Bryan C. Ulrich

1.7k total citations
17 papers, 819 citations indexed

About

Bryan C. Ulrich is a scholar working on Cancer Research, Pulmonary and Respiratory Medicine and Molecular Biology. According to data from OpenAlex, Bryan C. Ulrich has authored 17 papers receiving a total of 819 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Cancer Research, 7 papers in Pulmonary and Respiratory Medicine and 6 papers in Molecular Biology. Recurrent topics in Bryan C. Ulrich's work include Cancer Genomics and Diagnostics (10 papers), Lung Cancer Treatments and Mutations (7 papers) and RNA modifications and cancer (3 papers). Bryan C. Ulrich is often cited by papers focused on Cancer Genomics and Diagnostics (10 papers), Lung Cancer Treatments and Mutations (7 papers) and RNA modifications and cancer (3 papers). Bryan C. Ulrich collaborates with scholars based in United States, France and Japan. Bryan C. Ulrich's co-authors include Cloud P. Paweletz, Nicolas Guibert, Geoffrey R. Oxnard, Yuebi Hu, Julianna Supplee, Nora Feeney, Patrick H. Lizotte, Yanan Kuang, Kwok‐Kin Wong and Mark M. Awad and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Cancer Research and Clinical Cancer Research.

In The Last Decade

Bryan C. Ulrich

17 papers receiving 810 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bryan C. Ulrich United States 11 643 447 309 251 214 17 819
Carmen Say United States 4 734 1.1× 406 0.9× 372 1.2× 471 1.9× 201 0.9× 9 1.0k
Katja Fischereder Austria 9 461 0.7× 350 0.8× 223 0.7× 262 1.0× 115 0.5× 13 695
AmirAli Talasaz United States 11 970 1.5× 682 1.5× 620 2.0× 312 1.2× 380 1.8× 13 1.2k
Nora Feeney United States 8 959 1.5× 1.1k 2.5× 772 2.5× 516 2.1× 245 1.1× 11 1.5k
Elisabetta Campagnoli Italy 10 352 0.5× 446 1.0× 650 2.1× 288 1.1× 66 0.3× 20 952
Dzifa Y. Duose United States 16 239 0.4× 195 0.4× 170 0.6× 261 1.0× 94 0.4× 45 698
Shilpen Patel United States 9 422 0.7× 344 0.8× 989 3.2× 219 0.9× 61 0.3× 20 1.3k
Ryan S. Alden United States 10 1.0k 1.6× 1.2k 2.7× 719 2.3× 457 1.8× 264 1.2× 14 1.5k
Jawad Manekia United States 9 394 0.6× 288 0.6× 186 0.6× 191 0.8× 123 0.6× 10 593
R.E. Kibbelaar Netherlands 6 177 0.3× 412 0.9× 350 1.1× 312 1.2× 96 0.4× 8 740

Countries citing papers authored by Bryan C. Ulrich

Since Specialization
Citations

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

Fields of papers citing papers by Bryan C. Ulrich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bryan C. Ulrich. 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 Bryan C. Ulrich. The network helps show where Bryan C. Ulrich may publish in the future.

