Alberto Molano

1.5k total citations
21 papers, 1.2k citations indexed

About

Alberto Molano is a scholar working on Immunology, Molecular Biology and Epidemiology. According to data from OpenAlex, Alberto Molano has authored 21 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Immunology, 4 papers in Molecular Biology and 4 papers in Epidemiology. Recurrent topics in Alberto Molano's work include Immune Cell Function and Interaction (13 papers), T-cell and B-cell Immunology (10 papers) and Immunotherapy and Immune Responses (4 papers). Alberto Molano is often cited by papers focused on Immune Cell Function and Interaction (13 papers), T-cell and B-cell Immunology (10 papers) and Immunotherapy and Immune Responses (4 papers). Alberto Molano collaborates with scholars based in United States, United Kingdom and France. Alberto Molano's co-authors include Steven A. Porcelli, Petr A. Illarionov, Gurdyal S. Besra, Jin S. Im, Claire Forestier, Young‐Tae Chang, Karl O. A. Yu, Chaim Putterman, Yves Dutronc and Sachiko Miyake and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Experimental Medicine and Immunity.

In The Last Decade

Alberto Molano

21 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alberto Molano United States 16 884 229 178 154 119 21 1.2k
Maureen A. McGargill United States 17 1.1k 1.2× 561 2.4× 206 1.2× 228 1.5× 87 0.7× 36 1.6k
Urban Ramstedt United States 21 732 0.8× 337 1.5× 163 0.9× 149 1.0× 154 1.3× 40 1.4k
César Terrazas United States 23 488 0.6× 178 0.8× 207 1.2× 151 1.0× 107 0.9× 38 1.2k
Warren McComas United States 8 690 0.8× 286 1.2× 123 0.7× 233 1.5× 63 0.5× 11 1.1k
Filippo Volpe United Kingdom 13 542 0.6× 349 1.5× 217 1.2× 82 0.5× 140 1.2× 15 949
Qiulong Huang United States 10 712 0.8× 507 2.2× 249 1.4× 320 2.1× 211 1.8× 13 1.5k
Anthony McMickle United States 11 770 0.9× 232 1.0× 229 1.3× 375 2.4× 58 0.5× 12 1.2k
Hiromi Tanji Japan 15 1.3k 1.5× 537 2.3× 343 1.9× 86 0.6× 122 1.0× 15 1.6k
David D. Duncan United States 17 957 1.1× 384 1.7× 117 0.7× 130 0.8× 81 0.7× 21 1.4k
Aline Blaecke France 9 471 0.5× 237 1.0× 113 0.6× 112 0.7× 51 0.4× 9 822

Countries citing papers authored by Alberto Molano

Since Specialization
Citations

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

Fields of papers citing papers by Alberto Molano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alberto Molano

