Travis Sullivan

13.2k total citations
36 papers, 364 citations indexed

About

Travis Sullivan is a scholar working on Surgery, Pulmonary and Respiratory Medicine and Molecular Biology. According to data from OpenAlex, Travis Sullivan has authored 36 papers receiving a total of 364 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Surgery, 14 papers in Pulmonary and Respiratory Medicine and 13 papers in Molecular Biology. Recurrent topics in Travis Sullivan's work include MicroRNA in disease regulation (8 papers), Bladder and Urothelial Cancer Treatments (7 papers) and Renal and related cancers (7 papers). Travis Sullivan is often cited by papers focused on MicroRNA in disease regulation (8 papers), Bladder and Urothelial Cancer Treatments (7 papers) and Renal and related cancers (7 papers). Travis Sullivan collaborates with scholars based in United States, Switzerland and United Kingdom. Travis Sullivan's co-authors include Kimberly Rieger‐Christ, John A. Libertino, Eric Burks, Tanya Logvinenko, Ian C. Summerhayes, David Canes, Niall Harty, Spencer Kozinn, John G. Humphrey and Antonia H. Holway and has published in prestigious journals such as Journal of Clinical Oncology, PLoS ONE and Cancer Research.

In The Last Decade

Travis Sullivan

34 papers receiving 358 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Travis Sullivan United States 10 212 156 98 79 46 36 364
Mierxiati Abudurexiti China 10 156 0.7× 132 0.8× 55 0.6× 116 1.5× 14 0.3× 17 303
Vanessa Henriques Portugal 8 104 0.5× 63 0.4× 197 2.0× 106 1.3× 37 0.8× 18 374
Dawei Tian China 11 178 0.8× 114 0.7× 103 1.1× 64 0.8× 16 0.3× 40 346
Jürgen Beck Germany 8 96 0.5× 68 0.4× 70 0.7× 60 0.8× 13 0.3× 24 279
Shinya Ohara Japan 12 115 0.5× 43 0.3× 135 1.4× 152 1.9× 39 0.8× 29 376
Najla Amira France 6 246 1.2× 68 0.4× 383 3.9× 94 1.2× 36 0.8× 6 532
Alex Freeman United Kingdom 6 105 0.5× 45 0.3× 43 0.4× 48 0.6× 11 0.2× 10 226
Young Joon Byun South Korea 11 139 0.7× 105 0.7× 118 1.2× 129 1.6× 7 0.2× 29 300
Yae‐Eun Suh United Kingdom 9 188 0.9× 139 0.9× 57 0.6× 98 1.2× 4 0.1× 16 389
Mark Laible Germany 10 131 0.6× 101 0.6× 77 0.8× 66 0.8× 6 0.1× 19 302

Countries citing papers authored by Travis Sullivan

Since Specialization
Citations

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

Fields of papers citing papers by Travis Sullivan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Travis Sullivan

