Ruby Wasti

2.2k citations
2 papers · 1.3k · 1 hit paper · h-index 2

Impact in

  • Immunology top 5%
    • Immune cells in cancer
    • Immune Cell Function and Interaction
    • Immunotherapy and Immune Responses
    • T-cell and B-cell Immunology
  • Oncology top 5%
    • Cancer Immunotherapy and Biomarkers
    • CAR-T cell therapy research

Papers in

    • Microbial metabolism and enzyme function 1
    • Single-cell and spatial transcriptomics 1
    • Coagulation, Bradykinin, Polyphosphates, and Angioedema 1

Ruby Wasti

2 papers receiving 1.3k citations

Ruby Wasti's Hit Papers

Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment 2018 · 1.3k citations
1.3k0+2+5Years since publication4008001.2k

Peers

Ruby Wasti
Comparison fields: 5 of 73
  • Immunology 652
  • Oncology 548
  • Cancer Research 249
  • Molecular Biology 629
  • Biophysics 42
Replace Phuong Dao with:
Phuong Dao United States
Zemin Zhang China
Ayse Bassez Belgium
Daphne Tsoucas United States
Hye Hyeon Eum South Korea
Woosung Chung South Korea
Reuben Moncada United States
Ruben Bill Switzerland
Anuja Sathe United States
John Lövrot Sweden
Ruby Wasti relative to Phuong Dao United States Phuong Dao's profile →
Citations per field
00.5×1.5×
Phuong Dao · 1×
Citations per year

Countries citing papers authored by Ruby Wasti

Since Specialization
Citations

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

Fields of papers citing papers by Ruby Wasti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Ruby Wasti, 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 Ruby Wasti Line = papers co-authored together Ruby Wasti links everyone, so they are left out of the graph.

All Works

2 of 2 papers shown
#Work
1
Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment
Hit paper breakdown →
20181299
2
The oxidase activity of vascular adhesion protein-1 (VAP-1) is essential for function.
201324

About Ruby Wasti

Ruby Wasti is a scholar working on Molecular Biology, Genetics, Biochemistry, Immunology and Infectious Diseases, having authored 2 papers that have together received 1.3k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (1 paper), Coagulation, Bradykinin, Polyphosphates, and Angioedema (1 paper), Microbial metabolism and enzyme function (1 paper), Immune cells in cancer (1 paper), Single-cell and spatial transcriptomics (1 paper) and Biochemical Acid Research Studies (1 paper). The work is most often cited by research in Immunology (652 citations), Oncology (548 citations), Cancer Research (249 citations), Molecular Biology (629 citations) and Biophysics (42 citations). Ruby Wasti has collaborated with scholars based in Lithuania, Japan and United States. Frequent co-authors include Peter T. McKenney, Juozas Nainys, Ambrose Carr, Andrew Cornish, Elham Azizi, Krishna Kadaveru, Kristy Choi, Alexander Y. Rudensky, Sandhya Prabhakaran and Linas Mažutis. Their work appears in journals such as Cell and PubMed.

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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