Joanna Kitlińska
- Cellular and Molecular Neuroscience top 2%
- Molecular Biology
- Physiology top 10%
- Psychiatry and Mental health top 5%
- Oncology top 10%
- Co-authors
- Jason U. TilanZofia ŻukowskaEdward LeeLydia E. KuoLijun LiRichard KvětňanskýJennifer PonsMary Susan Burnett
- Topics
- Neuropeptides and Animal Physiology (27 papers)Neuroblastoma Research and Treatments (13 papers)Cancer, Stress, Anesthesia, and Immune Response (13 papers)
- Partner nations
- United StatesPolandSweden
In The Last Decade
Joanna Kitlińska
49 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 117
- Cellular and Molecular Neuroscience 785
- Molecular Biology 499
- Physiology 340
- Psychiatry and Mental health 331
- Oncology 325
Countries citing papers authored by Joanna Kitlińska
This map shows the geographic impact of Joanna Kitlińska'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 Kitlińska with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joanna Kitlińska more than expected).
Fields of papers citing papers by Joanna Kitlińska
This network shows the impact of papers produced by Joanna Kitlińska. 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 Kitlińska. The network helps show where Joanna Kitlińska may publish in the future.
Co-authorship network of co-authors of Joanna Kitlińska
This figure shows the co-authorship network connecting the top 25 collaborators of Joanna Kitlińska. A scholar is included among the top collaborators of Joanna Kitlińska 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 Kitlińska. Joanna Kitlińska is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 0 | |
| 3 | 6 | |
| 4 | 28 | |
| 5 | 15 | |
| 6 | 5 | |
| 7 | 2 | |
| 8 | 17 | |
| 9 | 29 | |
| 10 | 22 | |
| 11 | 35 | |
| 12 | 121 | |
| 13 | 16 | |
| 14 | 13 | |
| 15 | 2 | |
| 16 | 20 | |
| 17 | 155 | |
| 18 | 62 | |
| 19 | The influence of OLA-DRB1 (MHC class II) gene polymorphism on lamb body weight and weight gain in Polish Heath Sheep | 8 |
| 20 | 3 |
About Joanna Kitlińska
Joanna Kitlińska is a scholar working on Cellular and Molecular Neuroscience, Psychiatry and Mental health and Neurology, having authored 50 papers that have together received 1.8k indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (27 papers), Neuroblastoma Research and Treatments (13 papers) and Cancer, Stress, Anesthesia, and Immune Response (13 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (785 citations), Endocrine and Autonomic Systems (285 citations) and Behavioral Neuroscience (141 citations). Joanna Kitlińska has collaborated with scholars based in United States, Poland and Sweden. Frequent co-authors include Jason U. Tilan, Zofia Żukowska, Edward Lee, Lydia E. Kuo, Lijun Li, Richard Květňanský, Jennifer Pons, Mary Susan Burnett, Michael D. Johnson and Stephen B. Baker. Their work appears in journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and Nature Medicine.
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.