Majid Tebianian

811 total citations
66 papers, 655 citations indexed

About

Majid Tebianian is a scholar working on Epidemiology, Infectious Diseases and Molecular Biology. According to data from OpenAlex, Majid Tebianian has authored 66 papers receiving a total of 655 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Epidemiology, 21 papers in Infectious Diseases and 18 papers in Molecular Biology. Recurrent topics in Majid Tebianian's work include Influenza Virus Research Studies (16 papers), Tuberculosis Research and Epidemiology (9 papers) and Mycobacterium research and diagnosis (8 papers). Majid Tebianian is often cited by papers focused on Influenza Virus Research Studies (16 papers), Tuberculosis Research and Epidemiology (9 papers) and Mycobacterium research and diagnosis (8 papers). Majid Tebianian collaborates with scholars based in Iran, United Arab Emirates and United States. Majid Tebianian's co-authors include Seyyed Mahmoud Ebrahimi, Ali Mohammad Latifi, Mehdi Mahdavi, Nader Mosavari, Arash Memarnejadian, Mahdi Fasihi‐Ramandi, Meghdad Abdollahpour‐Alitappeh, Hassan Nili, Mohammad Nabavi and Delara Babaie and has published in prestigious journals such as SHILAP Revista de lepidopterología, Virology and Vaccine.

In The Last Decade

Majid Tebianian

59 papers receiving 637 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Majid Tebianian Iran 16 276 224 202 162 70 66 655
Teena Mohan India 17 361 1.3× 321 1.4× 431 2.1× 227 1.4× 29 0.4× 26 954
Miroslav Novák United States 16 308 1.1× 161 0.7× 318 1.6× 140 0.9× 23 0.3× 31 780
Yukari Hagiwara Japan 15 363 1.3× 158 0.7× 477 2.4× 192 1.2× 21 0.3× 17 862
Sae‐Hae Kim South Korea 17 111 0.4× 315 1.4× 411 2.0× 290 1.8× 64 0.9× 37 926
Gabriel Kristian Pedersen Denmark 21 415 1.5× 278 1.2× 671 3.3× 304 1.9× 46 0.7× 59 1.2k
Ernesto Galbán Rodríguez Cuba 4 98 0.4× 176 0.8× 238 1.2× 69 0.4× 28 0.4× 6 449
Young‐Tae Lee United States 22 823 3.0× 283 1.3× 605 3.0× 378 2.3× 60 0.9× 54 1.4k
Barry Benaissa-Trouw Netherlands 16 280 1.0× 378 1.7× 362 1.8× 358 2.2× 80 1.1× 49 1.2k
Nicolas Rochereau France 17 183 0.7× 335 1.5× 566 2.8× 241 1.5× 33 0.5× 30 1.1k
Ricardo Mondragón‐Flores Mexico 16 283 1.0× 282 1.3× 302 1.5× 272 1.7× 45 0.6× 47 937

Countries citing papers authored by Majid Tebianian

Since Specialization
Citations

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

Fields of papers citing papers by Majid Tebianian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Majid Tebianian