Co-authorship network of co-authors of Bryan C. Ulrich

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

All Works

17 of 17 papers shown
1.
Qian, David C., Bryan C. Ulrich, Gang Peng, et al.. (2022). Outcomes Stratification of Head and Neck Cancer Using Pre- and Post-treatment DNA Methylation From Peripheral Blood. International Journal of Radiation Oncology*Biology*Physics. 115(5). 1217–1228. 1 indexed citations
2.
McMahon, James T., et al.. (2022). Circulating Tumor DNA in Adults With Glioma: A Systematic Review and Meta-Analysis of Biomarker Performance. Neurosurgery. 91(2). 231–238. 10 indexed citations
3.
Eldridge, Ronald C., Karan Uppal, D. Neil Hayes, et al.. (2021). Plasma Metabolic Phenotypes of HPV-Associated versus Smoking-Associated Head and Neck Cancer and Patient Survival. Cancer Epidemiology Biomarkers & Prevention. 30(10). 1858–1866. 5 indexed citations
4.
Ulrich, Bryan C., Anne Pradines, Julien Mazières, & Nicolas Guibert. (2021). Detection of Tumor Recurrence via Circulating Tumor DNA Profiling in Patients with Localized Lung Cancer: Clinical Considerations and Challenges. Cancers. 13(15). 3759–3759. 12 indexed citations
5.
Ulrich, Bryan C., Cloud P. Paweletz, Marina S.D. Milan, et al.. (2021). P34.04 Circulating Tumor DNA (ctDNA) as a Marker of Progressive Disease in Patients with Advanced Lung Cancer. Journal of Thoracic Oncology. 16(3). S416–S416. 1 indexed citations
6.
Hu, Chao, Mengxia Yu, Chenying Li, et al.. (2020). miR-550-1 functions as a tumor suppressor in acute myeloid leukemia via the hippo signaling pathway. International Journal of Biological Sciences. 16(15). 2853–2867. 14 indexed citations
7.
Pradines, Anne, Céline Basset, Bryan C. Ulrich, et al.. (2020). Liquid Biopsy of Non-Plasma Body Fluids in Non-Small Cell Lung Cancer: Look Closer to the Tumor!. Cells. 9(11). 2486–2486. 24 indexed citations
8.
Odegaard, Justin I., John J. Vincent, Stefanie Mortimer, et al.. (2018). Validation of a Plasma-Based Comprehensive Cancer Genotyping Assay Utilizing Orthogonal Tissue- and Plasma-Based Methodologies. Clinical Cancer Research. 24(15). 3539–3549. 283 indexed citations
9.
Hu, Yuebi, Bryan C. Ulrich, Julianna Supplee, et al.. (2018). False-Positive Plasma Genotyping Due to Clonal Hematopoiesis. Clinical Cancer Research. 24(18). 4437–4443. 290 indexed citations
10.
Guibert, Nicolas, David H. Hwang, Emily S. Chambers, et al.. (2018). Liquid biopsy of fine-needle aspiration supernatant for lung cancer genotyping. Lung Cancer. 122. 72–75. 43 indexed citations
11.
Uner, Ogul E., Bryan C. Ulrich, & G. Baker Hubbard. (2018). Potential of Aqueous Humor as a Surrogate Tumor Biopsy for Retinoblastoma. JAMA Ophthalmology. 136(5). 597–597. 3 indexed citations
12.
Hu, Yuebi, Ryan S. Alden, Justin I. Odegaard, et al.. (2017). Discrimination of Germline EGFR T790M Mutations in Plasma Cell-Free DNA Allows Study of Prevalence Across 31,414 Cancer Patients. Clinical Cancer Research. 23(23). 7351–7359. 63 indexed citations
13.
Ulrich, Bryan C., Rebecca J. Nagy, Justin I. Odegaard, et al.. (2017). Abstract 5692: Cross-platform detection and quantification of actionable mutations in cell-free DNA shows high concordance and correlation between next-generation sequencing and droplet digital PCR. Cancer Research. 77(13_Supplement). 5692–5692. 3 indexed citations
14.
Ulrich, Bryan C. & Cloud P. Paweletz. (2017). Cell-Free DNA in Oncology: Gearing up for Clinic. Annals of Laboratory Medicine. 38(1). 1–8. 30 indexed citations
15.
Kun, Ernest, Brigitte Langer, Bryan C. Ulrich, Helmut Holzer, & H. Grunicke. (1964). THE ROLE OF DPN ase IN THE MECHANISM OF ACTION OF AN ANTITUMOR ALKYLATING AGENT ON EHRLICH ASCITES CELLS. Proceedings of the National Academy of Sciences. 52(6). 1501–1506. 17 indexed citations
16.
Kroeger, Heinrich, et al.. (1960). [On the influence of carcinostatic agents on the DPN metabolism of tumors. I. Incorporation of C-14-ribose and C-14-nicotinamide into the DPN of ascites cells].. PubMed. 333. 148–54. 11 indexed citations
17.
Kroeger, Heinrich, et al.. (1960). [On the influence of carcinostatic agents on the DPN metabolism of tumors. II. Detection of DPN constituents in ascites cells].. PubMed. 333. 155–65. 9 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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