Benjamin T. Spike

3.9k total citations
44 papers, 2.4k citations indexed

About

Benjamin T. Spike is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Benjamin T. Spike has authored 44 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 24 papers in Oncology and 8 papers in Cancer Research. Recurrent topics in Benjamin T. Spike's work include Cancer Cells and Metastasis (17 papers), Epigenetics and DNA Methylation (9 papers) and Cancer-related Molecular Pathways (8 papers). Benjamin T. Spike is often cited by papers focused on Cancer Cells and Metastasis (17 papers), Epigenetics and DNA Methylation (9 papers) and Cancer-related Molecular Pathways (8 papers). Benjamin T. Spike collaborates with scholars based in United States, Switzerland and Canada. Benjamin T. Spike's co-authors include Geoffrey M. Wahl, Kay F. Macleod, Benjamin Dibling, Luo Wei Rodewald, James R. Knabb, Thomas J. Hope, Paul T. Schumacker, Rudolf Jaenisch, Mirit I. Aladjem and Kristin Tracy and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and The EMBO Journal.

In The Last Decade

Benjamin T. Spike

43 papers receiving 2.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Benjamin T. Spike United States 23 1.6k 1.0k 563 314 236 44 2.4k
Jan J. Molenaar Netherlands 32 1.8k 1.1× 894 0.9× 932 1.7× 172 0.5× 192 0.8× 91 3.2k
Alan H. Shih United States 25 2.7k 1.6× 694 0.7× 618 1.1× 243 0.8× 186 0.8× 37 3.8k
Fabrizio Bianchi Italy 32 1.8k 1.1× 853 0.8× 1.2k 2.1× 268 0.9× 361 1.5× 87 3.1k
Eiji Sugihara Japan 26 1.2k 0.7× 810 0.8× 546 1.0× 135 0.4× 308 1.3× 67 2.3k
Ichiro Onoyama Japan 23 1.8k 1.1× 885 0.9× 329 0.6× 228 0.7× 382 1.6× 58 2.4k
Ellen van Drunen Netherlands 27 2.5k 1.5× 960 1.0× 541 1.0× 189 0.6× 232 1.0× 42 3.7k
Kolja Eppert Canada 16 1.8k 1.1× 841 0.8× 491 0.9× 125 0.4× 227 1.0× 27 3.1k
Venkateshwar A. Reddy United States 17 1.4k 0.8× 807 0.8× 289 0.5× 206 0.7× 227 1.0× 29 2.1k
Iris Moll Germany 19 1.3k 0.8× 881 0.9× 450 0.8× 145 0.5× 150 0.6× 28 2.5k
Kalindi Parmar United States 28 2.1k 1.3× 862 0.9× 586 1.0× 110 0.4× 270 1.1× 60 3.0k

