Marcela K. Preininger

21 total papers · 952 total citations
13 papers, 527 citations indexed

About

Marcela K. Preininger is a scholar working on Molecular Biology, Surgery and Cellular and Molecular Neuroscience. According to data from OpenAlex, Marcela K. Preininger has authored 13 papers receiving a total of 527 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Surgery and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Marcela K. Preininger's work include Pluripotent Stem Cells Research (5 papers), Neuroscience and Neural Engineering (3 papers) and Tissue Engineering and Regenerative Medicine (2 papers). Marcela K. Preininger is often cited by papers focused on Pluripotent Stem Cells Research (5 papers), Neuroscience and Neural Engineering (3 papers) and Tissue Engineering and Regenerative Medicine (2 papers). Marcela K. Preininger collaborates with scholars based in United States and Canada. Marcela K. Preininger's co-authors include Chunhui Xu, Daniela Kaufer, Rajneesh Jha, Monalisa Singh, Qingling Wu, Mary B. Wagner, Greg Gibson, Dalia Arafat, Kevin Maher and Milton R. Brown and has published in prestigious journals such as The Journal of Immunology, Scientific Reports and International Journal of Molecular Sciences.

In The Last Decade

Marcela K. Preininger

13 papers receiving 523 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Marcela K. Preininger 234 115 99 95 87 13 527
Linda M. van der Graaf 228 1.0× 77 0.7× 109 1.1× 41 0.4× 42 0.5× 23 571
Holly M. Lauridsen 191 0.8× 59 0.5× 49 0.5× 43 0.5× 99 1.1× 11 551
David A. Finney 279 1.2× 59 0.5× 83 0.8× 54 0.6× 164 1.9× 17 582
Sara Biagiotti 222 0.9× 68 0.6× 91 0.9× 77 0.8× 21 0.2× 24 519
Koutaro Takamatsu 229 1.0× 71 0.6× 82 0.8× 22 0.2× 174 2.0× 26 608
Tadatsune Iida 156 0.7× 38 0.3× 125 1.3× 28 0.3× 43 0.5× 14 452
Christine A. Morton 187 0.8× 33 0.3× 121 1.2× 58 0.6× 26 0.3× 18 497
Frank K. Lee 286 1.2× 145 1.3× 70 0.7× 21 0.2× 25 0.3× 9 489
Francis Boudreault 227 1.0× 65 0.6× 82 0.8× 53 0.6× 21 0.2× 26 562
Peter S. Lu 178 0.8× 99 0.9× 38 0.4× 29 0.3× 67 0.8× 9 562

Countries citing papers authored by Marcela K. Preininger

Since Specialization
Citations

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

Fields of papers citing papers by Marcela K. Preininger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marcela K. Preininger. 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 Marcela K. Preininger. The network helps show where Marcela K. Preininger may publish in the future.

Co-authorship network of co-authors of Marcela K. Preininger

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

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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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