Alex Rolfe

2.5k total citations · 1 hit paper
18 papers, 1.8k citations indexed

About

Alex Rolfe is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Alex Rolfe has authored 18 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 7 papers in Oncology and 5 papers in Immunology. Recurrent topics in Alex Rolfe's work include Cancer Immunotherapy and Biomarkers (5 papers), Immune Cell Function and Interaction (3 papers) and Immune cells in cancer (3 papers). Alex Rolfe is often cited by papers focused on Cancer Immunotherapy and Biomarkers (5 papers), Immune Cell Function and Interaction (3 papers) and Immune cells in cancer (3 papers). Alex Rolfe collaborates with scholars based in United States, Germany and Italy. Alex Rolfe's co-authors include Pamela Sklar, Eric S. Lander, Kristin Ardlie, James Nemesh, George Q. Daley, James Ireland, David Altshuler, Nila Patil, Charles R. Lane and Lisa Friedland and has published in prestigious journals such as Nucleic Acids Research, Nature Genetics and SHILAP Revista de lepidopterología.

In The Last Decade

Alex Rolfe

18 papers receiving 1.7k citations

Hit Papers

Characterization of single-nucleotide polymorphisms in co... 1999 2026 2008 2017 1999 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alex Rolfe United States 11 1.1k 536 190 179 113 18 1.8k
Ian J. Purvis United Kingdom 23 1.1k 1.1× 737 1.4× 243 1.3× 307 1.7× 114 1.0× 37 2.1k
Rika Suzuki Japan 18 1.6k 1.5× 696 1.3× 163 0.9× 99 0.6× 141 1.2× 57 2.3k
Ok-Kyong Park-Sarge United States 21 1.3k 1.2× 384 0.7× 203 1.1× 267 1.5× 52 0.5× 28 1.8k
Nobuya Sasaki Japan 22 1.3k 1.2× 583 1.1× 224 1.2× 193 1.1× 174 1.5× 114 2.6k
Marcel van Duin Netherlands 27 1.4k 1.3× 444 0.8× 310 1.6× 152 0.8× 120 1.1× 39 3.2k
Manuela Haltmeier Germany 8 1.3k 1.2× 354 0.7× 261 1.4× 198 1.1× 248 2.2× 8 2.0k
Dori C. Woods United States 28 1.3k 1.2× 456 0.9× 231 1.2× 90 0.5× 38 0.3× 63 2.4k
Susannah Varmuza Canada 22 1.7k 1.6× 673 1.3× 325 1.7× 161 0.9× 97 0.9× 49 2.6k
Loan Nguyen United States 26 1.2k 1.1× 543 1.0× 129 0.7× 202 1.1× 177 1.6× 79 2.1k
T. Heinemeyer Germany 4 1.1k 1.0× 308 0.6× 344 1.8× 216 1.2× 83 0.7× 4 1.7k

Countries citing papers authored by Alex Rolfe

Since Specialization
Citations

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

Fields of papers citing papers by Alex Rolfe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alex Rolfe

