Hyunmin Kim

725 citations
10 papers · 401 indexed · h-index 8
Topics
Estrogen and related hormone effects (2 papers)Computational Drug Discovery Methods (2 papers)Immune cells in cancer (2 papers)

In The Last Decade

Hyunmin Kim

10 papers receiving 400 citations

Peers

Hyunmin Kim
Comparison fields: 5 of 69
  • Molecular Biology 294
  • Hematology 91
  • Epidemiology 87
  • Cancer Research 79
  • Plant Science 52
Replace Sai Mukund Ramakrishnan with:
Sai Mukund Ramakrishnan United States
Ui‐Hyun Park South Korea
Hua Yan China
Xiwen Cheng United States
J.R. Mertz United States
Caixia Li China
Chao Guo China
Liz J. Hernández Borrero United States
Chi Dug Kang South Korea
Hyunmin Kim relative to Sai Mukund Ramakrishnan United States Sai Mukund Ramakrishnan's profile →
Citations per field
00.5×2.7×
Sai Mukund Ramakrishnan · 1×
Citations per year

Countries citing papers authored by Hyunmin Kim

Since Specialization
Citations

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

Fields of papers citing papers by Hyunmin Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hyunmin Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Hyunmin Kim. A scholar is included among the top collaborators of Hyunmin Kim 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 Hyunmin Kim. Hyunmin Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
#WorkIndexed citations
1 1
2 11
3 10
4 23
5 65
6 28
7 198
8 10
9 50
10
Concept Recognition, Information Retrieval, and Machine Learning in Genomics Question-Answering
5

About Hyunmin Kim

Hyunmin Kim is a scholar working on Endocrine and Autonomic Systems, Computational Theory and Mathematics and Endocrinology, Diabetes and Metabolism, having authored 10 papers that have together received 401 indexed citations. Recurring topics across this work include Estrogen and related hormone effects (2 papers), Computational Drug Discovery Methods (2 papers) and Immune cells in cancer (2 papers). The work is most often cited by research in Hematology (91 citations), Cancer Research (79 citations) and Molecular Biology (294 citations). Hyunmin Kim has collaborated with scholars based in United States, South Korea and Germany. Frequent co-authors include Aik Choon Tan, Mohammad Minhajuddin, Clayton A. Smith, Jeremy N. Rich, Jason R. Myers, Craig T. Jordan, Brett M. Stevens, Daniel A. Pollyea, Anagha Inguva Sheth and Shanshan Pei. Their work appears in journals such as Clinical Cancer Research, Cell stem cell and Journal of Experimental Botany.

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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