Grace Kago

682 citations
10 papers · 423 · h-index 8

Impact in

  • Cell Biology top 10%
    • Cellular transport and secretion
    • Endoplasmic Reticulum Stress and Disease
    • Ubiquitin and proteasome pathways
    • Lipid Membrane Structure and Behavior
    • RNA Research and Splicing
    • Protein Degradation and Inhibitors
    • RNA and protein synthesis mechanisms

Papers in

    • Ubiquitin and proteasome pathways 3
    • Protein Degradation and Inhibitors 2
    • Lipid Membrane Structure and Behavior 2
    • Endoplasmic Reticulum Stress and Disease 2
    • Cellular transport and secretion 2

Grace Kago

10 papers receiving 420 citations

Peers

Grace Kago
Comparison fields: 5 of 71
  • Cell Biology 175
  • Molecular Biology 363
  • Biochemistry 19
  • Epidemiology 73
  • Oncology 43
Replace Steven J. Kaczowka with:
Steven J. Kaczowka United States
Valentina Cecatiello Italy
Ian Yu United States
Kai‐En Chen Australia
Chris MacDonald United States
Marc Gouw Germany
Xavier Pinson France
Liv Jensen United States
Walter Stelzer Germany
Rosemarie Ungricht Switzerland
Grace Kago relative to Steven J. Kaczowka United States Steven J. Kaczowka's profile →
Citations per field
00.5×10×13×
Steven J. Kaczowka · 1×
Citations per year

Countries citing papers authored by Grace Kago

Since Specialization
Citations

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

Fields of papers citing papers by Grace Kago

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Grace Kago, 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 Grace Kago Line = papers co-authored together Grace Kago links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 2021116
2 201591
3 201862
4 201654
5 201653
6 201320
7 201411
8 20228
9 20217
10 20231

About Grace Kago

Grace Kago is a scholar working on Molecular Biology, Cell Biology, Genetics, Epidemiology and Infectious Diseases, having authored 10 papers that have together received 423 indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (3 papers), Endoplasmic Reticulum Stress and Disease (2 papers), Protein Degradation and Inhibitors (2 papers), Lipid Membrane Structure and Behavior (2 papers), Cellular transport and secretion (2 papers), Bacterial Genetics and Biotechnology (2 papers), Folate and B Vitamins Research (1 paper) and Language and cultural evolution (1 paper). The work is most often cited by research in Cell Biology (175 citations), Molecular Biology (363 citations), Biochemistry (19 citations), Epidemiology (73 citations) and Oncology (43 citations). Grace Kago has collaborated with scholars based in United States, Japan and United Kingdom. Frequent co-authors include Andreas Matouschek, Houqing Yu, Jeanne C. Stachowiak, Jörg Richter, Eileen M. Lafer, Kasey J. Day, Liping Wang, Carl C. Hayden, M. Madan Babu and Tomonao Inobe. Their work appears in journals such as European Journal of Medicinal Chemistry, Journal of Biological Chemistry, Nature Structural & Molecular Biology, PLoS ONE and Frontiers in Communication.

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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