This figure shows the co-authorship network connecting the top 25 collaborators of Alberto Molano. A scholar is included among the top collaborators of Alberto Molano 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 Alberto Molano. Alberto Molano 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.
Molano, Alberto, Zhaofeng Huang, Melissa Marko, et al.. (2012). Age-Dependent Changes in the Sphingolipid Composition of Mouse CD4+ T Cell Membranes and Immune Synapses Implicate Glucosylceramides in Age-Related T Cell Dysfunction. PLoS ONE. 7(10). e47650–e47650. 23 indexed citations
2.
Molano, Alberto & Simin Nikbin Meydani. (2011). Vitamin E, signalosomes and gene expression in T cells. Molecular Aspects of Medicine. 33(1). 55–62. 21 indexed citations
3.
Molano, Alberto, Zhaofeng Huang, Melissa Marko, et al.. (2011). Age‐dependent changes in the sphingolipid composition of CD4+T cell membranes and immune synapses: impact on T cell proliferation. The FASEB Journal. 25(S1). 1 indexed citations
4.
Im, Jin S., Pooja Arora, Gabriel Bricard, et al.. (2009). Kinetics and Cellular Site of Glycolipid Loading Control the Outcome of Natural Killer T Cell Activation. Immunity. 30(6). 888–898. 138 indexed citations
5.
Molano, Alberto, et al.. (2009). TWEAK stimulation of kidney resident cells in the pathogenesis of graft versus host induced lupus nephritis. Immunology Letters. 125(2). 119–128. 33 indexed citations
6.
Molano, Alberto, et al.. (2008). SYNTHESIS AND in vitro LEISHMANICIDAL AND CYTOTOXIC ACTIVITIES OF 2-STYRYLQUINOLINES ANALOGS. Revista Vitae. 15(2). 259–266. 6 indexed citations
7.
Molano, Alberto, Petr A. Illarionov, Gurdyal S. Besra, Chaim Putterman, & Steven A. Porcelli. (2008). Modulation of invariant natural killer T cell cytokine responses by indoleamine 2,3-dioxygenase. Immunology Letters. 117(1). 81–90. 41 indexed citations
8.
Zhao, Zeguo, Linda C. Burkly, Sean Campbell, et al.. (2007). TWEAK/Fn14 Interactions Are Instrumental in the Pathogenesis of Nephritis in the Chronic Graft-versus-Host Model of Systemic Lupus erythematosus. The Journal of Immunology. 179(11). 7949–7958. 127 indexed citations
9.
Forestier, Claire, Toshiyuki Takaki, Alberto Molano, et al.. (2007). Improved Outcomes in NOD Mice Treated with a Novel Th2 Cytokine-Biasing NKT Cell Activator. The Journal of Immunology. 178(3). 1415–1425. 72 indexed citations
10.
Yu, Karl O. A., Jin S. Im, Alberto Molano, et al.. (2005). Modulation of CD1d-restricted NKT cell responses by using N- acyl variants of α-galactosylceramides. Proceedings of the National Academy of Sciences. 102(9). 3383–3388. 288 indexed citations
11.
Forestier, Claire, Alberto Molano, Jin S. Im, et al.. (2005). Expansion and Hyperactivity of CD1d-Restricted NKT Cells during the Progression of Systemic Lupus Erythematosus in (New Zealand Black × New Zealand White)F1 Mice. The Journal of Immunology. 175(2). 763–770. 48 indexed citations
12.
Dao, Dee N., Laurent Kremer, Yann Guérardel, et al.. (2004). Mycobacterium tuberculosisLipomannan Induces Apoptosis and Interleukin-12 Production in Macrophages. Infection and Immunity. 72(4). 2067–2074. 131 indexed citations
13.
14.
Janković, Vladimir, et al.. (2002). T Cell Recognition of an Engineered MHC Class I Molecule: Implications for Peptide-Independent Alloreactivity. The Journal of Immunology. 169(4). 1887–1892. 12 indexed citations
15.
16.
Molano, Alberto, Hediye Erdjument‐Bromage, Daved H. Fremont, et al.. (1998). Peptide Selection by an MHC H-2Kb Class I Molecule Devoid of the Central Anchor (“C”) Pocket. The Journal of Immunology. 160(6). 2815–2823. 16 indexed citations
17.
Liao, Lujian, Alberto Molano, Cristina Ciurli, et al.. (1996). TCR binding differs for a bacterial superantigen (SEE) and a viral superantigen (Mtv-9).. The Journal of Experimental Medicine. 184(4). 1471–1482. 14 indexed citations
18.
Vasović, Ljiljana V., et al.. (1995). CD4-independent in vivo priming of murine CTL by optimal MHC class I-restricted peptides derived from intracellular pathogens. International Immunology. 7(8). 1205–1212. 37 indexed citations
19.
20.
Calvo, Miguel, et al.. (1992). Specific interactions of synthetic peptides derived from P. falciparum merozoite proteins with human red blood cells.. PubMed. 4(6). 324–33. 19 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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