Nina Groß

760 total citations
4 papers, 65 citations indexed

About

Nina Groß is a scholar working on Molecular Biology, Organic Chemistry and Animal Science and Zoology. According to data from OpenAlex, Nina Groß has authored 4 papers receiving a total of 65 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Molecular Biology, 1 paper in Organic Chemistry and 1 paper in Animal Science and Zoology. Recurrent topics in Nina Groß's work include Assembly Line Balancing Optimization (1 paper), Manufacturing Process and Optimization (1 paper) and Flexible and Reconfigurable Manufacturing Systems (1 paper). Nina Groß is often cited by papers focused on Assembly Line Balancing Optimization (1 paper), Manufacturing Process and Optimization (1 paper) and Flexible and Reconfigurable Manufacturing Systems (1 paper). Nina Groß collaborates with scholars based in Germany, United Kingdom and Finland. Nina Groß's co-authors include Karin Schwarz, Stephan Drusch, Mark Griffiths, Darcy E. Wagner, Simone A. Walker, Marjo‐Riitta Järvelin, Maria Kolatsi‐Joannou, Laura L. Yates, Mélanie Königshoff and Eugenia Papakrivopoulou and has published in prestigious journals such as Cancers, European Journal of Lipid Science and Technology and Disease Models & Mechanisms.

In The Last Decade

Nina Groß

4 papers receiving 64 citations

Peers

Nina Groß
Nina Groß
Citations per year, relative to Nina Groß Nina Groß (= 1×) peers Kengo Banshoya

Countries citing papers authored by Nina Groß

Since Specialization
Citations

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

Fields of papers citing papers by Nina Groß

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nina Groß

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

All Works

4 of 4 papers shown
1.
Groß, Nina, et al.. (2021). Multi-criteria evaluation within concept planning phase of assembly system design. Procedia CIRP. 97. 296–301. 1 indexed citations
2.
Steiger, Katja, Nina Groß, Sebastian A. Widholz, et al.. (2020). Genetically Engineered Mouse Models of Liver Tumorigenesis Reveal a Wide Histological Spectrum of Neoplastic and Non-Neoplastic Liver Lesions. Cancers. 12(8). 2265–2265. 4 indexed citations
3.
Yates, Laura L., Simone A. Walker, Nina Groß, et al.. (2017). Heterozygous Vangl2 Looptail mice reveal novel roles for the planar cell polarity pathway in adult lung homeostasis and repair. Disease Models & Mechanisms. 10(4). 409–423. 27 indexed citations
4.
Drusch, Stephan, Nina Groß, & Karin Schwarz. (2008). Efficient stabilization of bulk fish oil rich in long‐chain polyunsaturated fatty acids. European Journal of Lipid Science and Technology. 110(4). 351–359. 33 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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