Fabian Birzele
- Cancer Research top 5%
- MicroRNA in disease regulation 14
- Cancer-related molecular mechanisms research 8
- Molecular Biology top 10%
- Protein Structure and Dynamics 8
- Circular RNAs in diseases 8
- RNA modifications and cancer 6
- Machine Learning in Bioinformatics 5
- RNA and protein synthesis mechanisms 5
- Health Informatics top 10%
- Oncology top 10%
- Immunology top 10%
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- Cancer Mechanisms and Therapy 9
- Co-authors
- Ulrich H. WeidleRüdiger RügerRalf ZimmerGergely CsabaGwendlyn KollmorgenSolveig BadilloBernhard SteiertJitao David Zhang
- Journals
- Cancer Genomics & Proteomics (17 papers)Bioinformatics (5 papers)Nucleic Acids Research (5 papers)
- Partner nations
- GermanySwitzerlandUnited States
In The Last Decade
Fabian Birzele
58 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 180
- Cancer Research 548
- Molecular Biology 1.2k
- Health Informatics 21
- Oncology 380
- Immunology 243
Countries citing papers authored by Fabian Birzele
This map shows the geographic impact of Fabian Birzele'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 Fabian Birzele with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabian Birzele more than expected).
Fields of papers citing papers by Fabian Birzele
This network shows the impact of papers produced by Fabian Birzele. 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 Fabian Birzele. The network helps show where Fabian Birzele may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Fabian Birzele, 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 | 2025 | 0 | |
| 2 | 2023 | 7 | |
| 3 | 2022 | 18 | |
| 4 | 2021 | 2 | |
| 5 | An Introduction to Machine Learningbreakdown → | 2020 | 503 |
| 6 | 2018 | 6 | |
| 7 | 2018 | 53 | |
| 8 | 2018 | 25 | |
| 9 | 2018 | 26 | |
| 10 | 2017 | 5 | |
| 11 | 2016 | 10 | |
| 12 | 2016 | 15 | |
| 13 | 2016 | 70 | |
| 14 | 2015 | 45 | |
| 15 | 2015 | 45 | |
| 16 | 2013 | 35 | |
| 17 | 2010 | 83 | |
| 18 | 2007 | 43 | |
| 19 | 2007 | 3 | |
| 20 | 2004 | 1 |
About Fabian Birzele
Fabian Birzele is a scholar working on Cancer Research, Pathology and Forensic Medicine and Molecular Biology, having authored 59 papers that have together received 2.2k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (14 papers), Cancer Mechanisms and Therapy (9 papers), Protein Structure and Dynamics (8 papers), Cancer-related molecular mechanisms research (8 papers), Circular RNAs in diseases (8 papers), RNA modifications and cancer (6 papers), Machine Learning in Bioinformatics (5 papers) and RNA and protein synthesis mechanisms (5 papers). The work is most often cited by research in Cancer Research (548 citations), Molecular Biology (1.2k citations) and Health Informatics (21 citations). Fabian Birzele has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include Ulrich H. Weidle, Rüdiger Rüger, Ralf Zimmer, Gergely Csaba, Gwendlyn Kollmorgen, Solveig Badillo, Bernhard Steiert, Jitao David Zhang, Iakov I. Davydov and Balázs Bánfai. Their work appears in journals such as Cancer Genomics & Proteomics, Bioinformatics, Nucleic Acids Research, Clinical Cancer Research and Scientific Reports.
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.