Countries citing papers authored by Benjamin T. Spike

Since Specialization
Citations

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

Fields of papers citing papers by Benjamin T. Spike

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Benjamin T. Spike

This figure shows the co-authorship network connecting the top 25 collaborators of Benjamin T. Spike. A scholar is included among the top collaborators of Benjamin T. Spike 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 Benjamin T. Spike. Benjamin T. Spike 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.
Syage, Amber R., et al.. (2025). OCA-B promotes pathogenic maturation of stem-like CD4+ T cells and autoimmune demyelination. Journal of Clinical Investigation. 135(13).
2.
Freeman, David W., et al.. (2024). Mcam stabilizes a luminal progenitor-like breast cancer cell state via Ck2 control and Src/Akt/Stat3 attenuation. npj Breast Cancer. 10(1). 80–80. 2 indexed citations
3.
Brot, Simone de, Eugenio Zoni, Antonella Brunello, et al.. (2024). CRIPTO’s multifaceted role in driving aggressive prostate cancer unveiled by in vivo, organoid, and patient data. Oncogene. 44(7). 462–475. 3 indexed citations
4.
Butterfield, Andrew, Sandra D. Scherer, Emilio Cortes-Sanchez, et al.. (2022). Multiparametric quantitative phase imaging for real-time, single cell, drug screening in breast cancer. Communications Biology. 5(1). 794–794. 22 indexed citations
5.
Parnell, Timothy J., Alex Jones, Chris Stubben, et al.. (2022). FoxA1 and FoxA2 control growth and cellular identity in NKX2-1-positive lung adenocarcinoma. Developmental Cell. 57(15). 1866–1882.e10. 22 indexed citations
6.
Zewdu, Rediet, Soledad A. Camolotto, Alex Jones, et al.. (2021). An NKX2-1/ERK/WNT feedback loop modulates gastric identity and response to targeted therapy in lung adenocarcinoma. eLife. 10. 11 indexed citations
7.
Heinz, Richard E., et al.. (2020). CRIPTO antagonist ALK4L75A-Fc inhibits breast cancer cell plasticity and adaptation to stress. Breast Cancer Research. 22(1). 125–125. 7 indexed citations
8.
DelGiorno, Kathleen E., Tejia Zhang, Randall P. French, et al.. (2017). Reprogramming pancreatic stellate cells via p53 activation: A putative target for pancreatic cancer therapy. PLoS ONE. 12(12). e0189051–e0189051. 29 indexed citations
9.
Pfefferle, Adam D., et al.. (2015). Luminal progenitor and fetal mammary stem cell expression features predict breast tumor response to neoadjuvant chemotherapy. Breast Cancer Research and Treatment. 149(2). 425–437. 23 indexed citations
10.
Zhu, Genyuan, Miao Wang, Benjamin T. Spike, et al.. (2014). Differential requirement of GRP94 and GRP78 in mammary gland development. Scientific Reports. 4(1). 5390–5390. 9 indexed citations
11.
Spike, Benjamin T., Jonathan A. Kelber, Madhuri Kalathur, et al.. (2014). CRIPTO/GRP78 Signaling Maintains Fetal and Adult Mammary Stem Cells Ex Vivo. Stem Cell Reports. 2(4). 427–439. 50 indexed citations
12.
Spike, Benjamin T., Dannielle D. Engle, Jennifer Lin, et al.. (2012). A Mammary Stem Cell Population Identified and Characterized in Late Embryogenesis Reveals Similarities to Human Breast Cancer. Cell stem cell. 10(2). 183–197. 169 indexed citations
13.
Liu, Huiping, James R. Knabb, Benjamin T. Spike, & Kay F. Macleod. (2009). Elevated Poly-(ADP-Ribose)-Polymerase Activity Sensitizes Retinoblastoma-Deficient Cells to DNA Damage–Induced Necrosis. Molecular Cancer Research. 7(7). 1099–1109. 17 indexed citations
14.
Spike, Benjamin T. & Kay F. Macleod. (2007). Effects of Hypoxia on Heterotypic Macrophage Interactions. Cell Cycle. 6(21). 2620–2624. 7 indexed citations
15.
Spike, Benjamin T., Benjamin Dibling, James Marvin, et al.. (2004). The Rb tumor suppressor is required for stress erythropoiesis. The EMBO Journal. 23(21). 4319–4329. 74 indexed citations
16.
Spike, Benjamin T. & Kay F. Macleod. (2004). The Rb Tumor Suppressor in Stress Responses and Hematopoietic Homeostasis. Cell Cycle. 4(1). 42–45. 19 indexed citations
17.
Liu, Huiping, et al.. (2003). New roles for the RB tumor suppressor protein. Current Opinion in Genetics & Development. 14(1). 55–64. 73 indexed citations
18.
Rowley, Anne H., et al.. (2001). Oligoclonal IgA Response in the Vascular Wall in Acute Kawasaki Disease. The Journal of Immunology. 166(2). 1334–1343. 130 indexed citations
19.
Max, Nicole, et al.. (2001). Nested Quantitative Real Time PCR for Detection of Occult Tumor Cells. Recent results in cancer research. 158. 25–31. 15 indexed citations
20.
Aladjem, Mirit I., Benjamin T. Spike, Luo Wei Rodewald, et al.. (1998). ES cells do not activate p53-dependent stress responses and undergo p53-independent apoptosis in response to DNA damage. Current Biology. 8(3). 145–155. 366 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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