Goar Frishman
- Molecular Biology top 5%
- Bioinformatics and Genomic Networks 10
- Microbial Metabolic Engineering and Bioproduction 4
- RNA and protein synthesis mechanisms 4
- Machine Learning in Bioinformatics 3
- Biomedical Text Mining and Ontologies 3
- RNA modifications and cancer 3
- Cancer Research top 5%
- Spectroscopy top 5%
- Advanced Proteomics Techniques and Applications 4
- Cell Biology top 5%
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- Chromosomal and Genetic Variations 3
- Co-authors
- Andreas RueppCorinna MontroneBarbara BraunerGisela FoboHans‐Werner MewesMartin LechnerDmitrij FrishmanMădălina Giurgiu
- Partner nations
- GermanyRussiaUnited States
In The Last Decade
Goar Frishman
22 papers receiving 2.8k citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Molecular Biology 2.5k
- Computational Theory and Mathematics 478
- Cancer Research 357
- Spectroscopy 312
- Cell Biology 234
Countries citing papers authored by Goar Frishman
This map shows the geographic impact of Goar Frishman'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 Goar Frishman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Goar Frishman more than expected).
Fields of papers citing papers by Goar Frishman
This network shows the impact of papers produced by Goar Frishman. 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 Goar Frishman. The network helps show where Goar Frishman may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Goar Frishman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 1 | |
| 2 | 2022 | 93 | |
| 3 | 2022 | 14 | |
| 4 | 2021 | 1 | |
| 5 | 2021 | 34 | |
| 6 | 2021 | 7 | |
| 7 | 2020 | 6 | |
| 8 | 2018 | 12 | |
| 9 | 2017 | 8 | |
| 10 | 2016 | 66 | |
| 11 | 2014 | 98 | |
| 12 | 2013 | 125 | |
| 13 | 2012 | 20 | |
| 14 | 2010 | 232 | |
| 15 | CORUM: the comprehensive resource of mammalian protein complexes—2009breakdown → | 2009 | 997 |
| 16 | 2009 | 96 | |
| 17 | 2007 | 11 | |
| 18 | 2007 | 255 | |
| 19 | 2005 | 11 | |
| 20 | 2004 | 382 |
About Goar Frishman
Goar Frishman is a scholar working on Behavioral Neuroscience, Molecular Biology and Spectroscopy, having authored 22 papers that have together received 2.9k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (10 papers), Advanced Proteomics Techniques and Applications (4 papers), Microbial Metabolic Engineering and Bioproduction (4 papers), RNA and protein synthesis mechanisms (4 papers), Machine Learning in Bioinformatics (3 papers), Biomedical Text Mining and Ontologies (3 papers), RNA modifications and cancer (3 papers) and Chromosomal and Genetic Variations (3 papers). The work is most often cited by research in Molecular Biology (2.5k citations), Computational Theory and Mathematics (478 citations) and Cancer Research (357 citations). Goar Frishman has collaborated with scholars based in Germany, Russia and United States. Frequent co-authors include Andreas Ruepp, Corinna Montrone, Barbara Brauner, Gisela Fobo, Hans‐Werner Mewes, Martin Lechner, Dmitrij Frishman, Mădălina Giurgiu, Volker Stümpflen and Philipp Pagel. Their work appears in journals such as Nucleic Acids Research, Scientific Reports, Bioinformatics, Cell stem cell and Genome 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.