Rosa García

474 total citations
10 papers, 369 citations indexed

About

Rosa García is a scholar working on Immunology, Hematology and Cell Biology. According to data from OpenAlex, Rosa García has authored 10 papers receiving a total of 369 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Immunology, 3 papers in Hematology and 3 papers in Cell Biology. Recurrent topics in Rosa García's work include Multiple Myeloma Research and Treatments (2 papers), T-cell and B-cell Immunology (2 papers) and Immune Cell Function and Interaction (2 papers). Rosa García is often cited by papers focused on Multiple Myeloma Research and Treatments (2 papers), T-cell and B-cell Immunology (2 papers) and Immune Cell Function and Interaction (2 papers). Rosa García collaborates with scholars based in Canada, United States and India. Rosa García's co-authors include Paul G. Smith, Khalid Sendide, Zakaria Hmama, Karen M. Dobos, Amina Talal, Neil E. Reiner, Megan K. Levings, Audrey O’Neill, Jonathan M. Han and Kiran Assi and has published in prestigious journals such as The Journal of Immunology, Journal of the American College of Cardiology and Journal of Cell Science.

In The Last Decade

Rosa García

9 papers receiving 358 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rosa García Canada	7	121	103	96	50	43	10	369
Le Sun China	11	226 1.9×	144 1.4×	143 1.5×	63 1.3×	19 0.4×	23	509
K. Aroni Greece	12	125 1.0×	65 0.6×	64 0.7×	53 1.1×	71 1.7×	45	560
Medhavi Bole United States	4	55 0.5×	111 1.1×	79 0.8×	25 0.5×	14 0.3×	7	305
Sharissa L. Latham Australia	14	336 2.8×	95 0.9×	74 0.8×	56 1.1×	20 0.5×	20	520
Tony Chu United Kingdom	8	171 1.4×	92 0.9×	149 1.6×	64 1.3×	57 1.3×	10	515
Cristina Mazzon Italy	12	183 1.5×	150 1.5×	46 0.5×	45 0.9×	12 0.3×	16	457
John G. Pizzolo United States	11	148 1.2×	65 0.6×	26 0.3×	34 0.7×	50 1.2×	17	482
Nancy Mora Mexico	12	152 1.3×	245 2.4×	40 0.4×	50 1.0×	12 0.3×	18	499
Shaojing Ye United States	14	167 1.4×	172 1.7×	158 1.6×	52 1.0×	9 0.2×	26	682

Countries citing papers authored by Rosa García

Since Specialization

Citations

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

Fields of papers citing papers by Rosa García

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rosa García

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

Rezende, Paulo Cury, Whady Hueb, Mark A. Hlatky, et al.. (2019). VARIABILITY IN GLYCATED HEMOGLOBIN VALUES AND CARDIOVASCULAR EVENTS IN PATIENTS WITH TYPE 2 DIABETES AND MULTIVESSEL CORONARY ARTERY DISEASE. Journal of the American College of Cardiology. 73(9). 108–108.

Lad, Deepesh, Qing Huang, R. Hoeppli, et al.. (2019). Evaluating the role of Tregs in the progression of multiple myeloma. Leukemia & lymphoma. 60(9). 2134–2142. 21 indexed citations

Broady, Raewyn, Jessica Huang, Romy E. Hoeppli, et al.. (2017). Evaluating the Role of Tregs in the Progression of Multiple Myeloma. Clinical Lymphoma Myeloma & Leukemia. 17(1). e42–e43. 6 indexed citations

Patterson, Scott J., Jonathan M. Han, Rosa García, et al.. (2011). Cutting Edge: PHLPP Regulates the Development, Function, and Molecular Signaling Pathways of Regulatory T Cells. The Journal of Immunology. 186(10). 5533–5537. 58 indexed citations

Miller, Christopher C.J., et al.. (2011). Gaseous nitric oxide exhibits minimal effect on skin fibroblast extracellular matrix gene expression and immune cell viability. Cell Biology International. 35(4). 407–415. 19 indexed citations

Patterson, Scott J., Rosa García, Audrey O’Neill, et al.. (2010). PHLPP Regulates the Development, Function and Molecular Signaling Pathways of T Regulatory Cells. Clinical Immunology. 135. S6–S6. 1 indexed citations

Hmama, Zakaria, Khalid Sendide, Amina Talal, et al.. (2004). Quantitative analysis of phagolysosome fusion in intact cells: inhibition by mycobacterial lipoarabinomannan and rescue by an 1α,25-dihydroxyvitamin D3–phosphoinositide 3-kinase pathway. Journal of Cell Science. 117(10). 2131–2140. 123 indexed citations

Subirá, Dolores, et al.. (1998). CD19/CD5 acute lymphoblastic leukemia. Medical and Pediatric Oncology. 31(6). 551–552. 8 indexed citations

Smith, Paul G., et al.. (1998). Mechanical Strain Increases Protein Tyrosine Phosphorylation in Airway Smooth Muscle Cells. Experimental Cell Research. 239(2). 353–360. 52 indexed citations

10.

Smith, Paul G., et al.. (1997). Strain Reorganizes Focal Adhesions and Cytoskeleton in Cultured Airway Smooth Muscle Cells. Experimental Cell Research. 232(1). 127–136. 81 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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