Genaro Pimienta

976 total citations
19 papers, 775 citations indexed

About

Genaro Pimienta is a scholar working on Molecular Biology, Oncology and Epidemiology. According to data from OpenAlex, Genaro Pimienta has authored 19 papers receiving a total of 775 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 6 papers in Oncology and 5 papers in Epidemiology. Recurrent topics in Genaro Pimienta's work include Viral-associated cancers and disorders (4 papers), Nicotinic Acetylcholine Receptors Study (3 papers) and Glycosylation and Glycoproteins Research (2 papers). Genaro Pimienta is often cited by papers focused on Viral-associated cancers and disorders (4 papers), Nicotinic Acetylcholine Receptors Study (3 papers) and Glycosylation and Glycoproteins Research (2 papers). Genaro Pimienta collaborates with scholars based in United States, Mexico and Italy. Genaro Pimienta's co-authors include Jaime Pascual, Joan A. Steitz, Kristina M. Herbert, Nara Lee, Lynne Regan, Daniel DiMaio, Suzanne J. DeGregorio, Andrei Alexandrov, Leena Kuruvilla and Michael R. Wyler and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and The FASEB Journal.

In The Last Decade

Genaro Pimienta

19 papers receiving 764 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Genaro Pimienta United States 14 518 134 132 122 111 19 775
Jianyin Lin China 17 362 0.7× 96 0.7× 135 1.0× 93 0.8× 65 0.6× 33 612
Philippe Gonzalo France 17 661 1.3× 109 0.8× 65 0.5× 88 0.7× 115 1.0× 37 943
Debomita Sengupta India 16 653 1.3× 105 0.8× 78 0.6× 52 0.4× 160 1.4× 31 944
Ferdy R. van Diemen Netherlands 6 734 1.4× 114 0.9× 74 0.6× 176 1.4× 93 0.8× 6 974
Katarzyna Kulej United States 18 688 1.3× 137 1.0× 57 0.4× 180 1.5× 151 1.4× 30 1.0k
Paul Tawa United States 17 695 1.3× 175 1.3× 128 1.0× 99 0.8× 157 1.4× 48 1.2k
Anne-Marie Hesse France 16 710 1.4× 65 0.5× 83 0.6× 121 1.0× 82 0.7× 34 1.0k
Flavia Autore United Kingdom 15 688 1.3× 128 1.0× 93 0.7× 58 0.5× 63 0.6× 19 1.1k
Qi Hu United States 17 1.0k 2.0× 142 1.1× 65 0.5× 90 0.7× 127 1.1× 29 1.3k
Rafael Cuesta United States 17 1.2k 2.3× 115 0.9× 129 1.0× 72 0.6× 107 1.0× 19 1.4k

Countries citing papers authored by Genaro Pimienta

Since Specialization
Citations

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

Fields of papers citing papers by Genaro Pimienta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Genaro Pimienta

