Miguel A. Farroni

528 total citations
10 papers, 446 citations indexed

About

Miguel A. Farroni is a scholar working on Infectious Diseases, Immunology and Epidemiology. According to data from OpenAlex, Miguel A. Farroni has authored 10 papers receiving a total of 446 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Infectious Diseases, 6 papers in Immunology and 5 papers in Epidemiology. Recurrent topics in Miguel A. Farroni's work include Tuberculosis Research and Epidemiology (7 papers), Mycobacterium research and diagnosis (3 papers) and Adrenal Hormones and Disorders (2 papers). Miguel A. Farroni is often cited by papers focused on Tuberculosis Research and Epidemiology (7 papers), Mycobacterium research and diagnosis (3 papers) and Adrenal Hormones and Disorders (2 papers). Miguel A. Farroni collaborates with scholars based in Argentina, United Kingdom and Germany. Miguel A. Farroni's co-authors include Diana Dlugovitzky, Óscar Bottasso, Hugo O. Besedovsky, Adriana del Rey, Marie Lund Bay, María Luisa Bay, John A. Stanford, Cynthia Stanford and Diego J. Martinel Lamas and has published in prestigious journals such as Brain Behavior and Immunity, Clinical & Experimental Immunology and Respiratory Medicine.

In The Last Decade

Miguel A. Farroni

10 papers receiving 439 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Miguel A. Farroni Argentina 8 286 228 185 109 49 10 446
Vânia Niéto Brito de Souza Brazil 12 280 1.0× 241 1.1× 94 0.5× 129 1.2× 14 0.3× 31 432
Caian L. Vinhaes Brazil 13 214 0.7× 199 0.9× 71 0.4× 105 1.0× 14 0.3× 31 414
Mohamed Said Egypt 12 86 0.3× 386 1.7× 39 0.2× 62 0.6× 12 0.2× 51 705
Francisca Portero Spain 9 76 0.3× 286 1.3× 117 0.6× 68 0.6× 39 0.8× 15 491
Najwa El‐Nachef United States 12 160 0.6× 116 0.5× 31 0.2× 88 0.8× 45 0.9× 31 362
Lívia H. Yamashiro Brazil 8 187 0.7× 93 0.4× 229 1.2× 45 0.4× 36 0.7× 8 356
Kiyoshi Shima Japan 9 65 0.2× 65 0.3× 120 0.6× 49 0.4× 36 0.7× 24 277
C. Ruth Butlin United Kingdom 14 464 1.6× 257 1.1× 89 0.5× 225 2.1× 12 0.2× 43 581
Alexandre S. de Almeida Brazil 10 273 1.0× 185 0.8× 124 0.7× 120 1.1× 30 0.6× 14 368
S. Prabhu Anand India 8 118 0.4× 80 0.4× 75 0.4× 32 0.3× 17 0.3× 11 320

Countries citing papers authored by Miguel A. Farroni

Since Specialization
Citations

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

Fields of papers citing papers by Miguel A. Farroni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Miguel A. Farroni. 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 Miguel A. Farroni. The network helps show where Miguel A. Farroni may publish in the future.

Co-authorship network of co-authors of Miguel A. Farroni

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

All Works

10 of 10 papers shown
1.
Dlugovitzky, Diana, et al.. (2010). Immunotherapy with Oral, Heat-Killed, Mycobacterium Vaccae in Patients with Moderate to Advanced Pulmonary Tuberculosis. Immunotherapy. 2(2). 159–169. 18 indexed citations
3.
Farroni, Miguel A., et al.. (2007). Functional Characteristics of Neutrophils and Mononuclear Cells from Tuberculosis Patients Stimulated In vitro with Heat Killed M. tuberculosis. Archives of Medical Research. 38(5). 526–533. 7 indexed citations
4.
Rey, Adriana del, et al.. (2006). Endocrine and cytokine responses in humans with pulmonary tuberculosis. Brain Behavior and Immunity. 21(2). 171–179. 89 indexed citations
5.
Dlugovitzky, Diana, et al.. (2005). Immunological consequences of three doses of heat-killed Mycobacterium vaccae in the immunotherapy of tuberculosis. Respiratory Medicine. 100(6). 1079–1087. 44 indexed citations
6.
Bay, Marie Lund, et al.. (2004). Cortisol and Dehydroepiandrosterone Affect the Response of Peripheral Blood Mononuclear Cells to Mycobacterial Antigens during Tuberculosis. Scandinavian Journal of Immunology. 60(6). 639–646. 40 indexed citations
7.
Farroni, Miguel A., et al.. (2004). TNF-α, TGF-β and NO relationship in sera from tuberculosis (TB) patients of different severity. Immunology Letters. 98(1). 45–48. 48 indexed citations
8.
Bottasso, Óscar, et al.. (2003). Impaired neutrophil function in patients with pulmonary tuberculosis and its normalization in those undergoing specific treatment, except the HIV-coinfected cases. FEMS Immunology & Medical Microbiology. 35(2). 159–164. 11 indexed citations
9.
Dlugovitzky, Diana, et al.. (2000). Influence of disease severity on nitrite and cytokine production by peripheral blood mononuclear cells (PBMC) from patients with pulmonary tuberculosis (TB). Clinical & Experimental Immunology. 122(3). 343–349. 70 indexed citations
10.
Dlugovitzky, Diana, et al.. (1997). Circulating profile of Th1 and Th2 cytokines in tuberculosis patients with different degrees of pulmonary involvement. FEMS Immunology & Medical Microbiology. 18(3). 203–207. 117 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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