Deeksha Deep

1.3k total citations · 1 hit paper
9 papers, 713 citations indexed

About

Deeksha Deep is a scholar working on Immunology, Molecular Biology and Infectious Diseases. According to data from OpenAlex, Deeksha Deep has authored 9 papers receiving a total of 713 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Immunology, 4 papers in Molecular Biology and 3 papers in Infectious Diseases. Recurrent topics in Deeksha Deep's work include T-cell and B-cell Immunology (4 papers), Immune Cell Function and Interaction (4 papers) and Biochemical and Structural Characterization (3 papers). Deeksha Deep is often cited by papers focused on T-cell and B-cell Immunology (4 papers), Immune Cell Function and Interaction (4 papers) and Biochemical and Structural Characterization (3 papers). Deeksha Deep collaborates with scholars based in United States, Japan and Portugal. Deeksha Deep's co-authors include Alexander Y. Rudensky, Herman Gudjonson, Dana Pe’er, Christina S. Leslie, Charlotte E. Ariyan, Chrysothemis C. Brown, Alejandra Mendoza, Vincent‐Philippe Lavallée, Linas Mažutis and Yuri Pritykin and has published in prestigious journals such as Cell, Angewandte Chemie International Edition and The Journal of Experimental Medicine.

In The Last Decade

Deeksha Deep

9 papers receiving 707 citations

Hit Papers

Transcriptional Basis of Mouse and Human Dendritic Cell H... 2019 2026 2021 2023 2019 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Deeksha Deep United States 7 464 204 138 72 51 9 713
Vanessa G. Oliveira Portugal 13 913 2.0× 182 0.9× 121 0.9× 43 0.6× 23 0.5× 17 1.1k
Rahul Kushwah Canada 14 443 1.0× 281 1.4× 97 0.7× 51 0.7× 21 0.4× 27 785
Ronald A. Backer Netherlands 13 814 1.8× 221 1.1× 256 1.9× 30 0.4× 25 0.5× 17 1.0k
Keri Csencsits‐Smith United States 17 383 0.8× 135 0.7× 54 0.4× 69 1.0× 17 0.3× 26 686
Masashi Watanabe Japan 20 622 1.3× 195 1.0× 261 1.9× 42 0.6× 12 0.2× 27 900
Shoshana D. Katzman United States 13 398 0.9× 103 0.5× 78 0.6× 21 0.3× 74 1.5× 16 596
Catherine A. Rumbley United States 13 332 0.7× 127 0.6× 88 0.6× 31 0.4× 65 1.3× 17 569
Mohey Eldin El Shikh United States 15 484 1.0× 174 0.9× 117 0.8× 24 0.3× 22 0.4× 24 767
Bijal A. Parikh United States 15 346 0.7× 317 1.6× 74 0.5× 23 0.3× 20 0.4× 48 800
David J. Munster Australia 13 928 2.0× 289 1.4× 174 1.3× 46 0.6× 55 1.1× 30 1.2k

Countries citing papers authored by Deeksha Deep

Since Specialization
Citations

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

Fields of papers citing papers by Deeksha Deep

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Deeksha Deep

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

All Works

9 of 9 papers shown
1.
Deep, Deeksha, Herman Gudjonson, Chrysothemis C. Brown, et al.. (2024). Precursor central memory versus effector cell fate and naïve CD4+ T cell heterogeneity. The Journal of Experimental Medicine. 221(10). 3 indexed citations
2.
Wong, Harikesh S., Anita Gola, António P. Baptista, et al.. (2021). A local regulatory T cell feedback circuit maintains immune homeostasis by pruning self-activated T cells. Cell. 184(15). 3981–3997.e22. 90 indexed citations
3.
Brown, Chrysothemis C., Herman Gudjonson, Yuri Pritykin, et al.. (2019). Transcriptional Basis of Mouse and Human Dendritic Cell Heterogeneity. Cell. 179(4). 846–863.e24. 374 indexed citations breakdown →
4.
Tietjen, Gregory T., Sarah A. Hosgood, Jiajia Cui, et al.. (2017). Nanoparticle targeting to the endothelium during normothermic machine perfusion of human kidneys. Science Translational Medicine. 9(418). 112 indexed citations
5.
Kadoki, Motohiko, Ashwini Patil, Donald Brooks, et al.. (2017). Organism-Level Analysis of Vaccination Reveals Networks of Protection across Tissues. Cell. 171(2). 398–413.e21. 63 indexed citations
6.
Kaushal, Himanshu, Rachel Bras‐Gonçalves, Kumar Avishek, et al.. (2016). Evaluation of cellular immunological responses in mono- and polymorphic clinical forms of post-kala-azar dermal leishmaniasis in India. Clinical & Experimental Immunology. 185(1). 50–60. 16 indexed citations
7.
Gautam, Samir, Taehan Kim, Takuji Shoda, et al.. (2015). An Activity‐Based Probe for Studying Crosslinking in Live Bacteria. Angewandte Chemie International Edition. 54(36). 10492–10496. 22 indexed citations
8.
Gautam, Samir, Taehan Kim, Evan Lester, Deeksha Deep, & David A. Spiegel. (2015). Wall teichoic acids prevent antibody binding to epitopes within the cell wall of Staphylococcus aureus. ACS Chemical Biology. 11(1). 25–30. 30 indexed citations
9.
Gautam, Samir, Taehan Kim, Takuji Shoda, et al.. (2015). An Activity‐Based Probe for Studying Crosslinking in Live Bacteria. Angewandte Chemie. 127(36). 10638–10642. 3 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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