Anna V. Ivshina
- Molecular Biology top 10%
- Cancer Research top 5%
- Oncology top 10%
- Infectious Diseases top 10%
- Genetics
- Co-authors
- Vladimir A. KuznetsovO. V. Sen’koLance D. MillerThomas Choudary PuttiJoshy GeorgePer HallEdison T. LiuJohn E.L. Wong
- Topics
- Gene expression and cancer classification (6 papers)Bioinformatics and Genomic Networks (5 papers)Cancer-related molecular mechanisms research (4 papers)
- Partner nations
- SingaporeUnited StatesJapan
In The Last Decade
Anna V. Ivshina
23 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Molecular Biology 748
- Cancer Research 364
- Oncology 233
- Infectious Diseases 122
- Genetics 112
Countries citing papers authored by Anna V. Ivshina
This map shows the geographic impact of Anna V. Ivshina'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 Anna V. Ivshina with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anna V. Ivshina more than expected).
Fields of papers citing papers by Anna V. Ivshina
This network shows the impact of papers produced by Anna V. Ivshina. 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 Anna V. Ivshina. The network helps show where Anna V. Ivshina may publish in the future.
Co-authorship network of co-authors of Anna V. Ivshina
This figure shows the co-authorship network connecting the top 25 collaborators of Anna V. Ivshina. A scholar is included among the top collaborators of Anna V. Ivshina 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 Anna V. Ivshina. Anna V. Ivshina is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 18 | |
| 3 | 55 | |
| 4 | 26 | |
| 5 | 19 | |
| 6 | 19 | |
| 7 | 21 | |
| 8 | 60 | |
| 9 | 44 | |
| 10 | 2 | |
| 11 | Genetic Reclassification of Histologic Grade Delineates New Clinical Subtypes of Breast Cancerbreakdown → | 543 |
| 12 | Statistically Weighted Voting Analysis of Microarrays for Molecular Pattern Selection and Discovery Cancer Genotypes | 9 |
| 13 | 33 | |
| 14 | 19 | |
| 15 | 128 | |
| 16 | 2 | |
| 17 | Inactivated vaccines based on alternatives to wild-type seed virus. | 7 |
| 18 | 39 | |
| 19 | Prognosis of intravesical bacillus Calmette-Guerin therapy for superficial bladder cancer by immunological urinary measurements: statistically weighted syndrome analysis. | 42 |
| 20 | 37 |
About Anna V. Ivshina
Anna V. Ivshina is a scholar working on Cancer Research, Modeling and Simulation and Molecular Biology, having authored 23 papers that have together received 1.2k indexed citations. Recurring topics across this work include Gene expression and cancer classification (6 papers), Bioinformatics and Genomic Networks (5 papers) and Cancer-related molecular mechanisms research (4 papers). The work is most often cited by research in Cancer Research (364 citations), Molecular Biology (748 citations) and Oncology (233 citations). Anna V. Ivshina has collaborated with scholars based in Singapore, United States and Japan. Frequent co-authors include Vladimir A. Kuznetsov, O. V. Sen’ko, Lance D. Miller, Thomas Choudary Putti, Joshy George, Per Hall, Edison T. Liu, John E.L. Wong, Jonas Bergh and Johanna Smeds. Their work appears in journals such as Proceedings of the National Academy of Sciences, Cancer Research and Scientific Reports.
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.