Guy L. Reed

5.7k total citations
123 papers, 4.4k citations indexed

About

Guy L. Reed is a scholar working on Cardiology and Cardiovascular Medicine, Hematology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Guy L. Reed has authored 123 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Cardiology and Cardiovascular Medicine, 42 papers in Hematology and 37 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Guy L. Reed's work include Protease and Inhibitor Mechanisms (33 papers), Blood properties and coagulation (29 papers) and Blood Coagulation and Thrombosis Mechanisms (26 papers). Guy L. Reed is often cited by papers focused on Protease and Inhibitor Mechanisms (33 papers), Blood properties and coagulation (29 papers) and Blood Coagulation and Thrombosis Mechanisms (26 papers). Guy L. Reed collaborates with scholars based in United States, Bangladesh and China. Guy L. Reed's co-authors include Aiilyan K. Houng, Michael L. Fitzgerald, János Polgár, Inna P. Gladysheva, Gary R. Matsueda, Sarah M. King, Daniel E. Singer, Roman W. DeSanctis, Ernest H. Picard and Ryan D. Sullivan and has published in prestigious journals such as Nature, New England Journal of Medicine and Proceedings of the National Academy of Sciences.

In The Last Decade

Guy L. Reed

122 papers receiving 4.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Guy L. Reed United States 38 1.4k 1.2k 973 930 623 123 4.4k
Yujiro Asada Japan 45 1.8k 1.3× 1.0k 0.9× 1.7k 1.7× 1.1k 1.2× 484 0.8× 296 7.0k
Grzegorz Sawicki Canada 32 1.3k 0.9× 591 0.5× 1.4k 1.4× 347 0.4× 1.4k 2.3× 95 4.2k
Harald Tillmanns Germany 39 1.7k 1.2× 462 0.4× 1.2k 1.3× 560 0.6× 308 0.5× 193 4.7k
Daniel Sedding Germany 36 827 0.6× 416 0.4× 1.9k 2.0× 695 0.7× 702 1.1× 137 4.8k
Akikazu Takada Japan 37 513 0.4× 964 0.8× 926 1.0× 815 0.9× 1.2k 2.0× 263 4.3k
Tobias Goerge Germany 33 495 0.4× 1.5k 1.2× 860 0.9× 505 0.5× 201 0.3× 82 4.2k
Peter Libby United States 22 1.1k 0.8× 609 0.5× 1.2k 1.2× 796 0.9× 1.4k 2.3× 41 5.1k
Hideo Mugishima Japan 38 349 0.3× 752 0.6× 1.6k 1.7× 748 0.8× 454 0.7× 219 5.0k
Michel Neidhart Switzerland 45 950 0.7× 454 0.4× 2.2k 2.2× 469 0.5× 760 1.2× 112 6.5k
Robert L. Medcalf Australia 45 398 0.3× 1.5k 1.3× 2.0k 2.0× 556 0.6× 1.8k 2.8× 169 6.1k

Countries citing papers authored by Guy L. Reed

Since Specialization
Citations

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

Fields of papers citing papers by Guy L. Reed

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guy L. Reed. 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 Guy L. Reed. The network helps show where Guy L. Reed may publish in the future.

