Jaegyoon Ahn

1.6k total citations
52 papers, 1.2k citations indexed

About

Jaegyoon Ahn is a scholar working on Molecular Biology, Computational Theory and Mathematics and Cancer Research. According to data from OpenAlex, Jaegyoon Ahn has authored 52 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Molecular Biology, 14 papers in Computational Theory and Mathematics and 10 papers in Cancer Research. Recurrent topics in Jaegyoon Ahn's work include Bioinformatics and Genomic Networks (22 papers), Gene expression and cancer classification (17 papers) and Computational Drug Discovery Methods (14 papers). Jaegyoon Ahn is often cited by papers focused on Bioinformatics and Genomic Networks (22 papers), Gene expression and cancer classification (17 papers) and Computational Drug Discovery Methods (14 papers). Jaegyoon Ahn collaborates with scholars based in South Korea, United States and Puerto Rico. Jaegyoon Ahn's co-authors include Sanghyun Park, Chihyun Park, Xinshu Xiao, Youngmi Yoon, Jae‐Hyung Lee, Geonhee Lee, Chonghui Cheng, Xin D. Gao, Yilin Xu and Min Oh and has published in prestigious journals such as Nature Communications, Genes & Development and Bioinformatics.

In The Last Decade

Jaegyoon Ahn

48 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jaegyoon Ahn South Korea 19 883 285 206 99 97 52 1.2k
Xiang Zhuang China 13 441 0.5× 109 0.4× 146 0.7× 79 0.8× 54 0.6× 37 753
Neel S. Madhukar United States 11 523 0.6× 255 0.9× 195 0.9× 185 1.9× 145 1.5× 28 1.2k
Lit‐Hsin Loo Singapore 14 601 0.7× 134 0.5× 130 0.6× 29 0.3× 171 1.8× 33 1.2k
Krishna C. Bulusu United Kingdom 12 698 0.8× 451 1.6× 133 0.6× 55 0.6× 191 2.0× 18 1.1k
Xiaojun Liu China 20 1.1k 1.3× 116 0.4× 152 0.7× 26 0.3× 157 1.6× 54 1.4k
Brent M. Kuenzi United States 13 524 0.6× 190 0.7× 109 0.5× 45 0.5× 331 3.4× 22 923
Fathi Elloumi United States 16 603 0.7× 201 0.7× 312 1.5× 64 0.6× 403 4.2× 29 1.1k
Yubing Zhou China 19 524 0.6× 58 0.2× 249 1.2× 42 0.4× 186 1.9× 56 1.0k
Baofeng Lian China 14 575 0.7× 108 0.4× 317 1.5× 19 0.2× 86 0.9× 27 837
Kuan‐Ting Lin Taiwan 19 732 0.8× 49 0.2× 194 0.9× 58 0.6× 95 1.0× 46 963

Countries citing papers authored by Jaegyoon Ahn

Since Specialization
Citations

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

Fields of papers citing papers by Jaegyoon Ahn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jaegyoon Ahn

This figure shows the co-authorship network connecting the top 25 collaborators of Jaegyoon Ahn. A scholar is included among the top collaborators of Jaegyoon Ahn 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 Jaegyoon Ahn. Jaegyoon Ahn 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
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Lee, Su‐Yeon, et al.. (2023). Accurate Prediction of Cancer Prognosis by Exploiting Patient-Specific Cancer Driver Genes. International Journal of Molecular Sciences. 24(7). 6445–6445. 2 indexed citations
4.
Sung, Pil Soo, et al.. (2022). Blood-based biomarkers for immune-based therapy in advanced HCC: Promising but a long way to go. Frontiers in Oncology. 12. 1028728–1028728. 3 indexed citations
5.
Park, Sanghyun, et al.. (2021). Binding affinity prediction for protein–ligand complex using deep attention mechanism based on intermolecular interactions. BMC Bioinformatics. 22(1). 542–542. 65 indexed citations
6.
Ahn, Jaegyoon, et al.. (2021). GVES: machine learning model for identification of prognostic genes with a small dataset. Scientific Reports. 11(1). 439–439. 14 indexed citations
7.
Park, Sanghyun, et al.. (2020). RefDNN: a reference drug based neural network for more accurate prediction of anticancer drug resistance. Scientific Reports. 10(1). 1861–1861. 48 indexed citations
8.
Ahn, Jaegyoon, et al.. (2019). RN + : A Novel Biclustering Algorithm for Analysis of Gene Expression Data Using Protein–Protein Interaction Network. Journal of Computational Biology. 26(5). 432–441. 2 indexed citations
9.
Lee, Geonhee, Chihyun Park, & Jaegyoon Ahn. (2019). Novel deep learning model for more accurate prediction of drug-drug interaction effects. BMC Bioinformatics. 20(1). 415–415. 106 indexed citations
10.
Ahn, Jaegyoon, et al.. (2018). G2Vec: Distributed gene representations for identification of cancer prognostic genes. Scientific Reports. 8(1). 13729–13729. 24 indexed citations
11.
Oh, Min, et al.. (2017). Identifying the common genetic networks of ADR (adverse drug reaction) clusters and developing an ADR classification model. Molecular BioSystems. 13(9). 1788–1796. 7 indexed citations
12.
Bhate, Amruta, Darren J. Parker, Thomas W. Bebee, et al.. (2015). ESRP2 controls an adult splicing programme in hepatocytes to support postnatal liver maturation. Nature Communications. 6(1). 8768–8768. 78 indexed citations
13.
Bahn, Jae Hoon, Jaegyoon Ahn, Xianzhi Lin, et al.. (2015). Genomic analysis of ADAR1 binding and its involvement in multiple RNA processing pathways. Nature Communications. 6(1). 6355–6355. 121 indexed citations
14.
Kim, Hyunjin, Youngmi Yoon, Jaegyoon Ahn, & Sanghyun Park. (2015). A literature-driven method to calculate similarities among diseases. Computer Methods and Programs in Biomedicine. 122(2). 108–122. 11 indexed citations
15.
Xu, Yilin, Xin D. Gao, Jae‐Hyung Lee, et al.. (2014). Cell type-restricted activity of hnRNPM promotes breast cancer metastasis via regulating alternative splicing. Genes & Development. 28(11). 1191–1203. 186 indexed citations
16.
Kim, Hyunjin, Jaegyoon Ahn, Chihyun Park, Youngmi Yoon, & Sanghyun Park. (2013). ICP: A novel approach to predict prognosis of prostate cancer with inner-class clustering of gene expression data. Computers in Biology and Medicine. 43(10). 1363–1373. 6 indexed citations
17.
Ahn, Jaegyoon, Dae Hyun Lee, Youngmi Yoon, Yunku Yeu, & Sanghyun Park. (2013). Improved method for protein complex detection using bottleneck proteins. BMC Medical Informatics and Decision Making. 13(S1). S5–S5. 4 indexed citations
18.
Yeu, Yunku, et al.. (2012). A survey of sequence alignment algorithms for next-generation sequencing read. 28(1). 33–51.
19.
Yoon, Youngmi, et al.. (2011). TC-VGC: A Tumor Classification System using Variations in Genes’ Correlation. Computer Methods and Programs in Biomedicine. 104(3). e87–e101. 5 indexed citations
20.
Park, Chihyun, Jaegyoon Ahn, Youngmi Yoon, & Sanghyun Park. (2011). A Multi-Sample Based Method for Identifying Common CNVs in Normal Human Genomic Structure Using High-Resolution aCGH Data. PLoS ONE. 6(10). e26975–e26975. 5 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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