Amy S. Weinmann

6.4k total citations · 1 hit paper
47 papers, 5.0k citations indexed

About

Amy S. Weinmann is a scholar working on Immunology, Molecular Biology and Oncology. According to data from OpenAlex, Amy S. Weinmann has authored 47 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Immunology, 22 papers in Molecular Biology and 9 papers in Oncology. Recurrent topics in Amy S. Weinmann's work include Immune Cell Function and Interaction (27 papers), T-cell and B-cell Immunology (21 papers) and Epigenetics and DNA Methylation (11 papers). Amy S. Weinmann is often cited by papers focused on Immune Cell Function and Interaction (27 papers), T-cell and B-cell Immunology (21 papers) and Epigenetics and DNA Methylation (11 papers). Amy S. Weinmann collaborates with scholars based in United States, Australia and Czechia. Amy S. Weinmann's co-authors include Peggy Farnham, Kenneth J. Oestreich, Sara A. Miller, Pearlly S. Yan, Stephen T. Smale, Danielle A. Chisolm, Jennifer L. Matsuda, Laurent Gapin, Christine A. Biron and Laurie H. Glimcher and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and The Journal of Experimental Medicine.

In The Last Decade

Amy S. Weinmann

46 papers receiving 5.0k citations

Hit Papers

T-bet Regulates the Terminal Maturation and Homeostasis o... 2004 2026 2011 2018 2004 100 200 300 400 500

Peers

Amy S. Weinmann
Roberta Pelanda United States
Susan John United Kingdom
Galen H. Fisher United States
Dragana Cado United States
Zuoming Sun United States
Jillian Nicholl Australia
Katherine A. Forbush United States
Roberta Pelanda United States
Amy S. Weinmann
Citations per year, relative to Amy S. Weinmann Amy S. Weinmann (= 1×) peers Roberta Pelanda

Countries citing papers authored by Amy S. Weinmann

Since Specialization
Citations

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

Fields of papers citing papers by Amy S. Weinmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Amy S. Weinmann. 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 Amy S. Weinmann. The network helps show where Amy S. Weinmann may publish in the future.

Co-authorship network of co-authors of Amy S. Weinmann

This figure shows the co-authorship network connecting the top 25 collaborators of Amy S. Weinmann. A scholar is included among the top collaborators of Amy S. Weinmann 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 Amy S. Weinmann. Amy S. Weinmann 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.
Gilbertson, Sarah & Amy S. Weinmann. (2023). Discovering effector domains in human transcription factors. Trends in Immunology. 44(7). 493–495. 1 indexed citations
2.
Weinmann, Amy S., Ben Youngblood, Stephen T. Smale, et al.. (2020). A Future Outlook on Molecular Mechanisms of Immunity. Trends in Immunology. 41(7). 549–555. 1 indexed citations
3.
Papillion, Amber M., Michael D. Powell, Danielle A. Chisolm, et al.. (2019). Inhibition of IL-2 responsiveness by IL-6 is required for the generation of GC-T FH cells. Science Immunology. 4(39). 93 indexed citations
4.
Yan, Zhaoqi, Luke Parkitny, Sara A. Gibson, et al.. (2019). Deficiency of Socs3 leads to brain-targeted experimental autoimmune encephalomyelitis via enhanced neutrophil activation and ROS production. JCI Insight. 4(9). 40 indexed citations
5.
Chisolm, Danielle A. & Amy S. Weinmann. (2018). Metabolites, genome organization, and cellular differentiation gene programs. Current Opinion in Immunology. 51. 62–67. 8 indexed citations
6.
Botta, Davide, Michael J. Fuller, Tatiana T. Marquez‐Lago, et al.. (2017). Dynamic regulation of T follicular regulatory cell responses by interleukin 2 during influenza infection. Nature Immunology. 18(11). 1249–1260. 183 indexed citations
7.
Hough, Kenneth P., Danielle A. Chisolm, & Amy S. Weinmann. (2015). Transcriptional regulation of T cell metabolism. Molecular Immunology. 68(2). 520–526. 15 indexed citations
8.
Oestreich, Kenneth J., Kaitlin A. Read, Sarah Gilbertson, et al.. (2014). Bcl-6 directly represses the gene program of the glycolysis pathway. Nature Immunology. 15(10). 957–964. 157 indexed citations
9.
Weinmann, Amy S.. (2014). Roles for Helper T Cell Lineage-Specifying Transcription Factors in Cellular Specialization. Advances in immunology. 124. 171–206. 10 indexed citations
10.
Buckingham, Kati J., Margaret J. McMillin, Margaret M. Brassil, et al.. (2013). Multiple mutant T alleles cause haploinsufficiency of Brachyury and short tails in Manx cats. Mammalian Genome. 24(9-10). 400–408. 37 indexed citations
11.
Oestreich, Kenneth J., Albert C. Huang, & Amy S. Weinmann. (2011). The lineage-defining factors T-bet and Bcl-6 collaborate to regulate Th1 gene expression patterns. The Journal of Experimental Medicine. 208(5). 1001–1013. 126 indexed citations
12.
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
13.
Oestreich, Kenneth J. & Amy S. Weinmann. (2011). Encoding Stability Versus Flexibility: Lessons Learned From Examining Epigenetics in T Helper Cell Differentiation. Current topics in microbiology and immunology. 356. 145–164. 14 indexed citations
14.
Miller, Sara A. & Amy S. Weinmann. (2010). Molecular mechanisms by which T‐bet regulates T‐helper cell commitment. Immunological Reviews. 238(1). 233–246. 60 indexed citations
15.
Miller, Sara A., et al.. (2010). Jmjd3 and UTX Play a Demethylase-Independent Role in Chromatin Remodeling to Regulate T-Box Family Member-Dependent Gene Expression. Molecular Cell. 40(4). 594–605. 253 indexed citations
16.
Sekimata, Masayuki, Sara A. Miller, Amy S. Weinmann, et al.. (2009). CCCTC-Binding Factor and the Transcription Factor T-bet Orchestrate T Helper 1 Cell-Specific Structure and Function at the Interferon-γ Locus. Immunity. 31(4). 551–564. 114 indexed citations
17.
Miller, Sara A. & Amy S. Weinmann. (2009). An essential interaction between T-box proteins and histone-modifying enzymes. Epigenetics. 4(2). 85–88. 15 indexed citations
18.
Weinmann, Amy S. & Peggy Farnham. (2002). Identification of unknown target genes of human transcription factors using chromatin immunoprecipitation. Methods. 26(1). 37–47. 292 indexed citations
19.
Weinmann, Amy S., Stephanie M. Bartley, Theresa Zhang, Michael Q. Zhang, & Peggy Farnham. (2001). Use of Chromatin Immunoprecipitation To Clone Novel E2F Target Promoters. Molecular and Cellular Biology. 21(20). 6820–6832. 331 indexed citations
20.
Trinh, Le A., Roger Ferrini, Bradley S. Cobb, et al.. (2001). Down-regulation of TDT transcription in CD4+CD8+thymocytes by Ikaros proteins in direct competition with an Ets activator. Genes & Development. 15(14). 1817–1832. 127 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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