Gene S. Tan

7.4k citations

61 papers · 5.3k indexed · 1 hit paper · h-index 41

Epidemiology top 0.5%
Immunology top 1%
Infectious Diseases top 1%
Molecular Biology top 10%
Radiology, Nuclear Medicine and Imaging top 1%

Co-authors: Peter Palese Florian Krammer Rong Hai Jeffrey V. Ravetch David J. DiLillo Natalie Pica Irina Margine Thomas M. Moran
Topics: Influenza Virus Research Studies (40 papers)Respiratory viral infections research (25 papers)Immune Cell Function and Interaction (13 papers)
Cited by: Epidemiology Immunology Virology
Journals: Cell Proceedings of the National Academy of Sciences The Lancet
Partner nations: United States Canada Austria

In The Last Decade

Gene S. Tan

61 papers receiving 5.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Broadly neutralizing hemagglutinin stalk–specific antibodies require FcγR interactions for protection against influenza virus in vivo

2014 600 citations Gene S. Tan, Peter Palese et al. profile →

Peers

Countries citing papers authored by Gene S. Tan

Since Specialization

Citations

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

Fields of papers citing papers by Gene S. Tan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gene S. Tan. 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 Gene S. Tan. The network helps show where Gene S. Tan may publish in the future.

Co-authorship network of co-authors of Gene S. Tan

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

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Major alteration of lung microbiome and the host responses in critically ill COVID-19 patients with high viral load 2024 ·Scientific Reports ·Ingrid G. Bustos,(unknown),Harinder Singh,Benjamín L. Sievers,(unknown),Marcelo Freire,Gene S. Tan,Mónica P. Cala,J. Luis Guerrero,Ignacio Martín‐Loeches,Norberto González-Juarbe,Luis Felipe Reyes	1
2	Microbiome disturbance and resilience dynamics of the upper respiratory tract during influenza A virus infection 2020 ·Nature Communications ·Drishti Kaul,Raveen Rathnasinghe,Marcela Ferrés,Gene S. Tan,Aldo Barrera,Brett E Pickett,Barbara A. Methé,Suman R. Das,(unknown),Rebecca Halpin,David E. Wentworth,Mirco Schmolke,Ignacio Mena,Randy A. Albrecht,Indresh Singh,William Nelson,Adolfo Garcı́a-Sastre,Christopher L. Dupont,Rafael Medina	73
3	Collective interactions augment influenza A virus replication in a host-dependent manner 2020 ·Nature Microbiology ·(unknown),Ketaki Ganti,Nathan T. Jacobs,Chung-Young Lee,Silvia Carnaccini,(unknown),(unknown),Brett E Pickett,Gene S. Tan,Lucas M. Ferreri,Daniel R. Pérez,Anice C. Lowen	26
4	Antibodies Elicited by an NS1-Based Vaccine Protect Mice against Zika Virus 2019 ·mBio ·Mark Bailey,Felix Broecker,James Duehr,(unknown),Florian Krammer,Peter Palese,Gene S. Tan	54
5	Innate Immune Response to Influenza Virus at Single-Cell Resolution in Human Epithelial Cells Revealed Paracrine Induction of Interferon Lambda 1 2019 ·Journal of Virology ·Irene Ramos,Gregory R. Smith,Frederique Ruf-Zamojski,Carles Martínez‐Romero,Miguel Fribourg,(unknown),Boris Hartmann,Venugopalan D. Nair,Nada Marjanović,Paula L. Monteagudo,(unknown),Tinaye Mutetwa,Michel Zamojski,Gene S. Tan,C. Jayaprakash,Elena Zaslavsky,Randy A. Albrecht,Stuart C. Sealfon,Adolfo Garcı́a-Sastre,Ana Fernández-Sesma	67
6	Monoclonal Antibodies with Neutralizing Activity and Fc-Effector Functions against the Machupo Virus Glycoprotein 2019 ·Journal of Virology ·Fatima Amanat,James Duehr,Cheng Huang,Slobodan Paessler,Gene S. Tan,Florian Krammer	20
7	The L46P Mutant Confers a Novel Allosteric Mechanism of Resistance Toward the Influenza A Virus M2 S31N Proton Channel Blockers 2019 ·Molecular Pharmacology ·Rami Musharrafieh,Panagiotis Lagarias,Chunlong Ma,Gene S. Tan,Antonios Kolocouris,Jun Wang	13
8	Human antibodies targeting Zika virus NS1 provide protection against disease in a mouse model 2018 ·Nature Communications ·Mark Bailey,James Duehr,(unknown),Felix Broecker,Julia A. Brown,(unknown),(unknown),Victor H. Leyva-Grado,Matthew J. Evans,Viviana Simon,Jean K. Lim,Florian Krammer,Rong Hai,Peter Palese,Gene S. Tan	79
9	Synthetic Toll-Like Receptor 4 (TLR4) and TLR7 Ligands Work Additively via MyD88 To Induce Protective Antiviral Immunity in Mice 2017 ·Journal of Virology ·Peter H. Goff,Tomoko Hayashi,Wenqian He,Shiyin Yao,Howard B. Cottam,Gene S. Tan,Brian Crain,Florian Krammer,Karen Messer,Minya Pu,Dennis A. Carson,Peter Palese,Maripat Corr	28
