Dongsup Kim

5.1k total citations
111 papers, 2.7k citations indexed

About

Dongsup Kim is a scholar working on Molecular Biology, Computational Theory and Mathematics and Genetics. According to data from OpenAlex, Dongsup Kim has authored 111 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 86 papers in Molecular Biology, 21 papers in Computational Theory and Mathematics and 10 papers in Genetics. Recurrent topics in Dongsup Kim's work include Protein Structure and Dynamics (27 papers), Computational Drug Discovery Methods (21 papers) and Genomics and Chromatin Dynamics (15 papers). Dongsup Kim is often cited by papers focused on Protein Structure and Dynamics (27 papers), Computational Drug Discovery Methods (21 papers) and Genomics and Chromatin Dynamics (15 papers). Dongsup Kim collaborates with scholars based in South Korea, United States and Canada. Dongsup Kim's co-authors include Keunwan Park, Inkyung Jung, Minho Lee, Doheon Lee, Ying Xu, Jinbo Xu, Ming Li, Aeri Lee, Byung‐Chul Lee and Sangjo Han and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nucleic Acids Research.

In The Last Decade

Dongsup Kim

110 papers receiving 2.7k citations

Peers

Dongsup Kim

CTM

IMMUN

GENET

Christina Kiel Spain

Jong Cheol Jeong United States

Olli T. Pentikäinen Finland

Leo S. D. Caves United Kingdom

Hao Fan Singapore

Helge Weissig United States

Jacob de Vlieg Netherlands

Evangelia Petsalaki United Kingdom

Mu Gao United States

Christina Kiel Spain

Dongsup Kim

2.6k ×1.3

509 ×1.0

CTM

264 ×0.9

195 ×0.8

IMMUN

194 ×0.8

GENET

Citations per year, relative to Dongsup Kim Dongsup Kim (= 1×) peers Christina Kiel

Countries citing papers authored by Dongsup Kim

Since Specialization

Citations

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

Fields of papers citing papers by Dongsup Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dongsup Kim

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

All Works

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20 of 20 papers shown

Kim, Dongsup, et al.. (2024). Integrating genomic and molecular data to predict antimicrobial minimum inhibitory concentration in Klebsiella pneumoniae. Scientific Reports. 14(1). 25951–25951. 2 indexed citations

Park, Woong‐Yang, et al.. (2023). G-RANK: an equivariant graph neural network for the scoring of protein–protein docking models. Bioinformatics Advances. 3(1). vbad011–vbad011. 3 indexed citations

Seo, Yoojin, Seokyoung Bang, Dongsup Kim, et al.. (2021). Brain physiome: A concept bridging in vitro 3D brain models and in silico models for predicting drug toxicity in the brain. Bioactive Materials. 13. 135–148. 20 indexed citations

Lee, Minho, Sangjo Han, Miyoung Nam, et al.. (2018). Mutation Analysis of Synthetic DNA Barcodes in a Fission Yeast Gene Deletion Library by Sanger Sequencing. Genomics & Informatics. 16(2). 22–29. 2 indexed citations

Jeong, Chanseok & Dongsup Kim. (2016). Structure-based Markov random field model for representing evolutionary constraints on functional sites. BMC Bioinformatics. 17(1). 99–99. 8 indexed citations

Cho, Sung Yoon, Nayoung K. D. Kim, Francesca Forzano, et al.. (2016). BGN Mutations in X-Linked Spondyloepimetaphyseal Dysplasia. The American Journal of Human Genetics. 98(6). 1243–1248. 30 indexed citations

Kim, Seunghyo, Ha Young Kim, Dongsup Kim, et al.. (2016). FARS2 mutation and epilepsy: Possible link with early-onset epileptic encephalopathy. Epilepsy Research. 129. 118–124. 19 indexed citations

Lee, Aeri, et al.. (2016). Using reverse docking for target identification and its applications for drug discovery. Expert Opinion on Drug Discovery. 11(7). 707–715. 99 indexed citations

Jung, Inkyung, et al.. (2015). Global mapping of the regulatory interactions of histone residues. FEBS Letters. 589(24PartB). 4061–4070. 9 indexed citations

10.

Lee, Yuno, Joong‐jae Lee, Songmi Kim, et al.. (2014). Dissecting the Critical Factors for Thermodynamic Stability of Modular Proteins Using Molecular Modeling Approach. PLoS ONE. 9(5). e98243–e98243. 19 indexed citations

11.

Nam, Miyoung, Sook-Jeong Lee, Sangjo Han, et al.. (2014). Systematic targeted gene deletion using the gene-synthesis method in fission yeast. Journal of Microbiological Methods. 106. 72–77. 2 indexed citations

12.

Han, Sangjo, Minho Lee, Hyeshik Chang, et al.. (2013). Construction of the first compendium of chemical-genetic profiles in the fission yeast Schizosaccharomyces pombe and comparative compendium approach. Biochemical and Biophysical Research Communications. 436(4). 613–618. 11 indexed citations

13.

Park, Keunwan & Dongsup Kim. (2012). Structure-based rebuilding of coevolutionary information reveals functional modules in rhodopsin structure. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics. 1824(12). 1484–1489. 4 indexed citations

14.

Jung, Inkyung, Seung-Kyoon Kim, Mirang Kim, et al.. (2012). H2B monoubiquitylation is a 5′-enriched active transcription mark and correlates with exon–intron structure in human cells. Genome Research. 22(6). 1026–1035. 50 indexed citations

15.

Jung, Inkyung & Dongsup Kim. (2012). LinkNMF: Identification of histone modification modules in the human genome using nonnegative matrix factorization. Gene. 518(1). 215–221. 3 indexed citations

16.

Lee, Jungwoon, Yan Xia, Mi‐Young Son, et al.. (2012). A Novel Small Molecule Facilitates the Reprogramming of Human Somatic Cells into a Pluripotent State and Supports the Maintenance of an Undifferentiated State of Human Pluripotent Stem Cells. Angewandte Chemie International Edition. 51(50). 12509–12513. 34 indexed citations

17.

Park, Keunwan, Soyoung Lee, Hee‐Sung Ahn, & Dongsup Kim. (2009). Predicting the multi-modal binding propensity of small molecules: towards an understanding of drug promiscuity. Molecular BioSystems. 5(8). 844–853. 13 indexed citations

18.

Jung, Inkyung, et al.. (2008). Application of nonnegative matrix factorization to improve profile-profile alignment features for fold recognition and remote homolog detection. BMC Bioinformatics. 9(1). 298–298. 13 indexed citations

19.

Lee, KiYoung, et al.. (2006). Specificity of molecular interactions in transient protein–protein interaction interfaces. Proteins Structure Function and Bioinformatics. 65(3). 593–606. 32 indexed citations

20.

Kim, Dongsup & Sangyoub Lee. (1990). A Brownian dynamics method for systems of nonspherical Brownian particles. Bulletin of the Korean Chemical Society. 11(2). 127–131. 3 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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