Daniel Berenberg
Impact in
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- Machine Learning in Bioinformatics
- Protein Structure and Dynamics
- Bioinformatics and Genomic Networks
- Genomics and Phylogenetic Studies
- RNA and protein synthesis mechanisms
- Microbial Metabolic Engineering and Bioproduction
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- Computational Drug Discovery Methods
Papers in
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- Protein Structure and Dynamics 3
- Machine Learning in Bioinformatics 2
- Genomics and Phylogenetic Studies 1
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- Complex Network Analysis Techniques 2
- Co-authors
- Vladimir Gligorijević (3 shared papers)Richard Bonneau (3 shared papers)Julia Koehler Leman (3 shared papers)Kyunghyun Cho (2 shared papers)Chris Chandler (2 shared papers)P. Douglas Renfrew (2 shared papers)Bryn C. Taylor (2 shared papers)Tomasz Kościółek (2 shared papers)
- Journals
- Nature Communications (2 papers)Nature Biotechnology (1 paper)Proceedings of the ACM on Human-Computer Interaction (1 paper)Zenodo (CERN European Organization for Nuclear Research) (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesPolandNew Zealand
In The Last Decade
Daniel Berenberg
6 papers receiving 639 citations
Daniel Berenberg's Hit Papers
Peers
Comparison fields: 5 of 89
- Molecular Biology 471
- Computational Theory and Mathematics 106
- Molecular Medicine 10
- Microbiology 12
- Applied Microbiology and Biotechnology 3
Countries citing papers authored by Daniel Berenberg
This map shows the geographic impact of Daniel Berenberg'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 Daniel Berenberg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Berenberg more than expected).
Fields of papers citing papers by Daniel Berenberg
This network shows the impact of papers produced by Daniel Berenberg. 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 Daniel Berenberg. The network helps show where Daniel Berenberg may publish in the future.
Co-authors
The 21 scholars most cited alongside Daniel Berenberg, 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 | Structure-based protein function prediction using graph convolutional networks Hit paper breakdown → | 2021 | 510 |
| 2 | 2023 | 73 | |
| 3 | 2023 | 52 | |
| 4 | 2018 | 7 | |
| 5 | 2018 | 3 | |
| 6 | 2021 | 1 |
About Daniel Berenberg
Daniel Berenberg is a scholar working on Molecular Biology, Statistical and Nonlinear Physics, Computer Science Applications, Artificial Intelligence and Transportation, having authored 6 papers that have together received 646 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (3 papers), Mobile Crowdsensing and Crowdsourcing (2 papers), Complex Network Analysis Techniques (2 papers), Machine Learning in Bioinformatics (2 papers), Genomics and Phylogenetic Studies (1 paper), Privacy-Preserving Technologies in Data (1 paper), Advanced MRI Techniques and Applications (1 paper) and Enzyme Structure and Function (1 paper). The work is most often cited by research in Molecular Biology (471 citations), Computational Theory and Mathematics (106 citations), Molecular Medicine (10 citations), Microbiology (12 citations) and Applied Microbiology and Biotechnology (3 citations). Daniel Berenberg has collaborated with scholars based in United States, Poland and New Zealand. Frequent co-authors include Vladimir Gligorijević, Richard Bonneau, Julia Koehler Leman, Kyunghyun Cho, Chris Chandler, P. Douglas Renfrew, Bryn C. Taylor, Tomasz Kościółek, Tommi Vatanen and I. Fisk. Their work appears in journals such as Nature Communications, Nature Biotechnology, Proceedings of the ACM on Human-Computer Interaction, Zenodo (CERN European Organization for Nuclear Research) and arXiv (Cornell University).
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.