T. Riley

1.3k total citations
9 papers, 143 citations indexed

About

T. Riley is a scholar working on Surgery, Transplantation and Molecular Biology. According to data from OpenAlex, T. Riley has authored 9 papers receiving a total of 143 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Surgery, 3 papers in Transplantation and 2 papers in Molecular Biology. Recurrent topics in T. Riley's work include Transplantation: Methods and Outcomes (6 papers), Renal Transplantation Outcomes and Treatments (3 papers) and Global Cancer Incidence and Screening (2 papers). T. Riley is often cited by papers focused on Transplantation: Methods and Outcomes (6 papers), Renal Transplantation Outcomes and Treatments (3 papers) and Global Cancer Incidence and Screening (2 papers). T. Riley collaborates with scholars based in United States and Canada. T. Riley's co-authors include Barnett S. Kramer, Robert E. Schoen, Philip C. Prorok, Gerald L. Andriole, Edward P. Gelmann, Mona N. Fouad, Jonathan D. Clapp, Timothy R. Church, Lois Lamerato and David Chia and has published in prestigious journals such as JNCI Journal of the National Cancer Institute, Journal of Dairy Science and The Journal of Heart and Lung Transplantation.

In The Last Decade

T. Riley

7 papers receiving 140 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
T. Riley United States 4 61 55 28 24 21 9 143
Shoni Philpot Australia 8 74 1.2× 42 0.8× 24 0.9× 26 1.1× 16 0.8× 22 160
Nicolas Delanoy France 8 90 1.5× 101 1.8× 27 1.0× 28 1.2× 48 2.3× 32 208
Tatiana Hadjieva Bulgaria 5 47 0.8× 61 1.1× 26 0.9× 18 0.8× 22 1.0× 7 154
R.G.H.M. Cremers Netherlands 8 43 0.7× 142 2.6× 28 1.0× 37 1.5× 15 0.7× 16 222
Hannah Lambie United Kingdom 6 58 1.0× 36 0.7× 32 1.1× 16 0.7× 28 1.3× 9 141
Lionel Uwer France 6 140 2.3× 56 1.0× 29 1.0× 38 1.6× 14 0.7× 14 189
Arnaud Bayle France 8 51 0.8× 64 1.2× 17 0.6× 72 3.0× 15 0.7× 24 165
Carlos Bonilla Colombia 7 78 1.3× 48 0.9× 17 0.6× 11 0.5× 7 0.3× 29 158
Élise Dumas France 7 124 2.0× 36 0.7× 14 0.5× 19 0.8× 11 0.5× 25 195
Martín Lázaro-Quintela Spain 9 89 1.5× 84 1.5× 30 1.1× 22 0.9× 13 0.6× 20 170

Countries citing papers authored by T. Riley

Since Specialization
Citations

This map shows the geographic impact of T. Riley'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 T. Riley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Riley more than expected).

Fields of papers citing papers by T. Riley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of T. Riley

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

All Works

9 of 9 papers shown
1.
Holzhauser, Luise, Teruhiko Imamura, T. Riley, et al.. (2019). Cardiac Allograft Vasculopathy is Linked to Impaired Generation of Regulatory M2 Macrophages. The Journal of Heart and Lung Transplantation. 38(4). S42–S42.
2.
Nitta, Daisuke, Ann Nguyen, J. Raikhelkar, et al.. (2019). Correlation of ImmuKnow Assay Levels with Rejection and Infection after Heart Transplantation. The Journal of Heart and Lung Transplantation. 38(4). S221–S221. 1 indexed citations
3.
Nguyen, Ann, Ben Chung, Teruhiko Imamura, et al.. (2018). Increase in short-term risk of rejection in heart transplant patients receiving granulocyte colony-stimulating factor. The Journal of Heart and Lung Transplantation. 37(11). 1322–1328. 7 indexed citations
4.
Riley, T., Mary M. Reilly, Sara Kalantari, et al.. (2018). Association Between Tacrolimus Concentration/Dose Ratio and Renal Function Following Cardiac Transplant. The Journal of Heart and Lung Transplantation. 37(4). S306–S306.
5.
Holzhauser, Luise, Teruhiko Imamura, Andrew Nguyen, et al.. (2018). Circulating Monocyte Subtypes Correlate with Cardiac Allograft Vasculopathy and Differ from Atherosclerotic Disease: A Tool for Monitoring?. The Journal of Heart and Lung Transplantation. 37(4). S174–S175. 1 indexed citations
6.
Riley, T., et al.. (2015). The Role of Aspirin in the Prevention of Coronary Allograft Vasculopathy in Cardiac Transplant Patients. Journal of Cardiac Failure. 21(8). S111–S112. 3 indexed citations
7.
Tammemägi, Martin C., et al.. (2012). Predictors of Adverse Smoking Outcomes in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. JNCI Journal of the National Cancer Institute. 104(21). 1647–1659. 28 indexed citations
8.
Croswell, Jennifer M., Barnett S. Kramer, Aimée R. Kreimer, et al.. (2009). Cumulative Incidence of False-Positive Results in Repeated, Multimodal Cancer Screening. The Annals of Family Medicine. 7(3). 212–222. 102 indexed citations
9.
Riley, T., et al.. (1990). The effect of gonadotropin-releasing hormone (GnRH) at various injection sites on third service conception rates.. Journal of Dairy Science. 73. 1 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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