Ingoo Lee

1.2k total citations · 1 hit paper
8 papers, 683 citations indexed

About

Ingoo Lee is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Ingoo Lee has authored 8 papers receiving a total of 683 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 5 papers in Computational Theory and Mathematics and 3 papers in Materials Chemistry. Recurrent topics in Ingoo Lee's work include Computational Drug Discovery Methods (5 papers), Protein Structure and Dynamics (3 papers) and Machine Learning in Materials Science (3 papers). Ingoo Lee is often cited by papers focused on Computational Drug Discovery Methods (5 papers), Protein Structure and Dynamics (3 papers) and Machine Learning in Materials Science (3 papers). Ingoo Lee collaborates with scholars based in South Korea and United States. Ingoo Lee's co-authors include Hojung Nam, Hansol Lee, Minsu Park, Eun‐Young Kim, Minsu Park, Yong‐Chul Kim, Sahar Alkhairy, Robin E. Bachelder, Dylan Fong and Dexter Pratt and has published in prestigious journals such as Nature Methods, BMC Bioinformatics and PLoS Computational Biology.

In The Last Decade

Ingoo Lee

8 papers receiving 674 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequences

2019 414 citations Ingoo Lee, Hojung Nam et al. PLoS Computational Biology profile →

Peers

Ingoo Lee

MB

CTM

MC

PHARM

MICRO

Tunca Doğan Türkiye

Ahmet Süreyya Rifaioğlu Türkiye

Heval Ataş Türkiye

Oleksii Prykhodko Sweden

Panagiotis-Christos Kotsias Sweden

Shuting Jin China

Elif Özkırımlı Türkiye

Tong He China

Kathrin Heikamp Germany

Brice Hoffmann France

Tunca Doğan Türkiye

Ingoo Lee

859 ×1.6

MB

615 ×1.2

CTM

220 ×1.1

MC

65 ×1.4

PHARM

17 ×0.5

MICRO

Citations per year, relative to Ingoo Lee Ingoo Lee (= 1×) peers Tunca Doğan

Countries citing papers authored by Ingoo Lee

Since Specialization

Citations

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

Fields of papers citing papers by Ingoo Lee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ingoo Lee

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

All Works

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8 of 8 papers shown

1.

Alkhairy, Sahar, Ingoo Lee, Rudolf Pillich, et al.. (2024). Evaluation of large language models for discovery of gene set function. Nature Methods. 22(1). 82–91. 20 indexed citations

2.

Lee, Ingoo, et al.. (2022). AI-based prediction of new binding site and virtual screening for the discovery of novel P2X3 receptor antagonists. European Journal of Medicinal Chemistry. 240. 114556–114556. 10 indexed citations

3.

Lee, Ingoo & Hojung Nam. (2022). Sequence-based prediction of protein binding regions and drug–target interactions. Journal of Cheminformatics. 14(1). 5–5. 43 indexed citations

4.

Lee, Hansol, et al.. (2022). AMP‐BERT: Prediction of antimicrobial peptide function based on a BERT model. Protein Science. 32(1). e4529–e4529. 59 indexed citations

5.

Park, Minsu, et al.. (2022). BayeshERG: a robust, reliable and interpretable deep learning model for predicting hERG channel blockers. Briefings in Bioinformatics. 23(4). 19 indexed citations

6.

Kim, Eun‐Young, et al.. (2020). Artificial Intelligence in Drug Discovery: A Comprehensive Review of Data-driven and Machine Learning Approaches. Biotechnology and Bioprocess Engineering. 25(6). 895–930. 71 indexed citations

7.

Lee, Ingoo, et al.. (2019). DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequences. PLoS Computational Biology. 15(6). e1007129–e1007129. 414 indexed citations breakdown →

8.

Lee, Ingoo & Hojung Nam. (2018). Identification of drug-target interaction by a random walk with restart method on an interactome network. BMC Bioinformatics. 19(S8). 208–208. 47 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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