Mariana del Vas

945 total citations · 1 hit paper
33 papers, 686 citations indexed

About

Mariana del Vas is a scholar working on Plant Science, Molecular Biology and Infectious Diseases. According to data from OpenAlex, Mariana del Vas has authored 33 papers receiving a total of 686 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Plant Science, 11 papers in Molecular Biology and 8 papers in Infectious Diseases. Recurrent topics in Mariana del Vas's work include Plant Virus Research Studies (24 papers), Mosquito-borne diseases and control (7 papers) and Viral Infections and Vectors (7 papers). Mariana del Vas is often cited by papers focused on Plant Virus Research Studies (24 papers), Mosquito-borne diseases and control (7 papers) and Viral Infections and Vectors (7 papers). Mariana del Vas collaborates with scholars based in Argentina, Brazil and Belgium. Mariana del Vas's co-authors include Ana J. Distéfano, H. Esteban Hopp, Guillermo A. Maroniche, Vanesa Mongelli, G. Truol, Luis Rogelio Conci, Cecilia Vázquez Rovere, Oscar Taboga, Sara Maldonado and Peter Mertens and has published in prestigious journals such as PLoS ONE, Scientific Reports and Virology.

In The Last Decade

Mariana del Vas

32 papers receiving 668 citations

Hit Papers

ICTV Virus Taxonomy Profi... 2022 2026 2023 2024 2022 25 50 75 100

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mariana del Vas Argentina 15 449 240 169 127 70 33 686
Kunj B. Pathak United States 9 297 0.7× 123 0.5× 84 0.5× 73 0.6× 38 0.5× 9 434
Lucy R. Stewart United States 16 864 1.9× 264 1.1× 87 0.5× 293 2.3× 40 0.6× 49 1.1k
Justine Charon Australia 11 361 0.8× 201 0.8× 76 0.4× 43 0.3× 37 0.5× 18 551
Zsuzsanna Sasvári United States 17 726 1.6× 334 1.4× 59 0.3× 155 1.2× 76 1.1× 28 951
Tamaki Uehara‐Ichiki Japan 17 632 1.4× 210 0.9× 61 0.4× 235 1.9× 54 0.8× 31 691
Thiện Hồ United States 17 797 1.8× 151 0.6× 56 0.3× 170 1.3× 52 0.7× 37 1.0k
Xiaofei Cheng China 21 941 2.1× 416 1.7× 46 0.3× 169 1.3× 46 0.7× 62 1.1k
Delin Liang United States 11 228 0.5× 58 0.2× 69 0.4× 128 1.0× 25 0.4× 11 444
Francisco M. Ochoa‐Corona United States 18 656 1.5× 190 0.8× 60 0.4× 166 1.3× 47 0.7× 61 860
Zhike Feng China 15 503 1.1× 145 0.6× 37 0.2× 141 1.1× 44 0.6× 33 571

Countries citing papers authored by Mariana del Vas

Since Specialization
Citations

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

Fields of papers citing papers by Mariana del Vas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mariana del Vas. 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 Mariana del Vas. The network helps show where Mariana del Vas may publish in the future.