This figure shows the co-authorship network connecting the top 25 collaborators of Travis Sullivan. A scholar is included among the top collaborators of Travis Sullivan 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 Travis Sullivan. Travis Sullivan 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.
Burks, Eric, Travis Sullivan, & Kimberly Rieger‐Christ. (2024). Pulmonary adenocarcinoma of low malignant potential defines indolent NSCLC associated with overdiagnosis in the national lung screening trial. Cancer Biomarkers. 42(1). CBM230452–CBM230452.
3.
Sullivan, Travis, Hanqiao Liu, Xiaohui Xiao, et al.. (2023). Abstract 5632: Evaluating a novel molecular biomarker of angioinvasive lung adenocarcinoma with spatial transcriptomics. Cancer Research. 83(7_Supplement). 5632–5632. 1 indexed citations
4.
Sullivan, Travis, et al.. (2023). MicroRNA-155-5p Targets JADE-1, Promoting Proliferation, Migration, and Invasion in Clear Cell Renal Cell Carcinoma Cells. International Journal of Molecular Sciences. 24(9). 7825–7825. 8 indexed citations
5.
Jamil, Marcus, et al.. (2023). Urinary microbiome differences between lichen sclerosus induced and non-lichen sclerosus induced urethral stricture disease. World Journal of Urology. 41(9). 2495–2501. 6 indexed citations
6.
Sullivan, Travis, et al.. (2023). The Roles of miRNAs in Predicting Bladder Cancer Recurrence and Resistance to Treatment. International Journal of Molecular Sciences. 24(2). 964–964. 7 indexed citations
7.
Ma, Lina, Travis Sullivan, Kimberly Rieger‐Christ, et al.. (2023). Vascular invasion predicts the subgroup of lung adenocarcinomas ≤2.0 cm at risk of poor outcome treated by wedge resection compared to lobectomy. JTCVS Open. 16. 938–947. 6 indexed citations
8.
Sullivan, Travis, et al.. (2022). Vascular Invasion Predicts Recurrence in Stage IA2-IB Lung Adenocarcinoma but not Squamous Cell Carcinoma. Clinical Lung Cancer. 24(3). e126–e133. 4 indexed citations
9.
Sullivan, Travis, Kimberly Rieger‐Christ, Elliot L. Servais, et al.. (2022). Vascular invasion identifies the most aggressive histologic subset of stage I lung adenocarcinoma: Implications for adjuvant therapy. Lung Cancer. 171. 82–89. 8 indexed citations
10.
11.
Burks, Eric, Jiarui Zhang, Travis Sullivan, et al.. (2021). Pathologic and gene expression comparison of CT- screen detected and routinely detected stage I/0 lung adenocarcinoma in NCCN risk-matched cohorts.. Cancer Treatment and Research Communications. 29. 100486–100486. 4 indexed citations
12.
Sullivan, Travis, Luke E. Sebel, David Canes, et al.. (2020). MicroRNAs MiR-15a and MiR-26a cooperatively regulate O-GlcNAc-transferase to control proliferation in clear cell renal cell carcinoma. Cancer Biomarkers. 30(3). 343–351. 7 indexed citations
13.
Sullivan, Travis, et al.. (2020). Can genetics help predict efficacy of bariatric surgery? An analysis of microRNA profiles. Surgery for Obesity and Related Diseases. 16(11). 1802–1807. 4 indexed citations
14.
Sullivan, Travis, et al.. (2019). <p>Urinary Microbiome Evaluation in Patients Presenting with Hematuria with a Focus on Exposure to Tobacco Smoke</p>. Research and Reports in Urology. Volume 11. 359–367. 15 indexed citations
15.
Bennett, Jennifer A., Travis Sullivan, Kristian Stensland, et al.. (2019). Protein Expression Profiles among Lichen Sclerosus Urethral Strictures—Can Urethroplasty Success be Predicted?. The Journal of Urology. 203(4). 773–778. 10 indexed citations
16.
17.
Kowalik, Casey G., Travis Sullivan, John M. Dugan, et al.. (2017). Profiling micro RNA from nephrectomy and biopsy specimens: predictors of progression and survival in clear cell renal cell carcinoma. British Journal of Urology. 120(3). 428–440. 28 indexed citations
18.
Sullivan, Travis, et al.. (2017). MP88-15 DISTINCT EXOSOMAL MIRNA PROFILES IN CHEMORESISTANT BLADDER CARCINOMA CELL LINES. The Journal of Urology. 197(4S). 5 indexed citations
19.
Sullivan, Travis, John G. Humphrey, Tanya Logvinenko, et al.. (2015). A non-invasive miRNA based assay to detect bladder cancer in cell-free urine.. PubMed. 7(11). 2500–9. 83 indexed citations
20.
Hall, Janet E., et al.. (1955). Squamous carcinoma arising in previously benign cystic teratoma; report of two cases.. PubMed. 6(1). 93–8. 4 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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