Daniel Ziemek
Impact in
- Health Informatics top 5%
- Rheumatology top 10%
- Rheumatoid Arthritis Research and Therapies
Papers in
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- Bioinformatics and Genomic Networks 4
- Gene expression and cancer classification 2
- Single-cell and spatial transcriptomics 2
- Biomedical Text Mining and Ontologies 2
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- Rheumatoid Arthritis Research and Therapies 7
- Co-authors
- Ben S. Sidders (5 shared papers)Ahmed Enayetallah (8 shared papers)Leonid Chindelevitch (4 shared papers)Ranjit Randhawa (3 shared papers)Mateusz Maciejewski (9 shared papers)Enoch S. Huang (2 shared papers)Kourosh Zarringhalam (5 shared papers)Susan A. Murphy (1 shared paper)
- Journals
- Bioinformatics (4 papers)Scientific Reports (4 papers)BMC Bioinformatics (4 papers)PLoS ONE (3 papers)Lara D. Veeken (2 papers)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Daniel Ziemek
35 papers receiving 1.3k citations
Daniel Ziemek's Hit Papers
Peers
Comparison fields: 5 of 132
- Health Informatics 47
- Rheumatology 140
- Health Information Management 44
- Internal Medicine 27
- Molecular Biology 493
Countries citing papers authored by Daniel Ziemek
This map shows the geographic impact of Daniel Ziemek'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 Ziemek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Ziemek more than expected).
Fields of papers citing papers by Daniel Ziemek
This network shows the impact of papers produced by Daniel Ziemek. 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 Ziemek. The network helps show where Daniel Ziemek may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Ziemek, 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 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | From hype to reality: data science enabling personalized medicine Hit paper breakdown → | 2018 | 303 |
| 2 | 2013 | 139 | |
| 3 | 2012 | 107 | |
| 4 | 2020 | 97 | |
| 5 | 2016 | 80 | |
| 6 | 2018 | 57 | |
| 7 | 2020 | 53 | |
| 8 | 2019 | 53 | |
| 9 | 2011 | 45 | |
| 10 | 2021 | 43 | |
| 11 | 2014 | 40 | |
| 12 | 2021 | 31 | |
| 13 | 2017 | 28 | |
| 14 | 2012 | 27 | |
| 15 | 2016 | 26 | |
| 16 | 2017 | 24 | |
| 17 | 2019 | 21 | |
| 18 | 2014 | 20 | |
| 19 | 2011 | 19 | |
| 20 | 2021 | 18 |
About Daniel Ziemek
Daniel Ziemek is a scholar working on Molecular Biology, Rheumatology, Physiology, Genetics and Surgery, having authored 35 papers that have together received 1.4k indexed citations. Recurring topics across this work include Rheumatoid Arthritis Research and Therapies (7 papers), Bioinformatics and Genomic Networks (4 papers), Gene expression and cancer classification (2 papers), T-cell and B-cell Immunology (2 papers), Single-cell and spatial transcriptomics (2 papers), Lipid metabolism and biosynthesis (2 papers), Adipose Tissue and Metabolism (2 papers) and Biomedical Text Mining and Ontologies (2 papers). The work is most often cited by research in Health Informatics (47 citations), Rheumatology (140 citations), Health Information Management (44 citations), Internal Medicine (27 citations) and Molecular Biology (493 citations). Daniel Ziemek has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Ben S. Sidders, Ahmed Enayetallah, Leonid Chindelevitch, Ranjit Randhawa, Mateusz Maciejewski, Enoch S. Huang, Kourosh Zarringhalam, Susan A. Murphy, Rainer Spang and Marloes H. Maathuis. Their work appears in journals such as Bioinformatics, Scientific Reports, BMC Bioinformatics, PLoS ONE and Lara D. Veeken.
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.