Jeffrey E. Segall

18.1k total citations · 6 hit papers
144 papers, 14.3k citations indexed

About

Jeffrey E. Segall is a scholar working on Molecular Biology, Cell Biology and Oncology. According to data from OpenAlex, Jeffrey E. Segall has authored 144 papers receiving a total of 14.3k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Molecular Biology, 63 papers in Cell Biology and 49 papers in Oncology. Recurrent topics in Jeffrey E. Segall's work include Cellular Mechanics and Interactions (56 papers), Cancer Cells and Metastasis (29 papers) and Cell Adhesion Molecules Research (28 papers). Jeffrey E. Segall is often cited by papers focused on Cellular Mechanics and Interactions (56 papers), Cancer Cells and Metastasis (29 papers) and Cell Adhesion Molecules Research (28 papers). Jeffrey E. Segall collaborates with scholars based in United States, United Kingdom and Germany. Jeffrey E. Segall's co-authors include John S. Condeelis, Jeffrey Wyckoff, Howard C. Berg, Erik Sahai, E. Richard Stanley, Sumanta Goswami, Weigang Wang, Yarong Wang, Jeffrey W. Pollard and Stephan Block and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Jeffrey E. Segall

141 papers receiving 14.1k citations

Hit Papers

A Paracrine Loop between Tumor Cells and Macrophages Is R... 2003 2026 2010 2018 2004 2007 2003 2012 2005 250 500 750
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.

  1. A Paracrine Loop between Tumor Cells and Macrophages Is Required for Tumor Cell Migration in Mammary Tumors
    2004 901 citations Jeffrey Wyckoff, Weigang Wang et al. Cancer Research profile →
  2. Direct Visualization of Macrophage-Assisted Tumor Cell Intravasation in Mammary Tumors
    2007 807 citations Jeffrey Wyckoff, Yarong Wang et al. Cancer Research profile →
  3. Intravital imaging of cell movement in tumours
    2003 725 citations John S. Condeelis, Jeffrey E. Segall profile →
  4. Classifying collective cancer cell invasion
    2012 714 citations Joseph Locker, Erik Sahai et al. profile →
  5. Macrophages Promote the Invasion of Breast Carcinoma Cells via a Colony-Stimulating Factor-1/Epidermal Growth Factor Paracrine Loop
    2005 585 citations Sumanta Goswami, Erik Sahai et al. Cancer Research profile →
  6. Molecular mechanisms of invadopodium formation
    2005 549 citations Salvatore J. Coniglio, Jeffrey E. Segall et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jeffrey E. Segall United States 59 6.6k 4.8k 4.7k 2.7k 2.4k 144 14.3k
Patricia J. Keely United States 58 4.5k 0.7× 5.3k 1.1× 4.8k 1.0× 4.0k 1.5× 947 0.4× 102 13.8k
Erik Sahai United Kingdom 71 11.9k 1.8× 9.1k 1.9× 8.7k 1.8× 3.1k 1.2× 4.0k 1.7× 135 24.2k
Frank B. Gertler United States 78 9.8k 1.5× 7.9k 1.7× 2.7k 0.6× 1.7k 0.6× 1.8k 0.7× 163 18.9k
Andrew J. Ewald United States 49 6.9k 1.0× 3.0k 0.6× 4.8k 1.0× 2.2k 0.8× 1.2k 0.5× 109 13.6k
Jacco van Rheenen Netherlands 47 5.1k 0.8× 2.2k 0.5× 3.2k 0.7× 1.6k 0.6× 1.4k 0.6× 120 9.9k
Michiyuki Matsuda Japan 67 11.2k 1.7× 5.2k 1.1× 2.2k 0.5× 911 0.3× 2.7k 1.1× 304 18.1k
Katarina Wolf Netherlands 35 4.4k 0.7× 6.2k 1.3× 3.4k 0.7× 3.2k 1.2× 875 0.4× 48 11.7k
Johanna Ivaska Finland 62 6.9k 1.0× 5.0k 1.1× 2.7k 0.6× 1.2k 0.5× 1.6k 0.7× 150 13.5k
Laura M. Machesky United Kingdom 68 7.9k 1.2× 8.8k 1.9× 1.3k 0.3× 1.0k 0.4× 1.8k 0.7× 199 15.9k
Philippe Chavrier France 65 9.2k 1.4× 8.3k 1.8× 1.6k 0.3× 1.3k 0.5× 2.1k 0.9× 134 16.0k

