Taemook Kim

541 total citations
12 papers, 351 citations indexed

About

Taemook Kim is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Taemook Kim has authored 12 papers receiving a total of 351 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 3 papers in Cancer Research and 2 papers in Oncology. Recurrent topics in Taemook Kim's work include Genomics and Chromatin Dynamics (5 papers), RNA modifications and cancer (3 papers) and Genomics and Phylogenetic Studies (3 papers). Taemook Kim is often cited by papers focused on Genomics and Chromatin Dynamics (5 papers), RNA modifications and cancer (3 papers) and Genomics and Phylogenetic Studies (3 papers). Taemook Kim collaborates with scholars based in South Korea, United States and Austria. Taemook Kim's co-authors include Keunsoo Kang, Kyung Hyun Yoo, Daeyoup Lee, Lothar Hennighausen, Young Kim, Choong‐Gu Lee, Jong Hee Nam, Dipayan Rudra, Sin‐Hyeog Im and Ho‐Keun Kwon and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Molecular and Cellular Biology.

In The Last Decade

Taemook Kim

12 papers receiving 347 citations

Peers

Taemook Kim

MB

CR

ONCOL

PRM

GENET

Xu Zhu China

Joana Apolónio Portugal

Keun Young Kim South Korea

Lucía C. Leal-Esteban Switzerland

Jia Shusheng China

Qilian Yang China

Hae Rim Jung South Korea

Sang Hyun Song South Korea

Athanasios Pagkalos Greece

Xu Zhu China

Taemook Kim

195 ×0.8

MB

110 ×1.2

CR

42 ×0.8

ONCOL

45 ×1.2

PRM

35 ×0.9

GENET

Citations per year, relative to Taemook Kim Taemook Kim (= 1×) peers Xu Zhu

Countries citing papers authored by Taemook Kim

Since Specialization

Citations

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

Fields of papers citing papers by Taemook Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Taemook Kim

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

All Works

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12 of 12 papers shown

1.

Kim, Taemook, Sungwook Han, Yujin Chun, et al.. (2022). Comparative characterization of 3D chromatin organization in triple-negative breast cancers. Experimental & Molecular Medicine. 54(5). 585–600. 18 indexed citations

2.

Han, Sungwook, et al.. (2021). The chromatin remodeler Ino80 mediates RNAPII pausing site determination. Genome biology. 22(1). 294–294. 8 indexed citations

3.

Kim, Taemook, et al.. (2021). A compendium of chromatin contact maps reflecting regulation by chromatin remodelers in budding yeast. Nature Communications. 12(1). 6380–6380. 7 indexed citations

4.

Kim, Gi-Cheon, Choong‐Gu Lee, Ravi Verma, et al.. (2020). ETS1 Suppresses Tumorigenesis of Human Breast Cancer via Trans-Activation of Canonical Tumor Suppressor Genes. Frontiers in Oncology. 10. 642–642. 16 indexed citations

5.

Lee, Choong‐Gu, Ho‐Keun Kwon, Hye-Ji Kang, et al.. (2019). Ets1 suppresses atopic dermatitis by suppressing pathogenic T cell responses. JCI Insight. 4(5). 12 indexed citations

6.

Mun, Seyoung, Taemook Kim, Kang-Hoon Lee, et al.. (2019). Transposable element-mediated structural variation analysis in dog breeds using whole-genome sequencing. Mammalian Genome. 30(9-10). 289–300. 10 indexed citations

7.

Kim, Gi-Cheon, Ho‐Keun Kwon, Choong‐Gu Lee, et al.. (2018). Upregulation of Ets1 expression by NFATc2 and NFKB1/RELA promotes breast cancer cell invasiveness. Oncogenesis. 7(11). 91–91. 43 indexed citations

8.

Kim, Taemook, et al.. (2018). Octopus-toolkit: a workflow to automate mining of public epigenomic and transcriptomic next-generation sequencing data. Nucleic Acids Research. 46(9). e53–e53. 46 indexed citations

9.

Shen, Qingyu, Jung Woo Eun, Kyoung Bun Lee, et al.. (2017). Barrier to autointegration factor 1, procollagen‐lysine, 2‐oxoglutarate 5‐dioxygenase 3, and splicing factor 3b subunit 4 as early‐stage cancer decision markers and drivers of hepatocellular carcinoma. Hepatology. 67(4). 1360–1377. 89 indexed citations

10.

Kim, Taemook, et al.. (2017). The T47D cell line is an ideal experimental model to elucidate the progesterone-specific effects of a luminal A subtype of breast cancer. Biochemical and Biophysical Research Communications. 486(3). 752–758. 73 indexed citations

11.

Sakamoto, Kazuhito, Kyung Hyun Yoo, Taemook Kim, et al.. (2016). Janus Kinase 1 Is Essential for Inflammatory Cytokine Signaling and Mammary Gland Remodeling. Molecular and Cellular Biology. 36(11). 1673–1690. 28 indexed citations

12.

Kim, Taemook, Wooseok Lee, Kyudong Han, & Keunsoo Kang. (2014). An automated analysis pipeline for a large set of ChIP-seq data: AutoChIP. Genes & Genomics. 37(3). 305–311. 1 indexed citations

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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