William E. Gillanders

14.7k total citations · 1 hit paper
157 papers, 7.0k citations indexed

About

William E. Gillanders is a scholar working on Oncology, Immunology and Cancer Research. According to data from OpenAlex, William E. Gillanders has authored 157 papers receiving a total of 7.0k indexed citations (citations by other indexed papers that have themselves been cited), including 67 papers in Oncology, 58 papers in Immunology and 47 papers in Cancer Research. Recurrent topics in William E. Gillanders's work include Immunotherapy and Immune Responses (52 papers), Breast Cancer Treatment Studies (38 papers) and T-cell and B-cell Immunology (25 papers). William E. Gillanders is often cited by papers focused on Immunotherapy and Immune Responses (52 papers), Breast Cancer Treatment Studies (38 papers) and T-cell and B-cell Immunology (25 papers). William E. Gillanders collaborates with scholars based in United States, Switzerland and Nigeria. William E. Gillanders's co-authors include David J. Cole, Rebecca Aft, Timothy J. Eberlein, Mohamed L. Salem, Peter S. Goedegebuure, Julie A. Margenthaler, Michael Mitas, Kaidi Mikhitarian, Narendra V. Sankpal and Brian A. Belt and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

William E. Gillanders

150 papers receiving 6.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

cDC1 prime and are licensed by CD4+ T cells to induce anti-tumour immunity

2020 356 citations Stephen T. Ferris, Renee Wu et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
William E. Gillanders United States	48	3.5k	2.9k	1.9k	1.6k	815	157	7.0k
Masaki Mandai Japan	49	4.6k 1.3×	3.6k 1.2×	2.9k 1.6×	1.2k 0.8×	676 0.8×	354	10.7k
Michael V. Seiden United States	49	4.1k 1.2×	1.9k 0.7×	3.0k 1.6×	1.5k 0.9×	718 0.9×	172	8.5k
Christian H. Ottensmeier United Kingdom	51	3.6k 1.0×	3.5k 1.2×	2.4k 1.3×	689 0.4×	725 0.9×	223	8.2k
Nicola Silvestris Italy	50	3.7k 1.1×	1.3k 0.5×	2.4k 1.3×	1.6k 1.0×	658 0.8×	319	7.4k
David J. Liewehr United States	50	3.1k 0.9×	1.6k 0.6×	1.9k 1.0×	1.2k 0.7×	882 1.1×	117	7.7k
Holbrook E. Kohrt United States	45	4.3k 1.2×	4.7k 1.6×	1.3k 0.7×	549 0.3×	865 1.1×	147	7.8k
Timothy J. Eberlein United States	47	4.0k 1.1×	3.9k 1.3×	1.3k 0.7×	1.9k 1.2×	1.4k 1.7×	190	8.5k
Martijn P. Lolkema Netherlands	44	4.0k 1.1×	1.8k 0.6×	2.9k 1.5×	2.1k 1.3×	440 0.5×	188	8.2k
Nelson J. Chao United States	54	2.8k 0.8×	3.6k 1.2×	2.1k 1.1×	784 0.5×	824 1.0×	337	11.0k
John T. Vetto United States	39	3.8k 1.1×	2.8k 1.0×	1.2k 0.7×	599 0.4×	547 0.7×	164	6.8k

Countries citing papers authored by William E. Gillanders

Since Specialization

Citations

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

Fields of papers citing papers by William E. Gillanders

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William E. Gillanders. 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 William E. Gillanders. The network helps show where William E. Gillanders may publish in the future.

Co-authorship network of co-authors of William E. Gillanders

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

All Works

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20 of 20 papers shown

Kiwala, Susanna, Zachary L. Skidmore, Jonathan J Song, et al.. (2024). pVACview: an interactive visualization tool for efficient neoantigen prioritization and selection. Genome Medicine. 16(1). 132–132. 1 indexed citations

Ou, Feiya, Stephen T. Ferris, Sun Kyung Kim, et al.. (2023). Enhanced in vitro type 1 conventional dendritic cell generation via the recruitment of hematopoietic stem cells and early progenitors by Kit ligand. European Journal of Immunology. 53(9). e2250201–e2250201. 3 indexed citations

Rice-Boucher, Paul J., Elena A. Kashentseva, Igor P. Dmitriev, et al.. (2023). Engineering a Novel Modular Adenoviral mRNA Delivery Platform Based on Tag/Catcher Bioconjugation. Viruses. 15(11). 2277–2277. 1 indexed citations

Storrs, Erik, Daniel Cui Zhou, Michael C. Wendl, et al.. (2022). Pollock: fishing for cell states. Bioinformatics Advances. 2(1). vbac028–vbac028. 2 indexed citations

Stadler, Guido, Tyler C. Helmann, Xiuli Zhang, et al.. (2022). 184 Discovery, cloning and functional validation of a neoantigen specific patient derived TCR on the berkeley lights platform, with implications in personalized cancer immunotherapy. Regular and Young Investigator Award Abstracts. A196–A196. 2 indexed citations

