Kitai Kim

5.5k citations
72 papers · 4.0k · 2 hit papers · h-index 26

Impact in

Papers in

    • Pluripotent Stem Cells Research 16
    • CRISPR and Genetic Engineering 10
    • Renal and related cancers 10
    • Epigenetics and DNA Methylation 5

Kitai Kim

70 papers receiving 3.9k citations

Kitai Kim's Hit Papers

Comprehensive methylome map of lineage commitment from haematopoietic progenitors 2010 · 467 citations
4670+7+15Years since publication200400600

Peers

Kitai Kim
Comparison fields: 5 of 161
  • Molecular Biology 2.5k
  • Reproductive Medicine 186
  • Oncology 576
  • Genetics 196
  • Genetics 466
Replace Theodore R. Oegema with:
Theodore R. Oegema United States
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MH Sham Hong Kong
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Kitai Kim relative to Theodore R. Oegema United States Theodore R. Oegema's profile →
Citations per field
00.5×1.5×
Theodore R. Oegema · 1×
Citations per year

Countries citing papers authored by Kitai Kim

Since Specialization
Citations

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

Fields of papers citing papers by Kitai Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 72 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Derivation of embryonic germ cells and male gametes from embryonic stem cells
Hit paper breakdown →
2003638
2
Comprehensive methylome map of lineage commitment from haematopoietic progenitors
Hit paper breakdown →
2010467
3 2011457
4 2009444
5 2009294
6 1995231
7 2006152
8 2008133
9 2003117
10 2007100
11 199566
12 201466
13 201957
14 200843
15 201438
16 200238
17 199837
18 199536
19 200236
20 201735

About Kitai Kim

Kitai Kim is a scholar working on Molecular Biology, Epidemiology, Oncology, Public Health, Environmental and Occupational Health and Cancer Research, having authored 72 papers that have together received 4.0k indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (16 papers), CRISPR and Genetic Engineering (10 papers), Renal and related cancers (10 papers), Pancreatic and Hepatic Oncology Research (7 papers), Reproductive Biology and Fertility (6 papers), Electrospun Nanofibers in Biomedical Applications (5 papers), Epigenetics and DNA Methylation (5 papers) and Cancer Genomics and Diagnostics (4 papers). The work is most often cited by research in Molecular Biology (2.5k citations), Reproductive Medicine (186 citations), Oncology (576 citations), Genetics (196 citations) and Genetics (466 citations). Kitai Kim has collaborated with scholars based in United States, South Korea and United Kingdom. Frequent co-authors include George Q. Daley, Niels Geijsen, Kevin Eggan, Joost Gribnau, Hongguang Huo, Yuin‐Han Loh, John M. Howard, Don R. Domenico, Andrew P. Feinberg and Martin J. Aryee. Their work appears in journals such as Fibers and Polymers, Diagnostic Cytopathology, Stem Cell Reports, Journal of Virology and Surgery.

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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