Taejeong Bae

5.0k total citations
23 papers, 649 citations indexed

About

Taejeong Bae is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Taejeong Bae has authored 23 papers receiving a total of 649 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 10 papers in Cancer Research and 5 papers in Genetics. Recurrent topics in Taejeong Bae's work include Cancer Genomics and Diagnostics (9 papers), Bioinformatics and Genomic Networks (7 papers) and Single-cell and spatial transcriptomics (5 papers). Taejeong Bae is often cited by papers focused on Cancer Genomics and Diagnostics (9 papers), Bioinformatics and Genomic Networks (7 papers) and Single-cell and spatial transcriptomics (5 papers). Taejeong Bae collaborates with scholars based in United States, South Korea and China. Taejeong Bae's co-authors include Alexej Abyzov, Yeongjun Jang, Flora M. Vaccarino, Livia Tomasini, Sung‐Hoon Kim, Bo Zhou, Alexander E. Urban, Kyoohyoung Rho, Jessica Mariani and Joong‐Won Lee and has published in prestigious journals such as Science, Nucleic Acids Research and PLoS ONE.

In The Last Decade

Taejeong Bae

22 papers receiving 643 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Taejeong Bae United States 11 498 179 130 82 65 23 649
Junmei Cairns United States 13 374 0.8× 133 0.7× 55 0.4× 50 0.6× 51 0.8× 28 604
Suzanne I. Specht United States 10 475 1.0× 101 0.6× 66 0.5× 40 0.5× 96 1.5× 11 609
Nora Rauch Ireland 10 426 0.9× 139 0.8× 33 0.3× 88 1.1× 50 0.8× 18 526
Andrew Olaharski United States 14 354 0.7× 155 0.9× 52 0.4× 54 0.7× 113 1.7× 21 642
Rochelle F. McAdam Canada 2 777 1.6× 86 0.5× 70 0.5× 145 1.8× 83 1.3× 2 935
Gregory Ryslik United States 7 556 1.1× 226 1.3× 91 0.7× 80 1.0× 19 0.3× 8 664
Raphaela Fritsche‐Guenther Germany 11 423 0.8× 90 0.5× 33 0.3× 51 0.6× 64 1.0× 27 580
Silvia Senese United States 15 758 1.5× 69 0.4× 88 0.7× 80 1.0× 150 2.3× 22 922
Kayo Yamada United Kingdom 12 652 1.3× 223 1.2× 91 0.7× 17 0.2× 71 1.1× 21 826
Jagruti Patel United States 9 694 1.4× 134 0.7× 63 0.5× 48 0.6× 43 0.7× 17 855

