Seonwoo Min

3.7k citations
32 papers · 2.3k indexed · 1 hit paper · h-index 17
Topics
CRISPR and Genetic Engineering (11 papers)RNA and protein synthesis mechanisms (11 papers)Machine Learning in Bioinformatics (5 papers)

In The Last Decade

Seonwoo Min

27 papers receiving 2.3k citations

Hit Papers

Deep learning in bioinformatics201620262019202220162505007501000

Peers

Seonwoo Min
Comparison fields: 5 of 158
  • Molecular Biology 1.7k
  • Artificial Intelligence 262
  • Genetics 261
  • Plant Science 164
  • Computational Theory and Mathematics 128
Replace Ivan Merelli with:
Ivan Merelli Italy
Nicolò Fusi United Kingdom
Wenjie Shu China
Yan Cui United States
Xinghua Shi United States
Qiao Liu China
Rosalba Giugno Italy
Faraz Faghri United States
Shaojie Zhang United States
Julien Gagneur Germany
Seonwoo Min relative to Ivan Merelli Italy Ivan Merelli's profile →
Citations per field
00.5×2.8×
Ivan Merelli · 1×
Citations per year

Countries citing papers authored by Seonwoo Min

Since Specialization
Citations

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

Fields of papers citing papers by Seonwoo Min

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seonwoo Min

This figure shows the co-authorship network connecting the top 25 collaborators of Seonwoo Min. A scholar is included among the top collaborators of Seonwoo Min 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 Seonwoo Min. Seonwoo Min 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
#WorkIndexed citations
1 39
2 33
3 6
4 12
5 65
6 27
7 12
8 33
9 24
10 81
11 146
12 193
13 106
14 11
15 18
16 140
17 245
18
Deep Recurrent Neural Network-Based Identification of Precursor microRNAs
22
19
A SeqGAN for Polyphonic Music Generation.
4
20
Supervised Learning with multilayer Bidirectional Associative Memory
0

About Seonwoo Min

Seonwoo Min is a scholar working on Aging, Signal Processing and Molecular Biology, having authored 32 papers that have together received 2.3k indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (11 papers), RNA and protein synthesis mechanisms (11 papers) and Machine Learning in Bioinformatics (5 papers). The work is most often cited by research in Business and International Management (96 citations), Aging (59 citations) and Molecular Biology (1.7k citations). Seonwoo Min has collaborated with scholars based in South Korea, United States and Ethiopia. Frequent co-authors include Sungroh Yoon, Byunghan Lee, Seokjoong Kim, Hui Kwon Kim, Jinman Park, Sungtae Lee, Jae Woo Choi, Younggwang Kim, Goosang Yu and Sung‐Rae Cho. Their work appears in journals such as Cell, Nature Communications and Nature Biotechnology.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026