Daniel Zaidman
Impact in
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- Computational Drug Discovery Methods
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- Protein Degradation and Inhibitors
- Ubiquitin and proteasome pathways
- Chemical Synthesis and Analysis
Papers in
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- Ubiquitin and proteasome pathways 2
- Protein Degradation and Inhibitors 2
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- Click Chemistry and Applications 3
- Co-authors
- Nir London (5 shared papers)Jaime Prilusky (2 shared papers)Haim J. Wolfson (3 shared papers)Ronen Gabizon (2 shared papers)Haim Barr (2 shared papers)Efrat Resnick (2 shared papers)A.N. Plotnikov (1 shared paper)Neta Gurwicz (1 shared paper)
- Journals
- Journal of Chemical Information and Modeling (2 papers)Scientific Reports (1 paper)Proteins Structure Function and Bioinformatics (1 paper)Proceedings of the National Academy of Sciences (1 paper)ChemBioChem (1 paper)
- Partner nations
- IsraelUnited KingdomAustralia
In The Last Decade
Daniel Zaidman
10 papers receiving 438 citations
Peers
Comparison fields: 5 of 56
- Computational Theory and Mathematics 106
- Molecular Biology 331
- Oncology 100
- Organic Chemistry 111
- Hematology 37
Countries citing papers authored by Daniel Zaidman
This map shows the geographic impact of Daniel Zaidman'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 Zaidman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Zaidman more than expected).
Fields of papers citing papers by Daniel Zaidman
This network shows the impact of papers produced by Daniel Zaidman. 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 Zaidman. The network helps show where Daniel Zaidman may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Zaidman, 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 | 2020 | 150 | |
| 2 | 2021 | 76 | |
| 3 | 2021 | 61 | |
| 4 | 2018 | 46 | |
| 5 | 2020 | 45 | |
| 6 | 2019 | 34 | |
| 7 | 2016 | 21 | |
| 8 | 2022 | 8 | |
| 9 | 2024 | 3 | |
| 10 | 2017 | 2 |
About Daniel Zaidman
Daniel Zaidman is a scholar working on Molecular Biology, Organic Chemistry, Radiology, Nuclear Medicine and Imaging, Computational Theory and Mathematics and Infectious Diseases, having authored 10 papers that have together received 446 indexed citations. Recurring topics across this work include Click Chemistry and Applications (3 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), Ubiquitin and proteasome pathways (2 papers), Protein Degradation and Inhibitors (2 papers), Computational Drug Discovery Methods (2 papers), Vitamin C and Antioxidants Research (1 paper), Cholinesterase and Neurodegenerative Diseases (1 paper) and Lymphoma Diagnosis and Treatment (1 paper). The work is most often cited by research in Computational Theory and Mathematics (106 citations), Molecular Biology (331 citations), Oncology (100 citations), Organic Chemistry (111 citations) and Hematology (37 citations). Daniel Zaidman has collaborated with scholars based in Israel, United Kingdom and Australia. Frequent co-authors include Nir London, Jaime Prilusky, Haim J. Wolfson, Ronen Gabizon, Haim Barr, Efrat Resnick, A.N. Plotnikov, Neta Gurwicz, Ziv Shulman and Rambabu Reddi. Their work appears in journals such as Journal of Chemical Information and Modeling, Scientific Reports, Proteins Structure Function and Bioinformatics, Proceedings of the National Academy of Sciences and ChemBioChem.
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.