Jill Angelosanto

6.7k total citations · 3 hit papers
16 papers, 5.0k citations indexed

About

Jill Angelosanto is a scholar working on Immunology, Molecular Biology and Oncology. According to data from OpenAlex, Jill Angelosanto has authored 16 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Immunology, 4 papers in Molecular Biology and 4 papers in Oncology. Recurrent topics in Jill Angelosanto's work include Immune Cell Function and Interaction (11 papers), Immunotherapy and Immune Responses (7 papers) and T-cell and B-cell Immunology (7 papers). Jill Angelosanto is often cited by papers focused on Immune Cell Function and Interaction (11 papers), Immunotherapy and Immune Responses (7 papers) and T-cell and B-cell Immunology (7 papers). Jill Angelosanto collaborates with scholars based in United States, Tunisia and Paraguay. Jill Angelosanto's co-authors include E. John Wherry, Alison Crawford, Travis A. Doering, Carly G.K. Ziegler, David Artis, Laurel A. Monticelli, Gregory F. Sonnenberg, Charlly Kao, Shawn D. Blackburn and Brian J. Laidlaw and has published in prestigious journals such as Nature, Immunity and Nature Immunology.

In The Last Decade

Jill Angelosanto

16 papers receiving 5.0k citations

Hit Papers

Innate lymphoid cells promote lung-tissue homeostasis aft... 2011 2026 2016 2021 2011 2011 2013 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jill Angelosanto United States 15 4.2k 1.6k 944 600 572 16 5.0k
Brian J. Laidlaw United States 25 4.4k 1.1× 1.3k 0.8× 585 0.6× 729 1.2× 626 1.1× 32 5.4k
Anja Fuchs United States 31 5.1k 1.2× 1.4k 0.9× 703 0.7× 867 1.4× 695 1.2× 54 6.7k
Chiara Romagnani Germany 39 4.4k 1.1× 708 0.5× 869 0.9× 566 0.9× 616 1.1× 69 5.3k
Max Löhning Germany 38 5.5k 1.3× 1.1k 0.7× 803 0.9× 1.0k 1.7× 454 0.8× 75 7.1k
Damian Turner United States 15 3.9k 0.9× 1.3k 0.8× 264 0.3× 353 0.6× 814 1.4× 18 4.5k
Taheri Sathaliyawala United States 8 2.9k 0.7× 1.3k 0.8× 229 0.2× 388 0.6× 387 0.7× 8 3.5k
Joseph J.C. Thome United States 15 2.6k 0.6× 531 0.3× 332 0.4× 431 0.7× 723 1.3× 16 3.5k
S. Marieke van Ham Netherlands 37 2.4k 0.6× 535 0.3× 610 0.6× 1.1k 1.8× 618 1.1× 135 4.5k
Ahmed N. Hegazy Germany 22 2.7k 0.6× 600 0.4× 380 0.4× 610 1.0× 291 0.5× 44 3.5k
Spencer C. Liang United States 14 4.4k 1.1× 312 0.2× 1.9k 2.0× 606 1.0× 461 0.8× 23 5.7k

Countries citing papers authored by Jill Angelosanto

Since Specialization
Citations

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

Fields of papers citing papers by Jill Angelosanto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jill Angelosanto

