Yulia Ivanova
Impact in
- Immunology top 1%
- Immune cells in cancer
- Immune Cell Function and Interaction
- IL-33, ST2, and ILC Pathways
- Phagocytosis and Immune Regulation
- Immune Response and Inflammation
- Biological Psychiatry top 5%
Papers in
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- Single-cell and spatial transcriptomics 1
- Sphingolipid Metabolism and Signaling 1
- Plant biochemistry and biosynthesis 1
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- IL-33, ST2, and ILC Pathways 1
- Reproductive System and Pregnancy 1
- Co-authors
- Maxim N. Artyomov (4 shared papers)Bart Everts (2 shared papers)Stanley Ching‐Cheng Huang (2 shared papers)Edward J. Pearce (2 shared papers)Ekaterina Loginicheva (1 shared paper)Vicky Lampropoulou (1 shared paper)Kelly M. Stewart (1 shared paper)Alexey Sergushichev (1 shared paper)
- Journals
- Nature Immunology (1 paper)eLife (1 paper)Organic Letters (1 paper)Science (1 paper)Immunity (1 paper)
- Partner nations
- United StatesChinaRussia
In The Last Decade
Yulia Ivanova
5 papers receiving 3.2k citations
Yulia Ivanova's Hit Papers
Peers
Comparison fields: 5 of 109
- Immunology 2.0k
- Biological Psychiatry 68
- Cancer Research 406
- Neurology 180
- Molecular Biology 1.2k
Countries citing papers authored by Yulia Ivanova
This map shows the geographic impact of Yulia Ivanova'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 Yulia Ivanova with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yulia Ivanova more than expected).
Fields of papers citing papers by Yulia Ivanova
This network shows the impact of papers produced by Yulia Ivanova. 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 Yulia Ivanova. The network helps show where Yulia Ivanova may publish in the future.
Co-authors
The 25 scholars most cited alongside Yulia Ivanova, 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 | Network Integration of Parallel Metabolic and Transcriptional Data Reveals Metabolic Modules that Regulate Macrophage Polarization Hit paper breakdown → | 2015 | 1462 |
| 2 | Cell-intrinsic lysosomal lipolysis is essential for alternative activation of macrophages Hit paper breakdown → | 2014 | 897 |
| 3 | 2014 | 447 | |
| 4 | 2014 | 324 | |
| 5 | 2009 | 48 |
About Yulia Ivanova
Yulia Ivanova is a scholar working on Molecular Biology, Immunology, Infectious Diseases, Pharmacology and Epidemiology, having authored 5 papers that have together received 3.2k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (1 paper), Sphingolipid Metabolism and Signaling (1 paper), IL-33, ST2, and ILC Pathways (1 paper), Calcium signaling and nucleotide metabolism (1 paper), Microbial Natural Products and Biosynthesis (1 paper), Reproductive System and Pregnancy (1 paper), Clostridium difficile and Clostridium perfringens research (1 paper) and Plant biochemistry and biosynthesis (1 paper). The work is most often cited by research in Immunology (2.0k citations), Biological Psychiatry (68 citations), Cancer Research (406 citations), Neurology (180 citations) and Molecular Biology (1.2k citations). Yulia Ivanova has collaborated with scholars based in United States, China and Russia. Frequent co-authors include Maxim N. Artyomov, Bart Everts, Stanley Ching‐Cheng Huang, Edward J. Pearce, Ekaterina Loginicheva, Vicky Lampropoulou, Kelly M. Stewart, Alexey Sergushichev, Abhishek Jha and Edward M. Driggers. Their work appears in journals such as Nature Immunology, eLife, Organic Letters, Science and Immunity.
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.