Countries citing papers authored by Taejeong Bae

Since Specialization
Citations

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

Fields of papers citing papers by Taejeong Bae

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Taejeong Bae

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

All Works

20 of 20 papers shown
1.
Panda, Arijit, Milovan Šuvakov, Jessica Mariani, et al.. (2023). Clonally Selected Lines After CRISPR-Cas Editing Are Not Isogenic. The CRISPR Journal. 6(2). 176–182. 4 indexed citations
2.
Jang, Yeongjun, Liana Fasching, Taejeong Bae, et al.. (2023). Efficient reconstruction of cell lineage trees for cell ancestry and cancer. Nucleic Acids Research. 51(10). e57–e57. 1 indexed citations
3.
Sarangi, Vivekananda, Yeongjun Jang, Milovan Šuvakov, et al.. (2022). All2: A tool for selecting mosaic mutations from comprehensive multi-cell comparisons. PLoS Computational Biology. 18(4). e1009487–e1009487. 1 indexed citations
4.
Bizzotto, Sara, Yanmei Dou, Javier Ganz, et al.. (2021). Landmarks of human embryonic development inscribed in somatic mutations. Science. 371(6535). 1249–1253. 55 indexed citations
5.
Fasching, Liana, Yeongjun Jang, Simone Tomasi, et al.. (2021). Early developmental asymmetries in cell lineage trees in living individuals. Science. 371(6535). 1245–1248. 35 indexed citations
6.
Sekar, Shobana, Livia Tomasini, Christos Proukakis, et al.. (2020). Complex mosaic structural variations in human fetal brains. Genome Research. 30(12). 1695–1704. 19 indexed citations
7.
Sarangi, Vivekananda, Alexandre Jourdon, Taejeong Bae, et al.. (2020). SCELLECTOR: ranking amplification bias in single cells using shallow sequencing. BMC Bioinformatics. 21(1). 521–521. 2 indexed citations
8.
Bae, Taejeong, et al.. (2020). Effect of Nutrition Counseling by Nutrition Care Process on Diet Therapy Practice and Glycemic Control in Type 2 Diabetic Patients. Korean Journal of Community Nutrition. 25(3). 214–214. 3 indexed citations
9.
Bae, Taejeong, Livia Tomasini, Jessica Mariani, et al.. (2017). Different mutational rates and mechanisms in human cells at pregastrulation and neurogenesis. Science. 359(6375). 550–555. 169 indexed citations
10.
Kim, Minsoo, Brooke R. Druliner, Taejeong Bae, et al.. (2017). Inferring modes of evolution from colorectal cancer with residual polyp of origin. Oncotarget. 9(6). 6780–6792. 2 indexed citations
11.
Druliner, Brooke R., Shahrooz Rashtak, Xiaoyang Ruan, et al.. (2016). Colorectal Cancer with Residual Polyp of Origin: A Model of Malignant Transformation. Translational Oncology. 9(4). 280–286. 8 indexed citations
12.
Bae, Taejeong, et al.. (2015). Restoration of paclitaxel resistance by CDK1 intervention in drug-resistant ovarian cancer. Carcinogenesis. 36(12). bgv140–bgv140. 32 indexed citations
13.
Bae, Taejeong, Kyoohyoung Rho, Jin Woo Choi, et al.. (2013). Identification of upstream regulators for prognostic expression signature genes in colorectal cancer. BMC Systems Biology. 7(1). 86–86. 10 indexed citations
14.
Saito, Shigeru, Xinrong Zhou, Taejeong Bae, Sung‐Hoon Kim, & Katsuhisa Horimoto. (2013). Identification of master regulator candidates in conjunction with network screening and inference. International Journal of Data Mining and Bioinformatics. 8(3). 366–366. 5 indexed citations
15.
Park, Kyung Hee, Nam Huh, Sohee Oh, et al.. (2012). Selecting SNPs for pharmacogenomic association study. International Journal of Data Mining and Bioinformatics. 6(5). 521–521. 2 indexed citations
16.
Lee, Ji Hyun, Taejeong Bae, Kyoohyoung Rho, et al.. (2012). CDA: Combinatorial Drug Discovery Using Transcriptional Response Modules. PLoS ONE. 7(8). e42573–e42573. 58 indexed citations
17.
Bae, Taejeong, Jihyun Lee, Dae Gyu Kim, et al.. (2012). Rational drug repositioning guided by an integrated pharmacological network of protein, disease and drug. BMC Systems Biology. 6(1). 80–80. 65 indexed citations
18.
Rho, Kyoohyoung, Bumjin Kim, Yeongjun Jang, et al.. (2011). GARNET – gene set analysis with exploration of annotation relations. BMC Bioinformatics. 12(S1). S25–S25. 10 indexed citations
19.
Saito, Shigeru, Xinrong Zhou, Taejeong Bae, Sung‐Hoon Kim, & Katsuhisa Horimoto. (2010). A procedure for identifying master regulators in conjunction with network screening and inference. 137. 296–301. 2 indexed citations
20.
Bae, Taejeong, Min‐Sik Kim, Hyo‐Jung Choo, et al.. (2004). Lipid raft proteome reveals ATP synthase complex in the cell surface. PROTEOMICS. 4(11). 3536–3548. 144 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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