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

All Works

16 of 16 papers shown
1.
Schadler, Keri, Erika J. Crosby, Alice Y. Zhou, et al.. (2014). Immunosurveillance by Antiangiogenesis: Tumor Growth Arrest by T Cell–Derived Thrombospondin-1. Cancer Research. 74(8). 2171–2181. 14 indexed citations
2.
Crawford, Alison, Jill Angelosanto, Charlly Kao, et al.. (2014). Molecular and Transcriptional Basis of CD4+ T Cell Dysfunction during Chronic Infection. Immunity. 40(2). 289–302. 358 indexed citations
3.
Hepworth, Matthew R., Laurel A. Monticelli, Thomas C. Fung, et al.. (2013). Innate lymphoid cells regulate CD4+ T-cell responses to intestinal commensal bacteria. Nature. 498(7452). 113–117. 598 indexed citations breakdown →
4.
Laidlaw, Brian J., Vilma Decman, Mohammed A. Ali, et al.. (2013). Cooperativity Between CD8+ T Cells, Non-Neutralizing Antibodies, and Alveolar Macrophages Is Important for Heterosubtypic Influenza Virus Immunity. PLoS Pathogens. 9(3). e1003207–e1003207. 124 indexed citations
5.
Angelosanto, Jill, Shawn D. Blackburn, Alison Crawford, & E. John Wherry. (2012). Progressive Loss of Memory T Cell Potential and Commitment to Exhaustion during Chronic Viral Infection. Journal of Virology. 86(15). 8161–8170. 217 indexed citations
6.
Doering, Travis A., Alison Crawford, Jill Angelosanto, et al.. (2012). Network Analysis Reveals Centrally Connected Genes and Pathways Involved in CD8+ T Cell Exhaustion versus Memory. Immunity. 37(6). 1130–1144. 383 indexed citations
7.
Monticelli, Laurel A., Gregory F. Sonnenberg, Michael C. Abt, et al.. (2011). Innate lymphoid cells promote lung-tissue homeostasis after infection with influenza virus. Nature Immunology. 12(11). 1045–1054. 1066 indexed citations breakdown →
8.
Kao, Charlly, Kenneth J. Oestreich, Michael Paley, et al.. (2011). Transcription factor T-bet represses expression of the inhibitory receptor PD-1 and sustains virus-specific CD8+ T cell responses during chronic infection. Nature Immunology. 12(7). 663–671. 375 indexed citations
9.
Crawford, Alison, et al.. (2011). A Role for the Chemokine RANTES in Regulating CD8 T Cell Responses during Chronic Viral Infection. PLoS Pathogens. 7(7). e1002098–e1002098. 138 indexed citations
10.
Monticelli, Laurel A., Gregory F. Sonnenberg, Michael C. Abt, et al.. (2011). Innate lymphoid cells promote lung-tissue homeostasis after infection with influenza virus.. Nature Immunology. 12(11). 1045–54. 1125 indexed citations breakdown →
11.
Angelosanto, Jill & E. John Wherry. (2010). Transcription factor regulation of CD8+ T‐cell memory and exhaustion. Immunological Reviews. 236(1). 167–175. 46 indexed citations
12.
Shin, Haina, Shawn D. Blackburn, Andrew M. Intlekofer, et al.. (2009). A Role for the Transcriptional Repressor Blimp-1 in CD8+ T Cell Exhaustion during Chronic Viral Infection. Immunity. 31(2). 309–320. 377 indexed citations
13.
Haining, W. Nicholas, Jeffrey K. Davies, Holger Kanzler, et al.. (2008). CpG Oligodeoxynucleotides Alter Lymphocyte and Dendritic Cell Trafficking in Humans. Clinical Cancer Research. 14(17). 5626–5634. 61 indexed citations
14.
Haining, W. Nicholas, Benjamin L. Ebert, E. John Wherry, et al.. (2008). Identification of an Evolutionarily Conserved Transcriptional Signature of CD8 Memory Differentiation That Is Shared by T and B Cells. The Journal of Immunology. 181(3). 1859–1868. 59 indexed citations
15.
Haining, W. Nicholas, Jill Angelosanto, Kenneth N. Ross, et al.. (2008). High-throughput gene expression profiling of memory differentiation in primary human T cells. BMC Immunology. 9(1). 44–44. 21 indexed citations
16.
Day, Regina M., Abena S. Agyeman, Michael J. Segel, et al.. (2005). Serotonin induces pulmonary artery smooth muscle cell migration. Biochemical Pharmacology. 71(3). 386–397. 37 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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