Victor C. Huber

1.7k total citations
48 papers, 1.4k citations indexed

About

Victor C. Huber is a scholar working on Epidemiology, Immunology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Victor C. Huber has authored 48 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Epidemiology, 20 papers in Immunology and 10 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Victor C. Huber's work include Influenza Virus Research Studies (33 papers), Respiratory viral infections research (24 papers) and Immune Response and Inflammation (11 papers). Victor C. Huber is often cited by papers focused on Influenza Virus Research Studies (33 papers), Respiratory viral infections research (24 papers) and Immune Response and Inflammation (11 papers). Victor C. Huber collaborates with scholars based in United States, Australia and United Kingdom. Victor C. Huber's co-authors include Jonathan A. McCullers, Dennis W. Metzger, Doris J. Bucher, Jianhua Le, Michael S. Chaussee, M.N. Brackin, Rachael Keating, Daniel R. Pérez, Laura A. Miller and Gene H. MacDonald and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Immunology and PLoS ONE.

In The Last Decade

Victor C. Huber

48 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Victor C. Huber United States 19 933 600 302 201 134 48 1.4k
Brad Gilbertson Australia 16 800 0.9× 463 0.8× 300 1.0× 340 1.7× 36 0.3× 30 1.2k
Teena Mohan India 17 361 0.4× 431 0.7× 227 0.8× 321 1.6× 65 0.5× 26 954
Matthew Angel United States 20 930 1.0× 479 0.8× 471 1.6× 300 1.5× 40 0.3× 31 1.4k
Mutsumi Ito Japan 19 911 1.0× 268 0.4× 413 1.4× 191 1.0× 34 0.3× 56 1.2k
Yoichiro Kino Japan 17 479 0.5× 156 0.3× 285 0.9× 115 0.6× 121 0.9× 42 750
Laurel Glaser United States 13 1.3k 1.4× 339 0.6× 497 1.6× 430 2.1× 46 0.3× 44 1.7k
Young‐Tae Lee United States 22 823 0.9× 605 1.0× 378 1.3× 283 1.4× 20 0.1× 54 1.4k
Shigeyuki Itamura Japan 18 857 0.9× 480 0.8× 640 2.1× 215 1.1× 31 0.2× 45 1.4k
Barry Benaissa-Trouw Netherlands 16 280 0.3× 362 0.6× 358 1.2× 378 1.9× 253 1.9× 49 1.2k
Emi Takashita Japan 29 2.4k 2.6× 467 0.8× 777 2.6× 562 2.8× 59 0.4× 76 2.7k

Countries citing papers authored by Victor C. Huber

Since Specialization
Citations

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

Fields of papers citing papers by Victor C. Huber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Victor C. Huber. 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 Victor C. Huber. The network helps show where Victor C. Huber may publish in the future.

Co-authorship network of co-authors of Victor C. Huber

This figure shows the co-authorship network connecting the top 25 collaborators of Victor C. Huber. A scholar is included among the top collaborators of Victor C. Huber 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 Victor C. Huber. Victor C. Huber 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.
Gnimpiéba, Etienne Z., et al.. (2024). Biofilm marker discovery with cloud-based dockerized metagenomics analysis of microbial communities. Briefings in Bioinformatics. 25(Supplement_1). 1 indexed citations
2.
Yuan, Fangfeng, Chi Chen, Victor C. Huber, et al.. (2023). Establish a Pregnant Sow–Neonate Model to Assess Maternal Immunity of a Candidate Influenza Vaccine. Vaccines. 11(3). 646–646. 4 indexed citations
3.
Huber, Victor C., et al.. (2023). Unique SARS-CoV-2 Variants, Tourism Metrics, and B.1.2 Emergence in Early COVID-19 Pandemic: A Correlation Analysis in South Dakota. International Journal of Environmental Research and Public Health. 20(18). 6748–6748. 1 indexed citations
4.
Chatterjee, Archana, Karita Ambrose, David H. Canaday, et al.. (2023). The association between influenza vaccine effectiveness and egg-based manufacturing technology: literature review and US expert consensus. Current Medical Research and Opinion. 40(2). 335–343. 2 indexed citations
5.
Holm, Rochelle H., et al.. (2023). Using wastewater to overcome health disparities among rural residents. Geoforum. 144. 103816–103816. 8 indexed citations
6.
Potts, Rashaun, et al.. (2023). Influenza enhances host susceptibility to non-pulmonary invasive Streptococcus pyogenes infections. Virulence. 14(1). 2265063–2265063. 7 indexed citations
7.
Cassada, David A., et al.. (2022). Population Health Metrics During the Early Stages of the COVID-19 Pandemic: Correlative Pilot Study. JMIR Formative Research. 6(10). e40215–e40215. 2 indexed citations
8.
Zaman, Mehfuz, Victor C. Huber, Victoria Ozberk, et al.. (2021). Combinatorial liposomal peptide vaccine induces IgA and confers protection against influenza virus and bacterial super‐infection. Clinical & Translational Immunology. 10(9). e1337–e1337. 5 indexed citations
9.
Hanson, Mary, James B. Dale, Rodney K. Tweten, et al.. (2020). Immunotherapy targeting the Streptococcus pyogenes M protein or streptolysin O to treat or prevent influenza A superinfection. PLoS ONE. 15(6). e0235139–e0235139. 7 indexed citations
10.
11.
Wang, Yin, Elizabeth Porter, Nanyan Lu, et al.. (2019). Development of a multiplex real-time RT-PCR assay for simultaneous detection and differentiation of influenza A, B, C, and D viruses. Diagnostic Microbiology and Infectious Disease. 95(1). 59–66. 8 indexed citations
12.
13.
Smith, Amber M. & Victor C. Huber. (2017). The Unexpected Impact of Vaccines on Secondary Bacterial Infections Following Influenza. Viral Immunology. 31(2). 159–173. 28 indexed citations
14.
Huber, Victor C., et al.. (2016). The Association between Invasive Group A Streptococcal Diseases and Viral Respiratory Tract Infections. Frontiers in Microbiology. 7. 342–342. 54 indexed citations
15.
Huber, Victor C.. (2013). Influenza vaccines: from whole virus preparations to recombinant protein technology. Expert Review of Vaccines. 13(1). 31–42. 26 indexed citations
16.
McCullers, Jonathan A. & Victor C. Huber. (2012). Correlates of vaccine protection from influenza and its complications. Human Vaccines & Immunotherapeutics. 8(1). 34–44. 50 indexed citations
17.
Huber, Victor C., et al.. (2011). Contribution of murine innate serum inhibitors toward interference within influenza virus immune assays. Influenza and Other Respiratory Viruses. 6(2). 127–135. 14 indexed citations
18.
Huber, Victor C., M.N. Brackin, Laura A. Miller, et al.. (2006). Distinct Contributions of Vaccine-Induced Immunoglobulin G1 (IgG1) and IgG2a Antibodies to Protective Immunity against Influenza. Clinical and Vaccine Immunology. 13(9). 981–990. 258 indexed citations
19.
Huber, Victor C., Tapan Kumar Mondal, Stewart A. Factor, Richard F. Seegal, & David A. Lawrence. (2006). Serum antibodies from Parkinson's disease patients react with neuronal membrane proteins from a mouse dopaminergic cell line and affect its dopamine expression. Journal of Neuroinflammation. 3(1). 1–1. 40 indexed citations
20.
McCullers, Jonathan A., et al.. (2005). A single amino acid change in the C-terminal domain of the matrix protein M1 of influenza B virus confers mouse adaptation and virulence. Virology. 336(2). 318–326. 43 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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