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

All Works

19 of 19 papers shown
1.
Heithoff, Douglas M., Genaro Pimienta, Scott Mahan, et al.. (2022). Coagulation factor protein abundance in the pre-septic state predicts coagulopathic activities that arise during late-stage murine sepsis. EBioMedicine. 78. 103965–103965. 10 indexed citations
2.
Pimienta, Genaro, Douglas M. Heithoff, Jeffrey D. Esko, et al.. (2019). Plasma Proteome Signature of Sepsis: a Functionally Connected Protein Network. PROTEOMICS. 19(5). e1800389–e1800389. 16 indexed citations
3.
4.
Herbert, Kristina M. & Genaro Pimienta. (2016). Consideration of Epstein-Barr Virus-Encoded Noncoding RNAs EBER1 and EBER2 as a Functional Backup of Viral Oncoprotein Latent Membrane Protein 1. mBio. 7(1). e01926–15. 16 indexed citations
5.
Plamann, Michael, et al.. (2015). Two microtubule-plus-end binding proteins LIS1-1 and LIS1-2, homologues of human LIS1 in Neurospora crassa. Fungal Genetics and Biology. 82. 213–227. 7 indexed citations
6.
Pimienta, Genaro, et al.. (2015). Proteomics and Transcriptomics of BJAB Cells Expressing the Epstein-Barr Virus Noncoding RNAs EBER1 and EBER2. PLoS ONE. 10(6). e0124638–e0124638. 25 indexed citations
7.
Herbert, Kristina M., Genaro Pimienta, Suzanne J. DeGregorio, Andrei Alexandrov, & Joan A. Steitz. (2013). Phosphorylation of DGCR8 Increases Its Intracellular Stability and Induces a Progrowth miRNA Profile. Cell Reports. 5(4). 1070–1081. 71 indexed citations
8.
Moss, Walter N., Nara Lee, Genaro Pimienta, & Joan A. Steitz. (2013). RNA families in Epstein–Barr virus. RNA Biology. 11(1). 10–17. 36 indexed citations
9.
Lipovsky, Alex, Andreea Popa, Genaro Pimienta, et al.. (2013). Genome-wide siRNA screen identifies the retromer as a cellular entry factor for human papillomavirus. Proceedings of the National Academy of Sciences. 110(18). 7452–7457. 156 indexed citations
10.
Lee, Nara, Genaro Pimienta, & Joan A. Steitz. (2012). AUF1/hnRNP D is a novel protein partner of the EBER1 noncoding RNA of Epstein-Barr virus. RNA. 18(11). 2073–2082. 66 indexed citations
11.
Grove, Tijana Ž., Jason D. Forster, Genaro Pimienta, Eric R. Dufresne, & Lynne Regan. (2012). A modular approach to the design of protein‐based smart gels. Biopolymers. 97(7). 508–517. 35 indexed citations
12.
Chen, Hexin, Genaro Pimienta, Xu Sun, et al.. (2011). Proteomic characterization of Her2/neu‐overexpressing breast cancer cells. PROTEOMICS - CLINICAL APPLICATIONS. 5(3-4). 201–201. 3 indexed citations
13.
Pimienta, Genaro, Kristina M. Herbert, & Lynne Regan. (2011). A Compound That Inhibits the HOP–Hsp90 Complex Formation and Has Unique Killing Effects in Breast Cancer Cell Lines. Molecular Pharmaceutics. 8(6). 2252–2261. 52 indexed citations
14.
Chen, Hexin, Genaro Pimienta, Xu Sun, et al.. (2010). Proteomic characterization of Her2/neu‐overexpressing breast cancer cells. PROTEOMICS. 10(21). 3800–3810. 31 indexed citations
15.
Pimienta, Genaro, Raghothama Chaerkady, & Akhilesh Pandey. (2009). SILAC for Global Phosphoproteomic Analysis. Methods in molecular biology. 527. 107–116. 23 indexed citations
16.
Pimienta, Genaro & Jaime Pascual. (2007). Canonical and Alternative MAPK Signaling. Cell Cycle. 6(21). 2628–2632. 97 indexed citations
17.
Pimienta, Genaro, Scott B. Ficarro, Gustavo J. Gutierrez, et al.. (2007). Autophosphorylation Properties of Inactive and Active JNK2. Cell Cycle. 6(14). 1762–1771. 13 indexed citations
18.
Río‐Portilla, Federico del, Genaro Pimienta, Fernando Z. Zamudio, et al.. (2004). NMR solution structure of Cn12, a novel peptide from the Mexican scorpion Centruroides noxius with a typical β‐toxin sequence but with α‐like physiological activity. European Journal of Biochemistry. 271(12). 2504–2516. 20 indexed citations
19.
Gurrola, Georgina B., Barbara Rosati, Marcella Rocchetti, et al.. (1999). A toxin to nervous, cardiac, and endocrine ERG K + channels isolated from Centruroides noxius scorpion venom. The FASEB Journal. 13(8). 953–962. 89 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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