Lubna Patrawala
- Molecular Biology top 2%
- Cancer Research top 0.5%
- Oncology top 1%
- Pulmonary and Respiratory Medicine top 5%
- Immunology top 10%
- Co-authors
- Dean G. TangRobin Schneider‐BroussardAndreas G. BaderJason F. WigginsKent ClaypoolKevin KelnarTammy Calhoun‐DavisCollene Jeter
- Topics
- Cancer Cells and Metastasis (8 papers)RNA Interference and Gene Delivery (4 papers)MicroRNA in disease regulation (4 papers)
- Partner nations
- United StatesJapan
In The Last Decade
Lubna Patrawala
12 papers receiving 4.7k citations
Hit Papers
Peers
Comparison fields: 5 of 101
- Molecular Biology 3.5k
- Cancer Research 2.6k
- Oncology 2.1k
- Pulmonary and Respiratory Medicine 732
- Immunology 333
Countries citing papers authored by Lubna Patrawala
This map shows the geographic impact of Lubna Patrawala'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 Lubna Patrawala with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lubna Patrawala more than expected).
Fields of papers citing papers by Lubna Patrawala
This network shows the impact of papers produced by Lubna Patrawala. 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 Lubna Patrawala. The network helps show where Lubna Patrawala may publish in the future.
Co-authorship network of co-authors of Lubna Patrawala
This figure shows the co-authorship network connecting the top 25 collaborators of Lubna Patrawala. A scholar is included among the top collaborators of Lubna Patrawala 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 Lubna Patrawala. Lubna Patrawala is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | The microRNA miR-34a inhibits prostate cancer stem cells and metastasis by directly repressing CD44breakdown → | 1136 |
| 2 | Development of a Lung Cancer Therapeutic Based on the Tumor Suppressor MicroRNA-34breakdown → | 532 |
| 3 | 30 | |
| 4 | 340 | |
| 5 | 280 | |
| 6 | 484 | |
| 7 | 31 | |
| 8 | 279 | |
| 9 | 38 | |
| 10 | 178 | |
| 11 | Highly purified CD44+ prostate cancer cells from xenograft human tumors are enriched in tumorigenic and metastatic progenitor cellsbreakdown → | 770 |
| 12 | Side Population Is Enriched in Tumorigenic, Stem-Like Cancer Cells, whereas ABCG2+ and ABCG2− Cancer Cells Are Similarly Tumorigenicbreakdown → | 737 |
About Lubna Patrawala
Lubna Patrawala is a scholar working on Cancer Research, Oncology and Immunology, having authored 12 papers that have together received 4.8k indexed citations. Recurring topics across this work include Cancer Cells and Metastasis (8 papers), RNA Interference and Gene Delivery (4 papers) and MicroRNA in disease regulation (4 papers). The work is most often cited by research in Cancer Research (2.6k citations), Oncology (2.1k citations) and Molecular Biology (3.5k citations). Lubna Patrawala has collaborated with scholars based in United States and Japan. Frequent co-authors include Dean G. Tang, Robin Schneider‐Broussard, Andreas G. Bader, Jason F. Wiggins, Kent Claypool, Kevin Kelnar, Tammy Calhoun‐Davis, Collene Jeter, Jianjun Zhou and David Brown. Their work appears in journals such as Journal of Biological Chemistry, Nature Medicine and Cancer 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.