Gina L. Costa
- Immunology top 0.5%
- Immunotherapy and Immune Responses 3
- T-cell and B-cell Immunology 3
- Oncology top 5%
- CAR-T cell therapy research 3
- Molecular Biology top 5%
- Molecular Biology Techniques and Applications 4
- CRISPR and Genetic Engineering 3
- RNA Interference and Gene Delivery 3
- Immunology and Allergy top 5%
- Genetics top 5%
- Virus-based gene therapy research 3
- Animal Genetics and Reproduction 2
- Co-authors
- C. Garrison FathmanSean KimSusanne J. SzaboXiankui ZhangLaurie H. GlimcherMichael P. WeinerJohn C. BauerEric J. Mathur
- Cited by
- ImmunologyOncologyMolecular Biology
- Partner nations
- United StatesIsrael
In The Last Decade
Gina L. Costa
16 papers receiving 4.2k citations
Hit Papers
Peers
Comparison fields: 5 of 128
- Immunology 2.5k
- Oncology 678
- Molecular Biology 1.4k
- Immunology and Allergy 109
- Genetics 465
Countries citing papers authored by Gina L. Costa
This map shows the geographic impact of Gina L. Costa'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 Gina L. Costa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gina L. Costa more than expected).
Fields of papers citing papers by Gina L. Costa
This network shows the impact of papers produced by Gina L. Costa. 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 Gina L. Costa. The network helps show where Gina L. Costa may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Gina L. Costa, 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 | 2025 | 3 | |
| 2 | 2023 | 1 | |
| 3 | 2015 | 7 | |
| 4 | Pillars article: A novel transcription factor, T-bet, directs Th1 lineage commitment. Cell. 2000. 100: 655-669. | 2015 | 24 |
| 5 | 2013 | 174 | |
| 6 | 2008 | 413 | |
| 7 | 2006 | 6 | |
| 8 | 2006 | 4 | |
| 9 | 2003 | 30 | |
| 10 | 2001 | 145 | |
| 11 | 2001 | 154 | |
| 12 | 2000 | 5 | |
| 13 | A Novel Transcription Factor, T-bet, Directs Th1 Lineage Commitmentbreakdown → | 2000 | 2819 |
| 14 | 2000 | 91 | |
| 15 | 1994 | 418 | |
| 16 | 1994 | 31 |
About Gina L. Costa
Gina L. Costa is a scholar working on Immunology, Genetics and Oncology, having authored 16 papers that have together received 4.3k indexed citations. Recurring topics across this work include Molecular Biology Techniques and Applications (4 papers), Virus-based gene therapy research (3 papers), CRISPR and Genetic Engineering (3 papers), CAR-T cell therapy research (3 papers), Immunotherapy and Immune Responses (3 papers), RNA Interference and Gene Delivery (3 papers), T-cell and B-cell Immunology (3 papers) and Animal Genetics and Reproduction (2 papers). The work is most often cited by research in Immunology (2.5k citations), Oncology (678 citations) and Molecular Biology (1.4k citations). Gina L. Costa has collaborated with scholars based in United States and Israel. Frequent co-authors include C. Garrison Fathman, Sean Kim, Susanne J. Szabo, Xiankui Zhang, Laurie H. Glimcher, Michael P. Weiner, John C. Bauer, Eric J. Mathur, Christine M. Seroogy and Atsuo Nakajima. Their work appears in journals such as The Journal of Immunology, Cold Spring Harbor Protocols, Gene, Journal of Surgical Oncology and Genome 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.