Vijay Baichwal
- Molecular Biology top 5%
- Immunology top 2%
- Oncology top 2%
- Cancer Research top 1%
- Pathology and Forensic Medicine top 5%
- Co-authors
- Bill SugdenPatrick A. BaeuerleHailing HsuJianing HuangHong-Bing ShuDavid V. GoeddelUlrike SchindlerRobert Tjian
- Topics
- NF-κB Signaling Pathways (8 papers)Immune Response and Inflammation (6 papers)Cell Adhesion Molecules Research (6 papers)
- Cited by
- Cancer ResearchImmunologyOncology
- Partner nations
- United StatesAustriaGermany
In The Last Decade
Vijay Baichwal
41 papers receiving 3.8k citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Molecular Biology 1.9k
- Immunology 1.4k
- Oncology 1.1k
- Cancer Research 1.1k
- Pathology and Forensic Medicine 383
Countries citing papers authored by Vijay Baichwal
This map shows the geographic impact of Vijay Baichwal'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 Vijay Baichwal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vijay Baichwal more than expected).
Fields of papers citing papers by Vijay Baichwal
This network shows the impact of papers produced by Vijay Baichwal. 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 Vijay Baichwal. The network helps show where Vijay Baichwal may publish in the future.
Co-authorship network of co-authors of Vijay Baichwal
This figure shows the co-authorship network connecting the top 25 collaborators of Vijay Baichwal. A scholar is included among the top collaborators of Vijay Baichwal 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 Vijay Baichwal. Vijay Baichwal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 44 | |
| 2 | 1 | |
| 3 | 56 | |
| 4 | Abstract #LB-204: MPI-0479605: A novel small molecule inhibitor of the mitotic kinase TTK with anti-tumor activity in pre-clinical models | 1 |
| 5 | 18 | |
| 6 | 110 | |
| 7 | 484 | |
| 8 | 63 | |
| 9 | TNF-Dependent Recruitment of the Protein Kinase RIP to the TNF Receptor-1 Signaling Complexbreakdown → | 966 |
| 10 | 108 | |
| 11 | 11 | |
| 12 | 65 | |
| 13 | 1 | |
| 14 | 70 | |
| 15 | 76 | |
| 16 | 193 | |
| 17 | 7 | |
| 18 | 50 | |
| 19 | 87 | |
| 20 | 82 |
About Vijay Baichwal
Vijay Baichwal is a scholar working on Immunology and Allergy, Cancer Research and Oncology, having authored 43 papers that have together received 3.9k indexed citations. Recurring topics across this work include NF-κB Signaling Pathways (8 papers), Immune Response and Inflammation (6 papers) and Cell Adhesion Molecules Research (6 papers). The work is most often cited by research in Cancer Research (1.1k citations), Immunology (1.4k citations) and Oncology (1.1k citations). Vijay Baichwal has collaborated with scholars based in United States, Austria and Germany. Frequent co-authors include Bill Sugden, Patrick A. Baeuerle, Hailing Hsu, Jianing Huang, Hong-Bing Shu, David V. Goeddel, Ulrike Schindler, Robert Tjian, Adam Park and Jinzhao Hou. Their work appears in journals such as Nature, Cell and Proceedings of the National Academy of Sciences.
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.