Co-authorship network of co-authors of Guy L. Reed

This figure shows the co-authorship network connecting the top 25 collaborators of Guy L. Reed. A scholar is included among the top collaborators of Guy L. Reed 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 Guy L. Reed. Guy L. Reed 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.
Yadav, Sudesh Kumar, et al.. (2025). Recent Pathophysiological Insights Are Advancing the Treatment of Venous Thromboembolism. JACC Basic to Translational Science. 10(5). 689–703. 3 indexed citations
2.
Padwad, Yogendra, et al.. (2024). Targeting Fibrinolytic Inhibition for Venous Thromboembolism Treatment: Overview of an Emerging Therapeutic Approach. Circulation. 150(11). 884–898. 3 indexed citations
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Li, Wenzhu, Chase W. Kessinger, Makoto Orii, et al.. (2021). Time-Restricted Salutary Effects of Blood Flow Restoration on Venous Thrombosis and Vein Wall Injury in Mouse and Human Subjects. Circulation. 143(12). 1224–1238. 23 indexed citations
6.
Agarwal, Manyoo, Neha Jain, Pradeep S. B. Podila, et al.. (2019). Association of history of heart failure with hospital outcomes of hyperglycemic crises: Analysis from a University hospital and national cohort. Journal of Diabetes and its Complications. 34(1). 107466–107466. 6 indexed citations
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Shah, Rahman, H.A. Abdul-Rashid, Inyong Hwang, et al.. (2017). Meta-Analysis of the Relative Efficacy and Safety of Oral P2Y12 Inhibitors in Patients With Acute Coronary Syndrome. The American Journal of Cardiology. 119(11). 1723–1728. 24 indexed citations
9.
Sullivan, Ryan D., Tai‐Hwang M. Fan, Dong Wang, et al.. (2017). Enhanced heart failure, mortality and renin activation in female mice with experimental dilated cardiomyopathy. PLoS ONE. 12(12). e0189315–e0189315. 22 indexed citations
10.
Yu, Hong, Yue Huang, Yongjun Wang, et al.. (2016). High-sensitivity C-reactive protein in stroke patients – The importance in consideration of influence of multiple factors in the predictability for disease severity and death. Journal of Clinical Neuroscience. 36. 12–19. 36 indexed citations
11.
Ibebuogu, Uzoma N., Oluwaseyi Bolorunduro, Smith Giri, et al.. (2015). Bivalirudin Versus Heparin Plus Glycoprotein IIb/IIIa Inhibitors in Patients with Diabetes Mellitus Undergoing Percutaneous Coronary Intervention: A Meta-Analysis of Randomized Controlled Trials. American Journal of Cardiovascular Drugs. 15(4). 275–285. 7 indexed citations
12.
Stein-Merlob, Ashley, Chase W. Kessinger, S. Sibel Erdem, et al.. (2015). Blood Accessibility to Fibrin in Venous Thrombosis is Thrombus Age-Dependent and Predicts Fibrinolytic Efficacy: An In Vivo Fibrin Molecular Imaging Study. Theranostics. 5(12). 1317–1327. 25 indexed citations
13.
Dias, James K., et al.. (2010). African-American Women Have a Higher Risk for Developing Peripartum Cardiomyopathy. Journal of the American College of Cardiology. 55(7). 654–659. 121 indexed citations
14.
Dodani, Sunita, et al.. (2008). Can dysfunctional HDL explain high coronary artery disease risk in South Asians?. International Journal of Cardiology. 129(1). 125–132. 45 indexed citations
15.
Nahrendorf, Matthias, Kai Hu, Stefan Frantz, et al.. (2006). Factor XIII Deficiency Causes Cardiac Rupture, Impairs Wound Healing, and Aggravates Cardiac Remodeling in Mice With Myocardial Infarction. Circulation. 113(9). 1196–1202. 122 indexed citations
16.
Reed, Guy L.. (2004). Platelet Secretory Mechanisms. Seminars in Thrombosis and Hemostasis. 30(4). 441–450. 101 indexed citations
17.
Tung, Ching‐Hsuan, Nan‐Hui Ho, Qing Zeng, et al.. (2003). Novel Factor XIII Probes for Blood Coagulation Imaging. ChemBioChem. 4(9). 897–899. 58 indexed citations
18.
Houng, Aiilyan K., János Polgár, & Guy L. Reed. (2003). Munc18-Syntaxin Complexes and Exocytosis in Human Platelets. Journal of Biological Chemistry. 278(22). 19627–19633. 37 indexed citations
19.
Fitzgerald, Michael L., Kathryn J. Moore, Mason W. Freeman, & Guy L. Reed. (2000). Lipopolysaccharide Induces Scavenger Receptor A Expression in Mouse Macrophages: A Divergent Response Relative to Human THP-1 Monocyte/Macrophages. The Journal of Immunology. 164(5). 2692–2700. 102 indexed citations
20.

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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