Michael Sierk
Impact in
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- Protein Structure and Dynamics
- Genomics and Phylogenetic Studies
- Genetics, Bioinformatics, and Biomedical Research
- Retinoids in leukemia and cellular processes
- RNA and protein synthesis mechanisms
- Machine Learning in Bioinformatics
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- Estrogen and related hormone effects
Papers in
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- Genetics, Bioinformatics, and Biomedical Research 3
- DNA and Nucleic Acid Chemistry 2
- Machine Learning in Bioinformatics 2
- Protein Structure and Dynamics 2
- Genomics and Phylogenetic Studies 2
- DNA Repair Mechanisms 1
- Glycosylation and Glycoproteins Research 1
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- Enzyme Structure and Function 2
- Co-authors
- William R. Pearson (3 shared papers)Gerard J. Kleywegt (1 shared paper)Fraydoon Rastinejad (2 shared papers)Qiang Zhao (2 shared papers)Bijan Ahvazi (1 shared paper)Scott Chasse (1 shared paper)Anne Rosenwald (2 shared papers)Mark Pauley (3 shared papers)
- Journals
- Communications Biology (1 paper)Structure (1 paper)PLoS Computational Biology (1 paper)Frontiers in Neuroscience (1 paper)Frontiers in Oncology (1 paper)
- Partner nations
- United StatesUnited KingdomSouth Africa
In The Last Decade
Michael Sierk
13 papers receiving 475 citations
Peers
Comparison fields: 5 of 108
- Molecular Biology 359
- Genetics 80
- Biochemistry 13
- Cellular and Molecular Neuroscience 38
- Information Systems and Management 14
Countries citing papers authored by Michael Sierk
This map shows the geographic impact of Michael Sierk'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 Michael Sierk with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Sierk more than expected).
Fields of papers citing papers by Michael Sierk
This network shows the impact of papers produced by Michael Sierk. 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 Michael Sierk. The network helps show where Michael Sierk may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Sierk, 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 | 2000 | 106 | |
| 2 | 2004 | 94 | |
| 3 | 2004 | 87 | |
| 4 | 2005 | 66 | |
| 5 | 2018 | 63 | |
| 6 | 2001 | 42 | |
| 7 | 2020 | 14 | |
| 8 | 2024 | 12 | |
| 9 | 2010 | 11 | |
| 10 | 2023 | 7 | |
| 11 | 2022 | 2 | |
| 12 | 2020 | 1 | |
| 13 | 2020 | 1 |
About Michael Sierk
Michael Sierk is a scholar working on Molecular Biology, Materials Chemistry, Infectious Diseases, Computer Networks and Communications and Information Systems, having authored 13 papers that have together received 506 indexed citations. Recurring topics across this work include Genetics, Bioinformatics, and Biomedical Research (3 papers), Enzyme Structure and Function (2 papers), DNA and Nucleic Acid Chemistry (2 papers), Machine Learning in Bioinformatics (2 papers), Protein Structure and Dynamics (2 papers), Genomics and Phylogenetic Studies (2 papers), DNA Repair Mechanisms (1 paper) and Glycosylation and Glycoproteins Research (1 paper). The work is most often cited by research in Molecular Biology (359 citations), Genetics (80 citations), Biochemistry (13 citations), Cellular and Molecular Neuroscience (38 citations) and Information Systems and Management (14 citations). Michael Sierk has collaborated with scholars based in United States, United Kingdom and South Africa. Frequent co-authors include William R. Pearson, Gerard J. Kleywegt, Fraydoon Rastinejad, Qiang Zhao, Bijan Ahvazi, Scott Chasse, Anne Rosenwald, Mark Pauley, Bruno Gaëta and Gabriella Rustici. Their work appears in journals such as Communications Biology, Structure, PLoS Computational Biology, Frontiers in Neuroscience and Frontiers in Oncology.
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.