М. М. Попов

2.9k total citations · 1 hit paper
14 papers, 1.7k citations indexed

About

М. М. Попов is a scholar working on Immunology, Molecular Biology and Emergency Medical Services. According to data from OpenAlex, М. М. Попов has authored 14 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Immunology, 4 papers in Molecular Biology and 4 papers in Emergency Medical Services. Recurrent topics in М. М. Попов's work include Pediatric health and respiratory diseases (4 papers), Virology and Viral Diseases (3 papers) and T-cell and Retrovirus Studies (2 papers). М. М. Попов is often cited by papers focused on Pediatric health and respiratory diseases (4 papers), Virology and Viral Diseases (3 papers) and T-cell and Retrovirus Studies (2 papers). М. М. Попов collaborates with scholars based in Ukraine, United Kingdom and France. М. М. Попов's co-authors include Jesús Gil, Selina Raguz, Ana O’Loghlen, David Bernard, Eva Hernando, Juan Carlos Acosta, Fabrizio d’Adda di Fagagna, Jonathan Melamed, Marzia Fumagalli and Marco Da Costa and has published in prestigious journals such as Cell, SHILAP Revista de lepidopterología and The EMBO Journal.

In The Last Decade

М. М. Попов

9 papers receiving 1.7k citations

Hit Papers

Chemokine Signaling via the CXCR2 Receptor Reinforces Sen... 2008 2026 2014 2020 2008 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
М. М. Попов Ukraine 4 893 764 510 308 299 14 1.7k
Direna Alonso‐Curbelo United States 14 947 1.1× 594 0.8× 595 1.2× 260 0.8× 540 1.8× 20 1.9k
Janelle Simon United States 11 993 1.1× 457 0.6× 504 1.0× 379 1.2× 727 2.4× 13 2.0k
Roderik M. Kortlever United States 13 1.0k 1.1× 282 0.4× 334 0.7× 388 1.3× 614 2.1× 15 1.6k
Amanda Kulick United States 9 640 0.7× 527 0.7× 491 1.0× 158 0.5× 518 1.7× 13 1.6k
Juling Ji China 14 646 0.7× 241 0.3× 334 0.7× 384 1.2× 225 0.8× 36 1.3k
Jeff S. Pawlikowski United States 12 600 0.7× 419 0.5× 251 0.5× 119 0.4× 204 0.7× 16 1.1k
Samirkumar B. Amin United States 18 1.3k 1.4× 263 0.3× 260 0.5× 686 2.2× 453 1.5× 43 2.3k
Ayako Nakamura‐Ishizu Japan 21 1.0k 1.2× 201 0.3× 538 1.1× 352 1.1× 183 0.6× 43 2.1k
Manuela Sarti Italy 16 893 1.0× 248 0.3× 417 0.8× 289 0.9× 537 1.8× 28 1.7k
Antonio Díez‐Juan Spain 21 1.1k 1.2× 149 0.2× 202 0.4× 567 1.8× 218 0.7× 38 1.9k

Countries citing papers authored by М. М. Попов

Since Specialization
Citations

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

Fields of papers citing papers by М. М. Попов

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of М. М. Попов

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

All Works

14 of 14 papers shown
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Попов, М. М., et al.. (2021). Features of toll-like receptor type 9 expression on immunocompetent peripheral blood cells of patients with measles infection of varying severity. SHILAP Revista de lepidopterología. 66–74. 1 indexed citations
5.
Попов, М. М., et al.. (2021). Cytokine profile of patients with the measles infection of varying severity. SHILAP Revista de lepidopterología. 18(1). 66–71.
6.
Попов, М. М., et al.. (2020). THE NATURE OF A SPECIFIC IMMUNE RESPONSE TO MEASLES INFECTION OF VARYING SEVERITY. SHILAP Revista de lepidopterología. 4(1). 100–100. 1 indexed citations
7.
Попов, М. М., et al.. (2019). FEATURES OF THE COURSE OF CHRONIC EPSTEIN-BARR VIRAL INFECTION. 85(4). 9–13.
8.
Попов, М. М., et al.. (2018). Principles of immunocorrective therapy in children with bronchial asthma. 2018(2). 23–28. 1 indexed citations
9.
Попов, М. М., et al.. (2017). CYTOKINE PRODUCTION PECULIARITIES IN DIFFERENT FORMS OF EPSTEIN-BARR VIRUS INFECTION.. PubMed. 55–59. 2 indexed citations
10.
Попов, М. М., et al.. (2014). POLYOXIDONIUM EFFECT ON IMMUNOREACTIVITY OF PATIENTS WITH CHRONIC STAPHYLOCOCCOSIS PHARYNGITIS. SHILAP Revista de lepidopterología. 1 indexed citations
11.
Martin, Nadine, М. М. Попов, Francesca Aguiló, et al.. (2013). Interplay between Homeobox proteins and Polycomb repressive complexes in p16INK4a regulation. The EMBO Journal. 32(7). 982–995. 30 indexed citations
12.
Smith, Lan‐Lan, Jenny Yeung, Bernd B. Zeisig, et al.. (2011). Functional Crosstalk between Bmi1 and MLL/Hoxa9 Axis in Establishment of Normal Hematopoietic and Leukemic Stem Cells. Cell stem cell. 8(6). 649–662. 89 indexed citations
13.
Попов, М. М. & Jesús Gil. (2010). Epigenetic regulation of theINK4b-ARF-INK4alocus. Epigenetics. 5(8). 685–690. 170 indexed citations
14.
Acosta, Juan Carlos, Ana O’Loghlen, Ana Banito, et al.. (2008). Chemokine Signaling via the CXCR2 Receptor Reinforces Senescence. Cell. 133(6). 1006–1018. 1374 indexed citations breakdown →

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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