Michael Kosicki
Impact in
- Aging top 5%
- Genetics, Aging, and Longevity in Model Organisms
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- Innovation and Socioeconomic Development
Papers in
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- CRISPR and Genetic Engineering 5
- Genomics and Chromatin Dynamics 4
- RNA and protein synthesis mechanisms 3
- Pluripotent Stem Cells Research 3
- RNA Interference and Gene Delivery 2
- Epigenetics and DNA Methylation 2
- RNA Research and Splicing 2
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- T-cell and B-cell Immunology 2
- Co-authors
- Felicity Allen (2 shared papers)Emmanouil Metzakopian (2 shared papers)Leopold Parts (2 shared papers)Allan Bradley (2 shared papers)Luca Crepaldi (2 shared papers)Petra Páleníková (1 shared paper)Heather P. Harding (1 shared paper)Vladimir Yu Kiselev (1 shared paper)
- Journals
- Nature Communications (4 papers)Nature (2 papers)Cell Genomics (1 paper)Nature Medicine (1 paper)Nucleic Acids Research (1 paper)
- Partner nations
- United StatesUnited KingdomDenmark
In The Last Decade
Michael Kosicki
12 papers receiving 643 citations
Michael Kosicki's Hit Papers
Peers
Comparison fields: 5 of 65
- Aging 57
- Business and International Management 61
- Molecular Biology 513
- Immunology 93
- Genetics 122
Countries citing papers authored by Michael Kosicki
This map shows the geographic impact of Michael Kosicki'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 Kosicki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Kosicki more than expected).
Fields of papers citing papers by Michael Kosicki
This network shows the impact of papers produced by Michael Kosicki. 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 Kosicki. The network helps show where Michael Kosicki may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Kosicki, 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 | Predicting the mutations generated by repair of Cas9-induced double-strand breaks Hit paper breakdown → | 2018 | 348 |
| 2 | 2014 | 122 | |
| 3 | 2018 | 66 | |
| 4 | 2022 | 57 | |
| 5 | 2017 | 24 | |
| 6 | 2024 | 10 | |
| 7 | 2024 | 9 | |
| 8 | 2024 | 5 | |
| 9 | 2025 | 4 | |
| 10 | 2024 | 3 | |
| 11 | 2025 | 2 | |
| 12 | 2013 | 1 | |
| 13 | 2026 | 0 |
About Michael Kosicki
Michael Kosicki is a scholar working on Molecular Biology, Immunology, Genetics, Cognitive Neuroscience and Oncology, having authored 13 papers that have together received 651 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (5 papers), Genomics and Chromatin Dynamics (4 papers), RNA and protein synthesis mechanisms (3 papers), Pluripotent Stem Cells Research (3 papers), RNA Interference and Gene Delivery (2 papers), Epigenetics and DNA Methylation (2 papers), RNA Research and Splicing (2 papers) and T-cell and B-cell Immunology (2 papers). The work is most often cited by research in Aging (57 citations), Business and International Management (61 citations), Molecular Biology (513 citations), Immunology (93 citations) and Genetics (122 citations). Michael Kosicki has collaborated with scholars based in United States, United Kingdom and Denmark. Frequent co-authors include Felicity Allen, Emmanouil Metzakopian, Leopold Parts, Allan Bradley, Luca Crepaldi, Petra Páleníková, Heather P. Harding, Vladimir Yu Kiselev, Vitalii Kleshchevnikov and Francisco Muñoz‐Martínez. Their work appears in journals such as Nature Communications, Nature, Cell Genomics, Nature Medicine and Nucleic Acids Research.
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.