Joanna Wysocka
- Molecular Biology top 0.1%
- Cancer Research top 0.5%
- Genetics top 0.5%
- Plant Science top 1%
- Immunology top 2%
- Co-authors
- Tomek SwigutC. David AllisEliezer CaloRyan A. FlynnÁlvaro Rada-IglesiasWinship HerrRuchi BajpaiSamantha A. Brugmann
- Topics
- Genomics and Chromatin Dynamics (41 papers)Epigenetics and DNA Methylation (30 papers)RNA Research and Splicing (20 papers)
- Partner nations
- United StatesPolandBelgium
In The Last Decade
Joanna Wysocka
108 papers receiving 19.3k citations
Hit Papers
Peers
Comparison fields: 5 of 160
- Molecular Biology 16.6k
- Cancer Research 2.7k
- Genetics 2.4k
- Plant Science 2.0k
- Immunology 1.4k
Countries citing papers authored by Joanna Wysocka
This map shows the geographic impact of Joanna Wysocka'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 Joanna Wysocka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joanna Wysocka more than expected).
Fields of papers citing papers by Joanna Wysocka
This network shows the impact of papers produced by Joanna Wysocka. 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 Joanna Wysocka. The network helps show where Joanna Wysocka may publish in the future.
Co-authorship network of co-authors of Joanna Wysocka
This figure shows the co-authorship network connecting the top 25 collaborators of Joanna Wysocka. A scholar is included among the top collaborators of Joanna Wysocka based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Joanna Wysocka. Joanna Wysocka is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 5 | |
| 4 | 1 | |
| 5 | 9 | |
| 6 | 29 | |
| 7 | 13 | |
| 8 | 1 | |
| 9 | 10 | |
| 10 | 89 | |
| 11 | 23 | |
| 12 | 45 | |
| 13 | 242 | |
| 14 | Ever-Changing Landscapes: Transcriptional Enhancers in Development and Evolutionbreakdown → | 607 |
| 15 | [Examples of application of X chromosomal markers in familial investigations and personal identification]. | 2 |
| 16 | Histone marks predict cell plasticity of the adult human retinal pigment epithelium | 1 |
| 17 | Identification of 67 Histone Marks and Histone Lysine Crotonylation as a New Type of Histone Modificationbreakdown → | 1385 |
| 18 | 293 | |
| 19 | CHARACTERISTICS OF ACID PHOSPHATASE FROM RAINBOW TROUT (ONCORHYNCHUS MYKISS) SPERMATOZOA | 2 |
| 20 | Human PAD4 Regulates Histone Arginine Methylation Levels via Demethyliminationbreakdown → | 774 |
About Joanna Wysocka
Joanna Wysocka is a scholar working on Molecular Biology, Aging and Physiology, having authored 112 papers that have together received 19.5k indexed citations. Recurring topics across this work include Genomics and Chromatin Dynamics (41 papers), Epigenetics and DNA Methylation (30 papers) and RNA Research and Splicing (20 papers). The work is most often cited by research in Molecular Biology (16.6k citations), Cancer Research (2.7k citations) and Aging (226 citations). Joanna Wysocka has collaborated with scholars based in United States, Poland and Belgium. Frequent co-authors include Tomek Swigut, C. David Allis, Eliezer Calo, Ryan A. Flynn, Álvaro Rada-Iglesias, Winship Herr, Ruchi Bajpai, Samantha A. Brugmann, Alexander J. Ruthenburg and Sara L. Prescott. Their work appears in journals such as Nature, Science and Cell.
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.