Ayana Sawai

4.3k citations
10 papers · 3.3k indexed · 3 hit papers · h-index 9

Ayana Sawai

10 papers receiving 3.2k citations

Hit Papers

PCGF Homologs, CBX Proteins, and RYBP Define Functionally...64620052026201220192505007501000

Peers

Ayana Sawai
Comparison fields: 5 of 95
  • Oncology 1.1k
  • Molecular Biology 2.7k
  • Cancer Research 335
  • Pathology and Forensic Medicine 354
  • Computational Theory and Mathematics 276
Replace Piro Lito with:
Piro Lito United States
Ensar Halilovic United States
Kim H.T. Paraiso United States
Paul Wan United Kingdom
Sidong Huang Canada
Vanessa Rodrik-Outmezguine United States
Peter M. Haverty United States
Danan Li United States
Kimberly B. Dahlman United States
Nathalie Dhomen United Kingdom
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Citations per field
00.5×1.7×
Piro Lito · 1×
Citations per year

Countries citing papers authored by Ayana Sawai

Since Specialization
Citations

This map shows the geographic impact of Ayana Sawai'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 Ayana Sawai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ayana Sawai more than expected).

Fields of papers citing papers by Ayana Sawai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ayana Sawai. 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 Ayana Sawai. The network helps show where Ayana Sawai may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Ayana Sawai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ayana Sawai Line = papers co-authored together Ayana Sawai links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1
PCGF Homologs, CBX Proteins, and RYBP Define Functionally Distinct PRC1 Family Complexesbreakdown →
2012646
2
AKT Inhibition Relieves Feedback Suppression of Receptor Tyrosine Kinase Expression and Activitybreakdown →
2011746
3 20111
4 2008145
5 2008195
6 2008144
7 200786
8 200666
9 2005228
10
BRAF mutation predicts sensitivity to MEK inhibitionbreakdown →
20051013

About Ayana Sawai

Ayana Sawai is a scholar working on Molecular Biology, Pathology and Forensic Medicine and Immunology, having authored 10 papers that have together received 3.3k indexed citations. Recurring topics across this work include Heat shock proteins research (5 papers), PI3K/AKT/mTOR signaling in cancer (4 papers), Melanoma and MAPK Pathways (3 papers), Cancer Mechanisms and Therapy (2 papers), Cancer-related gene regulation (2 papers), Lung Cancer Treatments and Mutations (2 papers), Toxin Mechanisms and Immunotoxins (2 papers) and Protein Kinase Regulation and GTPase Signaling (1 paper). The work is most often cited by research in Oncology (1.1k citations), Molecular Biology (2.7k citations) and Cancer Research (335 citations). Ayana Sawai has collaborated with scholars based in United States, Canada and Spain. Frequent co-authors include Neal Rosen, David B. Solit, Sarat Chandarlapaty, Andrea Basso, William R. Sellers, Christine A. Pratilas, José Baselga, Olivera Grbovic-Huezo, Maurizio Scaltriti and Violeta Serra. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Molecular Cell.

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.

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