Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Ink4a/Arf expression is a biomarker of aging
20041.2k citationsJanakiraman Krishnamurthy, Chad Torrice et al.Journal of Clinical Investigationprofile →
A Humanized Mouse Model to Study Hepatitis C Virus Infection, Immune Response, and Liver Disease
2011220 citationsMichael L. Washburn, Moses T. Bility et al.Gastroenterologyprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Kovalev Gi'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 Kovalev Gi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kovalev Gi more than expected).
This network shows the impact of papers produced by Kovalev Gi. 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 Kovalev Gi. The network helps show where Kovalev Gi may publish in the future.
Co-authorship network of co-authors of Kovalev Gi
This figure shows the co-authorship network connecting the top 25 collaborators of Kovalev Gi.
A scholar is included among the top collaborators of Kovalev Gi 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 Kovalev Gi. Kovalev Gi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Washburn, Michael L., Moses T. Bility, Liguo Zhang, et al.. (2011). A Humanized Mouse Model to Study Hepatitis C Virus Infection, Immune Response, and Liver Disease. Gastroenterology. 140(4). 1334–1344.220 indexed citations breakdown →
6.
Zhang, Liguo, et al.. (2011). Efficient infection, activation, and impairment of pDCs in the BM and peripheral lymphoid organs during early HIV-1 infection in humanized rag2(-/-)gamma C-/- mice in vivo. 117(23).14 indexed citations
Krishnamurthy, Janakiraman, Chad Torrice, Matthew R. Ramsey, et al.. (2004). Ink4a/Arf expression is a biomarker of aging. Journal of Clinical Investigation. 114(9). 1299–1307.1167 indexed citations breakdown →
12.
Krishnamurthy, Janakiraman, Chad Torrice, Matthew R. Ramsey, et al.. (2004). Ink4a/Arf expression is a biomarker of aging. Journal of Clinical Investigation. 114(9). 1299–1307.105 indexed citations
Gi, Kovalev, et al.. (2000). [Strain-specific response in mice to the neonatal administration of ACTH(4-10) fragment: behavior, neurochemistry, and brain morphology].. PubMed. 36(11). 1507–14.6 indexed citations
16.
Gi, Kovalev, et al.. (1993). [The sodium oxybutyrate and nooglutil correction of dopamine release in the striatum of prenatally alcoholized rat pups].. PubMed. 116(7). 56–8.4 indexed citations
17.
Gi, Kovalev, et al.. (1993). [The nooglutil correction of functional disorders of the central nervous system caused by prenatal alcoholization in rats].. PubMed. 55(1). 18–21.2 indexed citations
18.
Gi, Kovalev, et al.. (1991). [Peripheral blood of children exposed to radiation as a consequence of the Chernobyl AES accident].. PubMed. 21–6.1 indexed citations
19.
Gi, Kovalev, et al.. (1990). [Immunophenotype of peripheral blood lymphocytes in children living in radiation-polluted territories].. PubMed. 42–7.1 indexed citations
20.
Gi, Kovalev, et al.. (1988). Modulatory effect of neurotransmitters and neurotropic drugs on the release of 3H-D-aspartic acid from synaptosomes.. PubMed. 24(3). 383–8.
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.