This figure shows the co-authorship network connecting the top 25 collaborators of Majid Tebianian. A scholar is included among the top collaborators of Majid Tebianian 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 Majid Tebianian. Majid Tebianian 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.
Tebianian, Majid, et al.. (2023). The neuroprotective effect of betanin nanoparticles on brain ischemia–reperfusion injury. 27. 200145–200145. 3 indexed citations
2.
Shahsavandi, Shahla, Mohammad Majid Ebrahimi, Fatemeh Fotouhi, & Majid Tebianian. (2022). A Combination of Recombinant HA1-and Nucleoprotein-Based Chitosan Nanoparticles Induces Early and Potent Immune Responses Against the H9N2 Influenza Virus. Viral Immunology. 35(5). 365–374. 3 indexed citations
3.
Kargar, Mohammad, et al.. (2022). Designing of novel chimeric PvpA-pMGA protein of Mycoplasma gallisepticum, applicable for indirect ELISA. Journal of Genetic Engineering and Biotechnology. 20(1). 160–160. 1 indexed citations
4.
Shahsavandi, Shahla, et al.. (2022). Modulation of Immune Responses against HA1 Influenza Vaccine Candidate by B-lymphocyte Stimulator Cytokine in Mice. Iranian Journal of Allergy Asthma and Immunology. 21(2). 207–214. 1 indexed citations
5.
Alamian, Saeed, et al.. (2021). Brucella species circulating in rural and periurban dairy cattle farms: a comparative study in an endemic area. Tropical Animal Health and Production. 53(2). 200–200. 11 indexed citations
6.
7.
Mansouri, Reza, et al.. (2017). Evaluation of three different administration routes (IM, SC and IN) on humoral immune responses against Mycobacterium Tuberculosis ESAT-6/CFP-10 fusion protein. SHILAP Revista de lepidopterología.
8.
Tebianian, Majid, et al.. (2017). In Silico Analysis of L1/L2 Sequences of Human Papillomaviruses: Implication for Universal Vaccine Design. Viral Immunology. 30(3). 210–223. 12 indexed citations
9.
Tebianian, Majid, et al.. (2016). Evaluation of specific antibodies against Mycobacterium tuberculosis recombinant antigens for detection of recent infection. International Journal of Mycobacteriology. 5. S254–S254. 3 indexed citations
10.
Pirsaraei, Zarbakht Ansari, et al.. (2016). Determination of the Best Dietary Level of L-Arginine on Improving Growth Performance, Carcass Traits and Blood Parameters in Broiler Chickens in the Starter and Grower Periods. 6(12). 87–95. 1 indexed citations
11.
Tebianian, Majid, et al.. (2016). Evaluation of specific antibodies against Mycobacterium tuberculosis recombinant antigens for detection of recent infection. SHILAP Revista de lepidopterología.
12.
13.
Arshi, Saba, Delara Babaie, Mohammad Nabavi, et al.. (2014). Circulating level of CD4+ CD25+ FOXP3+ T cells in patients with chronic urticaria. International Journal of Dermatology. 53(12). e561–6. 36 indexed citations
14.
Ebrahimi, Seyyed Mahmoud, et al.. (2013). Use of N-trimethyl chitosan for intranasal delivery of DNA encoding M2e-HSP70c in mice. Iranian Journal of Veterinary Medicine. 7(2). 123–128. 1 indexed citations
15.
Tebianian, Majid, et al.. (2011). Analyzing Bacterial Agents of Keratoconjunctivitis in Patients Referred to Ophthal- mology Ward of Feiz Hospital in Isfahan. 1(2). 37–42. 3 indexed citations
16.
Ebrahimi, Seyyed Mahmoud & Majid Tebianian. (2010). Influenza A viruses: why focusing on M2e-based universal vaccines. Virus Genes. 42(1). 1–8. 62 indexed citations
17.
Bidhendi, Soheila Moradi, et al.. (2009). Fusion and sequence analysis of the influenza A (H9N2) virus M2e and C-terminal fragment of Mycobacterium tuberculosis HSP70 (H37Rv). SHILAP Revista de lepidopterología. 64(2). 71–76. 4 indexed citations
18.
Khosravi, Alireza, et al.. (2009). Effect of Invasive Aspergillosis Infection on the Immune Responses of Cancer Mice. 11(440). 242–249. 2 indexed citations
19.
Mazer, Bruce, et al.. (2004). Inhibition of IL-13 by Antisense Oligonucleotide Changes Immunoglobulin Isotype Profile in Cultured B-Lymphocytes. 8(4). 185–191. 1 indexed citations
20.
Dascombe, Michael J., et al.. (2004). The Immunomodulatory Effect of Cyclophosphamide on Regulation of T-Cell Subsets and Antigen Presenting Cells.. SHILAP Revista de lepidopterología. 57(57). 75–88.

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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