Elin Teppa
Impact in
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- Protein Structure and Dynamics
- Glycosylation and Glycoproteins Research
- RNA and protein synthesis mechanisms
- Genomics and Phylogenetic Studies
- Machine Learning in Bioinformatics
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- Computational Drug Discovery Methods
Papers in ⓘ
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- Glycosylation and Glycoproteins Research 8
- Protein Structure and Dynamics 5
- Genomics and Phylogenetic Studies 4
- Bioinformatics and Genomic Networks 3
- Machine Learning in Bioinformatics 2
- Co-authors
- Cristina Marino‐Buslje (7 shared papers)Morten Nielsen (3 shared papers)Franco L. Simonetti (2 shared papers)Ariel Chernomoretz (1 shared paper)Anne Harduin‐Lepers (9 shared papers)Daniel Petit (6 shared papers)Diego Javier Zea (5 shared papers)Tomás Di Domenico (1 shared paper)
In The Last Decade
Elin Teppa
20 papers receiving 446 citations
Peers
Comparison fields: 5 of 72
- Molecular Biology 347
- Computational Theory and Mathematics 49
- Endocrinology 15
- Immunology 57
- Cell Biology 39
Countries citing papers authored by Elin Teppa
This map shows the geographic impact of Elin Teppa'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 Elin Teppa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Elin Teppa more than expected).
Fields of papers citing papers by Elin Teppa
This network shows the impact of papers produced by Elin Teppa. 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 Elin Teppa. The network helps show where Elin Teppa may publish in the future.
Co-authors
The 25 scholars most cited alongside Elin Teppa, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 131 | |
| 2 | 2010 | 62 | |
| 3 | 2014 | 36 | |
| 4 | 2012 | 34 | |
| 5 | 2016 | 28 | |
| 6 | 2015 | 22 | |
| 7 | 2018 | 22 | |
| 8 | 2018 | 22 | |
| 9 | 2017 | 19 | |
| 10 | 2021 | 17 | |
| 11 | 2020 | 15 | |
| 12 | 2019 | 9 | |
| 13 | 2013 | 9 | |
| 14 | 2022 | 7 | |
| 15 | 2023 | 4 | |
| 16 | 2024 | 3 | |
| 17 | 2020 | 3 | |
| 18 | 2020 | 3 | |
| 19 | 2023 | 2 | |
| 20 | 2024 | 1 |
About Elin Teppa
Elin Teppa is a scholar working on Biotechnology, Molecular Biology, Hepatology, Cell Biology and Organic Chemistry, having authored 21 papers that have together received 449 indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (8 papers), Protein Structure and Dynamics (5 papers), Genomics and Phylogenetic Studies (4 papers), Carbohydrate Chemistry and Synthesis (4 papers), Proteoglycans and glycosaminoglycans research (3 papers), Bioinformatics and Genomic Networks (3 papers), Machine Learning in Bioinformatics (2 papers) and Computational Drug Discovery Methods (2 papers). The work is most often cited by research in Molecular Biology (347 citations), Computational Theory and Mathematics (49 citations), Endocrinology (15 citations), Immunology (57 citations) and Cell Biology (39 citations). Elin Teppa has collaborated with scholars based in France, Argentina and Germany. Frequent co-authors include Cristina Marino‐Buslje, Morten Nielsen, Franco L. Simonetti, Ariel Chernomoretz, Anne Harduin‐Lepers, Daniel Petit, Diego Javier Zea, Tomás Di Domenico, José M. Delfino and Angela D. Wilkins. Their work appears in journals such as International Journal of Molecular Sciences, Nucleic Acids Research, Scientific Reports, Virus Evolution and PLoS Computational Biology.
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.