Co-authorship network of co-authors of Mariana del Vas

This figure shows the co-authorship network connecting the top 25 collaborators of Mariana del Vas. A scholar is included among the top collaborators of Mariana del Vas 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 Mariana del Vas. Mariana del Vas 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.
Vas, Mariana del, et al.. (2023). Negative modulation of the GABAAρ1 receptor function by histamine. European Journal of Pharmacology. 955. 175880–175880. 1 indexed citations
2.
Melero, Roberto, Gabriela Sycz, Cristián Huck‐Iriart, et al.. (2023). A Fijivirus Major Viroplasm Protein Shows RNA-Stimulated ATPase Activity by Adopting Pentameric and Hexameric Assemblies of Dimers. mBio. 14(2). e0002323–e0002323.
3.
Zavallo, Diego, Mariana del Vas, Sebastián Asurmendi, et al.. (2022). Genome-wide identification of MITE-derived microRNAs and their targets in bread wheat. BMC Genomics. 23(1). 154–154. 12 indexed citations
4.
Vas, Mariana del, et al.. (2021). Functional characterization and intracellular localization of a Lotus tenuis NHX antiporter. Plant Cell Tissue and Organ Culture (PCTOC). 146(3). 565–576. 2 indexed citations
5.
Romão, Ema, Analía Delina Dumón, Andrés Wigdorovitz, et al.. (2021). Development of Nanobodies against Mal de Río Cuarto virus major viroplasm protein P9-1 for diagnostic sandwich ELISA and immunodetection. Scientific Reports. 11(1). 20013–20013. 7 indexed citations
6.
Haro, Luis Alejandro de, Ondřej Novák, Regina Feil, et al.. (2019). Mal de Río Cuarto virus infection causes hormone imbalance and sugar accumulation in wheat leaves. BMC Plant Biology. 19(1). 112–112. 19 indexed citations
7.
Dumón, Analía Delina, et al.. (2017). Co-infection with a wheat rhabdovirus causes a reduction inMal de Río Cuarto virustiter in its planthopper vector. Bulletin of Entomological Research. 108(2). 232–240. 7 indexed citations
9.
Dumón, Analía Delina, et al.. (2017). Complete genome sequence of maize yellow striate virus, a new cytorhabdovirus infecting maize and wheat crops in Argentina. Archives of Virology. 163(1). 291–295. 14 indexed citations
10.
Maroniche, Guillermo A., et al.. (2013). High Viral Load in the Planthopper Vector Delphacodes kuscheli (Hemiptera: Delphacidae) is Associated With Successful Transmission of Mal de Río Cuarto Virus. Annals of the Entomological Society of America. 106(1). 93–99. 11 indexed citations
11.
Alfonso, Victoria, et al.. (2012). AcMNPV Core Gene ac109 Is Required for Budded Virion Transport to the Nucleus and for Occlusion of Viral Progeny. PLoS ONE. 7(9). e46146–e46146. 22 indexed citations
12.
13.
Dumón, Analía Delina, et al.. (2011). Identificación y caracterización biológica del Barley yellow striate mosaic virus (BYSMV): nueva enfermedad del trigo en Argentina. Tropical Plant Pathology. 36(6). 374–382. 4 indexed citations
14.
Maroniche, Guillermo A., et al.. (2011). Reference gene selection for gene expression studies using RT-qPCR in virus-infected planthoppers. Virology Journal. 8(1). 308–308. 61 indexed citations
15.
Maroniche, Guillermo A., et al.. (2011). Development of a novel set of Gateway‐compatible vectors for live imaging in insect cells. Insect Molecular Biology. 20(5). 675–685. 14 indexed citations
16.
Bazzini, Ariel, Natalia Inés Almasia, Vanesa Mongelli, et al.. (2009). Virus infection elevates transcriptional activity of miR164a promoter in plants. BMC Plant Biology. 9(1). 152–152. 49 indexed citations
17.
Distéfano, Ana J., Sara Maldonado, H. Esteban Hopp, & Mariana del Vas. (2009). Mal de Río Cuarto virus (MRCV) genomic segment S3 codes for the major core capsid protein. Virus Genes. 38(3). 455–460. 7 indexed citations
18.
Distéfano, Ana J., et al.. (2008). Detection and subcellular localization of dehydrin-like proteins in quinoa (Chenopodium quinoa Willd.) embryos. PROTOPLASMA. 233(1-2). 149–156. 29 indexed citations
19.
Distéfano, Ana J., et al.. (2007). Detection of dehydrin-like proteins in embryos and endosperm of mature Euterpe edulis seeds. PROTOPLASMA. 231(1-2). 1–5. 23 indexed citations
20.
Distéfano, Ana J., H. Esteban Hopp, & Mariana del Vas. (2005). Sequence analysis of genome segments S5 and S10 of Mal de Río Cuarto virus (Fijivirus, Reoviridae). Archives of Virology. 150(6). 1241–1248. 20 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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