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

All Works

18 of 18 papers shown
2.
Vugmeyster, Yulia, George Locke, Christoph Helwig, et al.. (2022). Risk assessment of drug–drug interaction potential for bintrafusp alfa with cytochrome P4503A4 substrates: A totality of evidence approach. Clinical and Translational Science. 15(12). 2838–2843. 2 indexed citations
3.
Giovannoni, Gavin, Thomas Leist, Per Soelberg Sørensen, et al.. (2020). Revealing the Immune Cell Subtype Reconstitution Profile in Cladribine Treated Patients at the 96 Week Timepoint (CLARITY) Using Deconvolution Algorithms (1520). Neurology. 94(15_supplement). 1 indexed citations
5.
Strack, Elisabeth, Alex Rolfe, Annika F. Fink, et al.. (2020). Identification of tumor‐associated macrophage subsets that are associated with breast cancer prognosis. SHILAP Revista de lepidopterología. 10(8). e239–e239. 31 indexed citations
6.
Ihling, Christian, Bartholomew J. Naughton, Yue Zhang, et al.. (2019). Observational Study of PD-L1, TGF-β, and Immune Cell Infiltrates in Hepatocellular Carcinoma. Frontiers in Medicine. 6. 15–15. 26 indexed citations
7.
Strauss, Julius, Margaret E. Gatti‐Mays, Sébastien Salas, et al.. (2019). Abstract CT075: Phase I evaluation of M7824, a bifunctional fusion protein targeting TGF-β and PD-L1, in patients with human papillomavirus (HPV)-associated malignancies. Cancer Research. 79(13_Supplement). CT075–CT075. 15 indexed citations
8.
Schröder, Matthias, Christopher Bachran, Alex Rolfe, et al.. (2018). Genetic screen in myeloid cells identifies TNF-α autocrine secretion as a factor increasing MDSC suppressive activity via Nos2 up-regulation. Scientific Reports. 8(1). 13399–13399. 20 indexed citations
9.
Cho, Byoung Chul, Amaury Daste, Alain Ravaud, et al.. (2018). M7824 (MSB0011359C), a bifunctional fusion protein targeting PD-L1 and TGF-β, in patients (pts) with advanced SCCHN: Results from a phase I cohort. Annals of Oncology. 29. viii373–viii373. 6 indexed citations
10.
Xu, Chunxiao, Yanping Zhang, Alex Rolfe, et al.. (2017). Combination Therapy with NHS-muIL12 and Avelumab (anti-PD-L1) Enhances Antitumor Efficacy in Preclinical Cancer Models. Clinical Cancer Research. 23(19). 5869–5880. 58 indexed citations
11.
Koehler, Jeffrey W., Adrienne T. Hall, Alex Rolfe, et al.. (2014). Development and Evaluation of a Panel of Filovirus Sequence Capture Probes for Pathogen Detection by Next-Generation Sequencing. PLoS ONE. 9(9). e107007–e107007. 20 indexed citations
12.
Veenemans, Jacobien, I. T. M. A. Overdevest, Eveline Snelders, et al.. (2014). Next-Generation Sequencing for Typing and Detection of Resistance Genes: Performance of a New Commercial Method during an Outbreak of Extended-Spectrum-Beta-Lactamase-Producing Escherichia coli. Journal of Clinical Microbiology. 52(7). 2454–2460. 35 indexed citations
13.
Arena, Fabio, Alex Rolfe, Graeme Doran, et al.. (2014). Rapid Resistome Fingerprinting and Clonal Lineage Profiling of Carbapenem-Resistant Klebsiella pneumoniae Isolates by Targeted Next-Generation Sequencing. Journal of Clinical Microbiology. 52(3). 987–990. 12 indexed citations
14.
Arbab, Mandana, Shaun Mahony, Joel M. Chick, et al.. (2012). A multi-parametric flow cytometric assay to analyze DNA–protein interactions. Nucleic Acids Research. 41(2). e38–e38. 3 indexed citations
15.
Danford, Timothy, Alex Rolfe, & David K. Gifford. (2007). GSE: A COMPREHENSIVE DATABASE SYSTEM FOR THE REPRESENTATION, RETRIEVAL, AND ANALYSIS OF MICROARRAY DATA. PubMed. 539–550. 9 indexed citations
16.
Qi, Yuan, Alex Rolfe, Kenzie D. MacIsaac, et al.. (2006). High-resolution computational models of genome binding events. Nature Biotechnology. 24(8). 963–970. 62 indexed citations
17.
Robert, François, Dmitry Pokholok, Nancy M. Hannett, et al.. (2004). Global Position and Recruitment of HATs and HDACs in the Yeast Genome. Molecular Cell. 16(2). 199–209. 198 indexed citations
18.
Cargill, Michele, David Altshuler, James Ireland, et al.. (1999). Characterization of single-nucleotide polymorphisms in coding regions of human genes. Nature Genetics. 22(3). 231–238. 1266 indexed citations breakdown →

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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