Min Oh

666 total citations
14 papers, 474 citations indexed

About

Min Oh is a scholar working on Molecular Biology, Computational Theory and Mathematics and Pharmacology. According to data from OpenAlex, Min Oh has authored 14 papers receiving a total of 474 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 6 papers in Computational Theory and Mathematics and 3 papers in Pharmacology. Recurrent topics in Min Oh's work include Computational Drug Discovery Methods (6 papers), Bioinformatics and Genomic Networks (3 papers) and Gut microbiota and health (3 papers). Min Oh is often cited by papers focused on Computational Drug Discovery Methods (6 papers), Bioinformatics and Genomic Networks (3 papers) and Gut microbiota and health (3 papers). Min Oh collaborates with scholars based in United States, South Korea and United Kingdom. Min Oh's co-authors include Liqing Zhang, Amy Pruden, Chaoqi Chen, Lenwood S. Heath, Kang Xia, Liqing Zhang, Jaegyoon Ahn, Youngmi Yoon, Pang Du and Liqing Zhang and has published in prestigious journals such as PLoS ONE, Scientific Reports and Environment International.

In The Last Decade

Min Oh

13 papers receiving 464 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Min Oh United States	8	234	222	132	64	54	14	474
Longfei Xie China	14	93 0.4×	186 0.8×	51 0.4×	42 0.7×	21 0.4×	28	427
Stanley Chukwudozie Onuoha Nigeria	11	74 0.3×	153 0.7×	25 0.2×	13 0.2×	30 0.6×	25	332
Anna Philips Poland	12	70 0.3×	307 1.4×	51 0.4×	23 0.4×	38 0.7×	30	459
Shahin Mahmud Bangladesh	11	44 0.2×	79 0.4×	24 0.2×	13 0.2×	21 0.4×	75	336
Iffat Jahan Bangladesh	8	65 0.3×	66 0.3×	11 0.1×	23 0.4×	25 0.5×	25	315
Aubrie O’Rourke United States	9	16 0.1×	80 0.4×	19 0.1×	32 0.5×	21 0.4×	18	271
Javier Belmont-Díaz Mexico	11	15 0.1×	216 1.0×	51 0.4×	40 0.6×	7 0.1×	15	392
Gongli Zong China	11	38 0.2×	153 0.7×	52 0.4×	23 0.4×		34	294
Satish K. Walia United States	13	167 0.7×	81 0.4×	74 0.6×	51 0.8×	1 0.0×	21	306
A Kothari United States	3	25 0.1×	379 1.7×	4 0.0×	53 0.8×	20 0.4×	3	506

Countries citing papers authored by Min Oh

Since Specialization

Citations

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

Fields of papers citing papers by Min Oh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Min Oh

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

All Works

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14 of 14 papers shown

Climente-González, Héctor, Min Oh, Urszula Chajewska, et al.. (2025). Interpretable machine learning leverages proteomics to improve cardiovascular disease risk prediction and biomarker identification. Communications Medicine. 5(1). 170–170. 2 indexed citations

Oh, Min, Benjamin C. Davis, Connor Brown, et al.. (2024). MetaCompare 2.0: differential ranking of ecological and human health resistome risks. FEMS Microbiology Ecology. 100(12). 16 indexed citations

Oh, Min & Liqing Zhang. (2023). DeepGeni: deep generalized interpretable autoencoder elucidates gut microbiota for better cancer immunotherapy. Scientific Reports. 13(1). 4599–4599. 7 indexed citations

Oh, Min & Liqing Zhang. (2022). Generalizing predictions to unseen sequencing profiles via deep generative models. Scientific Reports. 12(1). 7151–7151. 7 indexed citations

Coşgun, Erdal & Min Oh. (2020). Exploring the Consistency of the Quality Scores with Machine Learning for Next‐Generation Sequencing Experiments. BioMed Research International. 2020(1). 8531502–8531502. 8 indexed citations

Oh, Min & Liqing Zhang. (2020). DeepMicro: deep representation learning for disease prediction based on microbiome data. Scientific Reports. 10(1). 6026–6026. 100 indexed citations

Chen, Chaoqi, Min Oh, Lenwood S. Heath, et al.. (2019). Effect of antibiotic use and composting on antibiotic resistance gene abundance and resistome risks of soils receiving manure-derived amendments. Environment International. 128. 233–243. 120 indexed citations

Oh, Min, Amy Pruden, Chaoqi Chen, et al.. (2018). MetaCompare: a computational pipeline for prioritizing environmental resistome risk. FEMS Microbiology Ecology. 94(7). 137 indexed citations

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

10.

Oh, Min, et al.. (2017). Drug voyager: a computational platform for exploring unintended drug action. BMC Bioinformatics. 18(1). 131–131. 9 indexed citations

11.

Park, Chihyun, Youngmi Yoon, Min Oh, Seok Jong Yu, & Jaegyoon Ahn. (2017). Systematic identification of differential gene network to elucidate Alzheimer's disease. Expert Systems with Applications. 85. 249–260. 14 indexed citations

12.

Oh, Min, et al.. (2016). Extraction of specific common genetic network of side effect pair, and prediction of side effects for a drug based on PPI network. Journal of the Korea Society of Computer and Information. 21(1). 115–123. 1 indexed citations

13.

Oh, Min, et al.. (2016). Novel Drug Similarity Measuring Method based on Text Mining for Predicting Similar Drugs. The Journal of Korean Institute of Information Technology. 14(7). 127–127. 2 indexed citations

14.

Oh, Min, Jaegyoon Ahn, & Youngmi Yoon. (2014). A Network-Based Classification Model for Deriving Novel Drug-Disease Associations and Assessing Their Molecular Actions. PLoS ONE. 9(10). e111668–e111668. 44 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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