Stephen De Rosa

951 total citations
10 papers, 443 citations indexed

About

Stephen De Rosa is a scholar working on Epidemiology, Molecular Biology and Immunology. According to data from OpenAlex, Stephen De Rosa has authored 10 papers receiving a total of 443 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Epidemiology, 3 papers in Molecular Biology and 3 papers in Immunology. Recurrent topics in Stephen De Rosa's work include Cytomegalovirus and herpesvirus research (3 papers), HIV Research and Treatment (2 papers) and T-cell and B-cell Immunology (2 papers). Stephen De Rosa is often cited by papers focused on Cytomegalovirus and herpesvirus research (3 papers), HIV Research and Treatment (2 papers) and T-cell and B-cell Immunology (2 papers). Stephen De Rosa collaborates with scholars based in United States, South Africa and Japan. Stephen De Rosa's co-authors include Michael T. Anderson, Mario Roederer, Leonard A. Herzenberg, Hajime Nakamura, Junji Yodoi, Arne Holmgren, Leonore A. Herzenberg, Leonore A. Herzenberg, Rachel M. Gerstein and Martin Bigos and has published in prestigious journals such as PLoS ONE, Biometrics and JAIDS Journal of Acquired Immune Deficiency Syndromes.

In The Last Decade

Stephen De Rosa

10 papers receiving 434 citations

Peers

Countries citing papers authored by Stephen De Rosa

Since Specialization

Citations

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

Fields of papers citing papers by Stephen De Rosa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen De Rosa. 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 Stephen De Rosa. The network helps show where Stephen De Rosa may publish in the future.

Co-authorship network of co-authors of Stephen De Rosa

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

All Works

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10 of 10 papers shown

#	Work	Indexed citations
1	Cytomegalovirus (CMV)-Specific Polyfunctional T-Cell Responses after Letermovir (LET) Prophylaxis in Hematopoietic Cell Transplantation (HCT) 2020 ·Biology of Blood and Marrow Transplantation ·Danniel Zamora, (unknown), Hu Xie, (unknown), (unknown), Terry Stevens‐Ayers, Ralf Wagner, Marco Mielcarek, Wendy M. Leisenring, Stephen De Rosa, Michael Boeckh	1
2	Silymarin suppresses basal and stimulus-induced activation, exhaustion, differentiation, and inflammatory markers in primary human immune cells 2017 ·PLoS ONE ·Erica S. Lovelace, Nicholas J. Maurice, Hannah W. Miller, Chloe K. Slichter, Robert Harrington, Amalia Magaret, Martin Prlic, Stephen De Rosa, Stephen J. Polyak	16
3	Changes in Vaginal Microbiota and Immune Mediators in HIV-1-Seronegative Kenyan Women Initiating Depot Medroxyprogesterone Acetate 2015 ·JAIDS Journal of Acquired Immune Deficiency Syndromes ·Alison C. Roxby, David N. Fredricks, Katherine Odem‐Davis, Kristjana Ásbjörnsdóttir, Linnet N. Masese, Tina L. Fiedler, Stephen De Rosa, Walter Jaoko, James Kiarie, Julie Overbaugh, R. Scott McClelland	37
4	Nonlinear Calibration Model Choice between the Four and Five-Parameter Logistic Models 2014 ·Journal of Biopharmaceutical Statistics ·(unknown), Youyi Fong, Xuesong Yu, Olivier Defawe, Nicole Frahm, Stephen De Rosa	25
5	Mixture models for single-cell assays with applications to vaccine studies 2013 ·Biostatistics ·Greg Finak, Andrew McDavid, Pratip K. Chattopadhyay, María Domínguez, Stephen De Rosa, (unknown), Raphaël Gottardo	33
6	Short Communication: T Cell Activation in HIV-1/Herpes Simplex Virus-2-Coinfected Kenyan Women Receiving Valacyclovir 2012 ·AIDS Research and Human Retroviruses ·Alison C. Roxby, Amy Liu, Alison L. Drake, James Kiarie, Barbra A. Richardson, Barbara Lohman‐Payne, Grace John‐Stewart, Anna Wald, Stephen De Rosa, Carey Farquhar	7
7	A Robust Bayesian Random Effects Model for Nonlinear Calibration Problems 2012 ·Biometrics ·Youyi Fong, Jon Wakefield, Stephen De Rosa, Nicole Frahm	18
8	T cell responses generated by HIV vaccines in clinical trials 2008 ·Current Opinion in HIV and AIDS ·Stephen De Rosa, M. Juliana McElrath	11
9	8 Color, 10-parameter flow cytometry to elucidate complex leukocyte heterogeneity 1997 ·Cytometry ·Mario Roederer, Stephen De Rosa, Rachel M. Gerstein, Michael T. Anderson, Martin Bigos, (unknown), (unknown), David R. Parks, Leonore A. Herzenberg, Leonard A. Herzenberg	125
10	Elevation of plasma thioredoxin levels in HIV-infected individuals 1996 ·International Immunology ·Hajime Nakamura, Stephen De Rosa, Mario Roederer, Michael T. Anderson, (unknown), Junji Yodoi, Arne Holmgren, Leonard A. Herzenberg, Leonore A. Herzenberg	170

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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