Ronning, Peter, Darren R. Cullinan, Kelsy C. Cotto, et al.. (2021). In Silico Epitope Prediction Analyses Highlight the Potential for Distracting Antigen Immunodominance with Allogeneic Cancer Vaccines. Cancer Research Communications. 1(2). 115–126. 4 indexed citations

Hundal, Jasreet, Susanna Kiwala, Joshua F. McMichael, et al.. (2020). pVACtools: A Computational Toolkit to Identify and Visualize Cancer Neoantigens. Cancer Immunology Research. 8(3). 409–420. 145 indexed citations

Richters, Megan M., Huiming Xia, Katie M. Campbell, et al.. (2019). Best practices for bioinformatic characterization of neoantigens for clinical utility. Genome Medicine. 11(1). 56–56. 143 indexed citations

Tiriveedhi, Venkataswarup, John M. Herndon, Lijin Li, et al.. (2014). Safety and Preliminary Evidence of Biologic Efficacy of a Mammaglobin-A DNA Vaccine in Patients with Stable Metastatic Breast Cancer. Clinical Cancer Research. 20(23). 5964–5975. 75 indexed citations

10.

Sankpal, Narendra V., Timothy P. Fleming, & William E. Gillanders. (2013). EpCAM Modulates NF-κB Signaling and Interleukin-8 Expression in Breast Cancer. Molecular Cancer Research. 11(4). 418–426. 29 indexed citations

11.

Li, Lijin, Sojung Kim, John M. Herndon, et al.. (2012). Cross-dressed CD8α ⁺ /CD103 ⁺ dendritic cells prime CD8 ⁺ T cells following vaccination. Proceedings of the National Academy of Sciences. 109(31). 12716–12721. 63 indexed citations

12.

Fisher, Carla S., X. Cynthia, William E. Gillanders, et al.. (2011). Neoadjuvant Chemotherapy Is Associated with Improved Survival Compared with Adjuvant Chemotherapy in Patients with Triple-Negative Breast Cancer Only after Complete Pathologic Response. Annals of Surgical Oncology. 19(1). 253–258. 54 indexed citations

13.

Liu, Ying, Maria Pérez, Rebecca Aft, et al.. (2010). Accuracy of Perceived Risk of Recurrence Among Patients With Early-Stage Breast Cancer. Cancer Epidemiology Biomarkers & Prevention. 19(3). 675–680. 41 indexed citations

14.

Pérez, Maria, Ying Liu, Mario Schootman, et al.. (2010). Changes in sexual problems over time in women with and without early-stage breast cancer. Menopause The Journal of The North American Menopause Society. 17(5). 924–937. 31 indexed citations

15.

Watson, Mark A., Lourdes R. Ylagan, Kathryn Trinkaus, et al.. (2007). Isolation and Molecular Profiling of Bone Marrow Micrometastases Identifies TWIST1 as a Marker of Early Tumor Relapse in Breast Cancer Patients. Clinical Cancer Research. 13(17). 5001–5009. 98 indexed citations

16.

Salem, Mohamed L., C. Marcela Díaz‐Montero, Yi‐An Chen, et al.. (2007). The TLR3 agonist poly (I:C) acted directly on mouse CD8 T cells and augmented their antigen-specific responses upon adoptive transfer into naive recipient mice (48.31). The Journal of Immunology. 178(1_Supplement). S80–S81. 1 indexed citations

17.

Salem, Mohamed L., William E. Gillanders, Andre N. Kadima, et al.. (2006). Review: Novel Nonviral Delivery Approaches for Interleukin-12 Protein and Gene Systems: Curbing Toxicity and Enhancing Adjuvant Activity. Journal of Interferon & Cytokine Research. 26(9). 593–608. 47 indexed citations

18.

Mikhitarian, Kaidi, William E. Gillanders, Jonas S. Almeida, et al.. (2005). An Innovative Microarray Strategy Identities Informative Molecular Markers for the Detection of Micrometastatic Breast Cancer. Clinical Cancer Research. 11(10). 3697–3704. 24 indexed citations

19.

Rubinstein, Mark P., Andre N. Kadima, Mohamed L. Salem, et al.. (2003). Transfer of TCR Genes into Mature T Cells Is Accompanied by the Maintenance of Parental T Cell Avidity. The Journal of Immunology. 170(3). 1209–1217. 42 indexed citations

20.

Rubinstein, Mark P., Andre N. Kadima, Mohamed L. Salem, et al.. (2002). Systemic Administration of IL-15 Augments the Antigen-Specific Primary CD8+ T Cell Response Following Vaccination with Peptide-Pulsed Dendritic Cells. The Journal of Immunology. 169(9). 4928–4935. 83 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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