Countries citing papers authored by Jeffrey E. Segall

Since Specialization
Citations

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

Fields of papers citing papers by Jeffrey E. Segall

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jeffrey E. Segall

This figure shows the co-authorship network connecting the top 25 collaborators of Jeffrey E. Segall. A scholar is included among the top collaborators of Jeffrey E. Segall 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 Jeffrey E. Segall. Jeffrey E. Segall 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.
Hu, Erqiang, J. An, A. Gersten, et al.. (2025). Virusplot: a web server for viral integration analysis and visualization. Frontiers in Oncology. 15. 1539782–1539782.
2.
Kim, Min-Ha, et al.. (2024). Mechanical compression regulates tumor spheroid invasion into a 3D collagen matrix. Physical Biology. 21(3). 36003–36003. 9 indexed citations
3.
Cheung, Brian C. H., Xingyu Chen, Louis Hodgson, et al.. (2024). Identification of CD44 as a key engager to hyaluronic acid-rich extracellular matrices for cell traction force generation and tumor invasion in 3D. Matrix Biology. 135. 1–11. 11 indexed citations
4.
Galbo, Phillip M., Anne Tranberg Madsen, Yang Liu, et al.. (2023). Functional Contribution and Clinical Implication of Cancer-Associated Fibroblasts in Glioblastoma. Clinical Cancer Research. 30(4). 865–876. 40 indexed citations
5.
Li, Daniel, Jeffrey E. Segall, Michael B. Prystowsky, et al.. (2021). Palbociclib Renders Human Papilloma Virus–Negative Head and Neck Squamous Cell Carcinoma Vulnerable to the Senolytic Agent Navitoclax. Molecular Cancer Research. 19(5). 862–873. 22 indexed citations
6.
Suyama, Kimita, Jiahong Yao, Outhiriaradjou Benard, et al.. (2017). An Akt3 Splice Variant Lacking the Serine 472 Phosphorylation Site Promotes Apoptosis and Suppresses Mammary Tumorigenesis. Cancer Research. 78(1). 103–114. 14 indexed citations
7.
Yao, Jiahong, Kimita Suyama, Xia Qian, et al.. (2014). Slug Promotes Survival during Metastasis through Suppression of Puma-Mediated Apoptosis. Cancer Research. 74(14). 3695–3706. 39 indexed citations
8.
Boimel, Pamela, Т. А. Смирнова, Zhen Ni Zhou, et al.. (2012). Contribution of CXCL12 secretion to invasion of breast cancer cells. Breast Cancer Research. 14(1). R23–R23. 95 indexed citations
9.
Goswami, Sumanta, et al.. (2011). Apoptosis Inhibitor ARC Promotes Breast Tumorigenesis, Metastasis, and Chemoresistance. Cancer Research. 71(24). 7705–7715. 52 indexed citations
10.
Flinn, Rory, Antonia Patsialou, Jeffrey Wyckoff, et al.. (2009). Differential Enhancement of Breast Cancer Cell Motility and Metastasis by Helical and Kinase Domain Mutations of Class IA Phosphoinositide 3-Kinase. Cancer Research. 69(23). 8868–8876. 70 indexed citations
11.
Hernandez, Lorena, Т. А. Смирнова, Dmitriy Kedrin, et al.. (2009). The EGF/CSF-1 Paracrine Invasion Loop Can Be Triggered by Heregulin β1 and CXCL12. Cancer Research. 69(7). 3221–3227. 96 indexed citations
12.
Wang, Weigang, Jeffrey Wyckoff, Sumanta Goswami, et al.. (2007). Coordinated Regulation of Pathways for Enhanced Cell Motility and Chemotaxis Is Conserved in Rat and Mouse Mammary Tumors. Cancer Research. 67(8). 3505–3511. 144 indexed citations
13.
Wyckoff, Jeffrey, Yarong Wang, Elaine Y. Lin, et al.. (2007). Direct Visualization of Macrophage-Assisted Tumor Cell Intravasation in Mammary Tumors. Cancer Research. 67(6). 2649–2656. 807 indexed citations breakdown →
14.
Pu, Jin, Colin McCaig, Lin Cao, et al.. (2007). EGF receptor signalling is essential for electric-field-directed migration of breast cancer cells. Journal of Cell Science. 120(19). 3395–3403. 114 indexed citations
15.
Xue, Chengsen, Jeffrey Wyckoff, Fubo Liang, et al.. (2006). Epidermal Growth Factor Receptor Overexpression Results in Increased Tumor Cell Motility In vivo Coordinately with Enhanced Intravasation and Metastasis. Cancer Research. 66(1). 192–197. 157 indexed citations
16.
Martin, Linda K., et al.. (2006). Interventions for pemphigus vulgaris and pemphigus foliaceus (Protocol). 1–7. 2 indexed citations
17.
Xue, Chengsen, Fubo Liang, Radma Mahmood, et al.. (2006). ErbB3-Dependent Motility and Intravasation in Breast Cancer Metastasis. Cancer Research. 66(3). 1418–1426. 84 indexed citations
18.
Goswami, Sumanta, Erik Sahai, Jeffrey Wyckoff, et al.. (2005). Macrophages Promote the Invasion of Breast Carcinoma Cells via a Colony-Stimulating Factor-1/Epidermal Growth Factor Paracrine Loop. Cancer Research. 65(12). 5278–5283. 585 indexed citations breakdown →
19.
Wang, Weigang, Sumanta Goswami, Kyle Lapidus, et al.. (2004). Identification and Testing of a Gene Expression Signature of Invasive Carcinoma Cells within Primary Mammary Tumors. Cancer Research. 64(23). 8585–8594. 367 indexed citations
20.
Wyckoff, Jeffrey, Weigang Wang, Elaine Y. Lin, et al.. (2004). A Paracrine Loop between Tumor Cells and Macrophages Is Required for Tumor Cell Migration in Mammary Tumors. Cancer Research. 64(19). 7022–7029. 901 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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