Daesong Yim

533 citations
10 papers · 435 · h-index 7

Impact in

  • Immunology top 10%
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology
    • Immunotherapy and Immune Responses
    • Immune cells in cancer
    • Immune Response and Inflammation
    • CAR-T cell therapy research
    • Cancer Immunotherapy and Biomarkers

Papers in

    • Immune Cell Function and Interaction 7
    • T-cell and B-cell Immunology 5
    • Immune Response and Inflammation 2
    • RNA Interference and Gene Delivery 2
    • RNA and protein synthesis mechanisms 1

Daesong Yim

10 papers receiving 425 citations

Peers

Daesong Yim
Comparison fields: 5 of 67
  • Immunology 299
  • Oncology 182
  • Cell Biology 51
  • Physiology 9
  • Hematology 20
Replace Kebria Hezaveh with:
Kebria Hezaveh Canada
Scott A. Wetzel United States
Jesper Kastrup Denmark
Olga Drize Israel
Daniela Carpani Italy
Xiaofang Xiong United States
Brandon Edwards United States
Koki Takeda Japan
Estela Famatiga United States
Lina Y. Dimberg Sweden
Daesong Yim relative to Kebria Hezaveh Canada Kebria Hezaveh's profile →
Citations per field
00.5×6.3×
Kebria Hezaveh · 1×
Citations per year

Countries citing papers authored by Daesong Yim

Since Specialization
Citations

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

Fields of papers citing papers by Daesong Yim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

10 of 10 papers shown
#Work
1 2007304
2
Immune defects in breast cancer patients after radiotherapy.
200847
3 200125
4 200617
5 200013
6 20029
7 20096
8 20015
9 20045
10 20044

About Daesong Yim

Daesong Yim is a scholar working on Immunology, Molecular Biology, Oncology, Radiology, Nuclear Medicine and Imaging and Animal Science and Zoology, having authored 10 papers that have together received 435 indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (7 papers), T-cell and B-cell Immunology (5 papers), Immune Response and Inflammation (2 papers), RNA Interference and Gene Delivery (2 papers), Cancer, Stress, Anesthesia, and Immune Response (1 paper), Animal Virus Infections Studies (1 paper), RNA and protein synthesis mechanisms (1 paper) and Endoplasmic Reticulum Stress and Disease (1 paper). The work is most often cited by research in Immunology (299 citations), Oncology (182 citations), Cell Biology (51 citations), Physiology (9 citations) and Hematology (20 citations). Daesong Yim has collaborated with scholars based in United States and Spain. Frequent co-authors include Segundo González, Roland K. Strong, Brett K. Kaiser, Zhenpeng Dai, I‐Ting Chow, Thomas A. Spies, H. Mann, Veronika Groh, Cynthia A. Wenner and Lewis L. Lanier. Their work appears in journals such as Immunogenetics, Nature, Cellular Immunology, Molecular Immunology and International Journal of Cancer.

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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