10	Alveolar macrophages are critical for broadly-reactive antibody-mediated protection against influenza A virus in mice 2017 ·Nature Communications ·Wenqian He,Chi-Jene Chen,Caitlin E. Mullarkey,Jennifer Hamilton,Christine Wong,Paul E. Leon,Melissa B. Uccellini,Veronika Chromikova,Carole Henry,Kevin W. Hoffman,Jean K. Lim,Patrick C. Wilson,Matthew S. Miller,Florian Krammer,Peter Palese,Gene S. Tan	125
11	Broadly protective murine monoclonal antibodies against influenza B virus target highly conserved neuraminidase epitopes 2017 ·Nature Microbiology ·Teddy John Wohlbold,Kira A. Podolsky,Veronika Chromikova,Ericka Kirkpatrick,V. Falconieri,Philip Meade,Fatima Amanat,Jessica Tan,Benjamin R. tenOever,Gene S. Tan,Sriram Subramaniam,Peter Palese,Florian Krammer	99
12	Generation of Escape Variants of Neutralizing Influenza Virus Monoclonal Antibodies 2017 ·Journal of Visualized Experiments ·Paul E. Leon,Teddy John Wohlbold,Wenqian He,Mark Bailey,Carole Henry,Patrick C. Wilson,Florian Krammer,Gene S. Tan	7
13	Both Neutralizing and Non-Neutralizing Human H7N9 Influenza Vaccine-Induced Monoclonal Antibodies Confer Protection 2016 ·Cell Host & Microbe ·Carole J. Henry Dunand,Paul E. Leon,Min Huang,Angela Choi,Veronika Chromikova,(unknown),Gene S. Tan,John Cruz,Ariana Hirsh,Nai‐Ying Zheng,Caitlin E. Mullarkey,Francis A. Ennis,Masanori Terajima,John J. Treanor,David J. Topham,Kanta Subbarao,Peter Palese,Florian Krammer,Patrick C. Wilson	209
14	Anti-HA Glycoforms Drive B Cell Affinity Selection and Determine Influenza Vaccine Efficacy 2015 ·Cell ·(unknown),Jad Maamary,Gene S. Tan,Stylianos Bournazos,Carl W. Davis,Florian Krammer,Sarah J. Schlesinger,Peter Palese,Rafi Ahmed,Jeffrey V. Ravetch	154
15	Vaccination with soluble headless hemagglutinin protects mice from challenge with divergent influenza viruses 2015 ·Vaccine ·Teddy John Wohlbold,Raffael Nachbagauer,Irina Margine,Gene S. Tan,Ariana Hirsh,Florian Krammer	71
16	Broadly Protective Monoclonal Antibodies against H3 Influenza Viruses following Sequential Immunization with Different Hemagglutinins 2010 ·PLoS Pathogens ·Taia T. Wang,Gene S. Tan,Rong Hai,Natalie Pica,(unknown),Thomas M. Moran,Peter Palese	245
17	Replication‐Deficient Rabies Virus–Based Vaccines Are Safe and Immunogenic in Mice and Nonhuman Primates 2009 ·The Journal of Infectious Diseases ·Jonathan Cenna,Meredith Hunter,Gene S. Tan,Amy B. Papaneri,Erin P. Ribka,Matthias J. Schnell,Preston A. Marx,James P. McGettigan	40
18	Intravenous Inoculation of a Bat-Associated Rabies Virus Causes Lethal Encephalopathy in Mice through Invasion of the Brain via Neurosecretory Hypothalamic Fibers 2009 ·PLoS Pathogens ·(unknown),Marie-Luise Faber,Gene S. Tan,Michael Bette,Bernhard Dietzschold,Eberhard Weihe,Matthias J. Schnell	31
19	The dynein light chain 8 binding motif of rabies virus phosphoprotein promotes efficient viral transcription 2007 ·Proceedings of the National Academy of Sciences ·Gene S. Tan,(unknown),John C. Williams,Matthias J. Schnell	101
20	The application of reverse genetics technology in the study of rabies virus (RV) pathogenesis and for the development of novel RV vaccines 2005 ·Journal of NeuroVirology ·Matthias J. Schnell,Gene S. Tan,(unknown)	34

About Gene S. Tan

Gene S. Tan is a scholar working on Virology, Epidemiology and Immunology, having authored 61 papers that have together received 5.3k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (40 papers), Respiratory viral infections research (25 papers) and Immune Cell Function and Interaction (13 papers). The work is most often cited by research in Epidemiology (3.9k citations), Immunology (2.1k citations) and Virology (425 citations). Gene S. Tan has collaborated with scholars based in United States, Canada and Austria. Frequent co-authors include Peter Palese, Florian Krammer, Rong Hai, Jeffrey V. Ravetch, David J. DiLillo, Natalie Pica, Irina Margine, Thomas M. Moran, Matthias J. Schnell and Taia T. Wang. Their work appears in journals such as Cell, Proceedings of the National Academy of Sciences and The Lancet.

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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