The Last Decade

Michael J. Mann

81 papers receiving 3.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael J. Mann United States 31 2.0k 966 836 473 434 82 3.8k
Patricia Lemarchand France 31 1.9k 0.9× 1.2k 1.2× 439 0.5× 464 1.0× 730 1.7× 70 3.6k
John J. Castellot United States 36 2.3k 1.1× 572 0.6× 415 0.5× 269 0.6× 316 0.7× 77 4.4k
Peter Oettgen United States 46 3.3k 1.6× 738 0.8× 519 0.6× 519 1.1× 437 1.0× 85 5.8k
Bin Yu China 33 2.6k 1.3× 570 0.6× 520 0.6× 264 0.6× 457 1.1× 176 4.9k
David A. Hess Canada 34 1.8k 0.9× 1.1k 1.1× 257 0.3× 285 0.6× 405 0.9× 125 4.2k
Lisa K. Jennings United States 35 1.0k 0.5× 1.0k 1.1× 1.8k 2.2× 668 1.4× 202 0.5× 133 5.1k
Marian T. Nakada United States 32 1.4k 0.7× 465 0.5× 471 0.6× 305 0.6× 251 0.6× 57 3.5k
Bruce A. Keyt United States 31 5.1k 2.5× 680 0.7× 514 0.6× 727 1.5× 386 0.9× 79 9.9k
Colin N. Chesterman Australia 33 1.7k 0.8× 581 0.6× 379 0.5× 299 0.6× 226 0.5× 67 4.1k
Sui Zhang United States 26 1.5k 0.7× 425 0.4× 1.3k 1.5× 439 0.9× 149 0.3× 91 3.9k

Countries citing papers authored by Michael J. Mann

Since Specialization
Citations

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

Fields of papers citing papers by Michael J. Mann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael J. Mann

This figure shows the co-authorship network connecting the top 25 collaborators of Michael J. Mann. A scholar is included among the top collaborators of Michael J. Mann 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 J. Mann. Michael J. Mann 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
1.
2.
Kratz, Johannes R., Jessica Tsui, Vivianne W. Ding, et al.. (2021). Genetic and immunologic features of recurrent stage I lung adenocarcinoma. Scientific Reports. 11(1). 23690–23690. 8 indexed citations
3.
Jiang, Long, Bhairavi Tolani, Che‐Chung Yeh, et al.. (2019). <p>Differential gene expression identifies KRT7 and MUC1 as potential metastasis-specific targets in sarcoma</p>. Cancer Management and Research. Volume 11. 8209–8218. 6 indexed citations
4.
Kratz, Johannes R., Nancy R. Cook, Jianxing He, et al.. (2019). Incorporation of a Molecular Prognostic Classifier Improves Conventional Non–Small Cell Lung Cancer Staging. Journal of Thoracic Oncology. 14(7). 1223–1232. 21 indexed citations
5.
Mann, Michael J., Peter M. Vallone, Erica L. Romsos, et al.. (2016). Developmental validation of the DNAscan™ Rapid DNA Analysis™ instrument and expert system for reference sample processing. Forensic Science International Genetics. 25. 145–156. 29 indexed citations
6.
Yeh, Che‐Chung, Deepak Malhotra, Yi‐Lin Yang, et al.. (2012). MEK1‐induced physiological hypertrophy inhibits chronic post‐myocardial infarction remodeling in mice. Journal of Cellular Biochemistry. 114(1). 47–55. 9 indexed citations
7.
Yeh, Che‐Chung, Hongzhe Li, Deepak Malhotra, et al.. (2010). Distinctive ERK and p38 signaling in remote and infarcted myocardium during post‐MI remodeling in the mouse. Journal of Cellular Biochemistry. 109(6). 1185–1191. 40 indexed citations
8.
Yeh, Che‐Chung, et al.. (2009). Surgical ventricular reconstruction in mice: Elucidating potential targets for combined molecular/surgical intervention. Journal of Thoracic and Cardiovascular Surgery. 137(4). 942–949. 3 indexed citations
9.
Mahimkar, Rajeev, Michael J. Mann, Che‐Chung Yeh, et al.. (2008). Cardiac transgenic matrix metalloproteinase-2 expression induces myxomatous valve degeneration: a potential model of mitral valve prolapse disease. Cardiovascular Pathology. 18(5). 253–261. 31 indexed citations
10.
Ratcliffe, Mark B., et al.. (2008). National Institutes of Health funding for cardiothoracic surgical research. Journal of Thoracic and Cardiovascular Surgery. 136(2). 392–397. 35 indexed citations
11.
Yeh, Che‐Chung, Bo‐Qing Zhu, Richard Tu, et al.. (2006). Abstract 792: Reduced Myocardial S1P Signaling Post-MI: Novel Target for Molecular Intervention. Circulation. 114. 1 indexed citations
12.
Mann, Michael J., et al.. (2005). Urbanization and governance in India. 20 indexed citations
13.
Dolan, James P., et al.. (2005). Thyrotoxicosis after Gastric Bypass Surgery Prompting Operative Re-exploration. Obesity Surgery. 15(6). 883–885. 3 indexed citations
14.
Stratmann, Greg, Elaine Tseng, Julie Hambleton, et al.. (2004). Reversal of Direct Thrombin Inhibition After Cardiopulmonary Bypass in a Patient with Heparin-Induced Thrombocytopenia. Anesthesia & Analgesia. 98(6). 1635–1639. 57 indexed citations
15.
Mann, Michael J. & Victor J. Dzau. (2002). Molecular approaches for the treatment of atherosclerosis. Cardiology Clinics. 20(4). 633–643. 5 indexed citations
16.
Leyen, Heiko E. von der, et al.. (1999). A Pressure-Mediated Nonviral Method for Efficient Arterial Gene and Oligonucleotide Transfer. Human Gene Therapy. 10(14). 2355–2364. 23 indexed citations
17.
18.
Mann, Michael J., Jeffrey J. Martin, Sharon C. Reimold, et al.. (1998). Complete reversal of ischemic wall motion abnormalities by combined use of gene therapy with transmyocardial laser revascularization. Journal of Thoracic and Cardiovascular Surgery. 116(5). 763–769. 50 indexed citations
19.
Mann, Michael J. & Victor J. Dzau. (1997). Genetic manipulation of vein grafts. Current Opinion in Cardiology. 12(6). 522–527. 9 indexed citations
20.
Tatemoto, Kazuhiko, Itsuro Nakano, George Makk, et al.. (1988). Isolation and primary structure of human peptide YY. Biochemical and Biophysical Research Communications. 157(2). 713–717. 30 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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