Jang‐Sik Choi

527 total citations
22 papers, 399 citations indexed

About

Jang‐Sik Choi is a scholar working on Molecular Biology, Oncology and Materials Chemistry. According to data from OpenAlex, Jang‐Sik Choi has authored 22 papers receiving a total of 399 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 6 papers in Oncology and 6 papers in Materials Chemistry. Recurrent topics in Jang‐Sik Choi's work include Advanced Chemical Sensor Technologies (5 papers), Metal complexes synthesis and properties (5 papers) and Lanthanide and Transition Metal Complexes (4 papers). Jang‐Sik Choi is often cited by papers focused on Advanced Chemical Sensor Technologies (5 papers), Metal complexes synthesis and properties (5 papers) and Lanthanide and Transition Metal Complexes (4 papers). Jang‐Sik Choi collaborates with scholars based in South Korea, South Africa and Greece. Jang‐Sik Choi's co-authors include My Kieu Ha, Tae Hyun Yoon, Shin‐Geol Kang, Hyung‐Gi Byun, Mi-Seon Kim, Tung X. Trinh, Kimoon Kim, Dongmok Whang, Ho‐Juhn Song and Jong Sung Koh and has published in prestigious journals such as Blood, PLoS ONE and Scientific Reports.

In The Last Decade

Jang‐Sik Choi

19 papers receiving 387 citations

Peers

Jang‐Sik Choi
Xiaotian Kong China
Kaushik Banerjee India
Haikuo Ma China
Marianna Talia Italy
Jianjiao Chen China
Ruhua Chen China
Bryan T. Greene United States
Eliška Potůčková Czechia
Rika Goda Japan
Qin Yue China
Xiaotian Kong China
Jang‐Sik Choi
Citations per year, relative to Jang‐Sik Choi Jang‐Sik Choi (= 1×) peers Xiaotian Kong

Countries citing papers authored by Jang‐Sik Choi

Since Specialization
Citations

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

Fields of papers citing papers by Jang‐Sik Choi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jang‐Sik Choi. 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 Jang‐Sik Choi. The network helps show where Jang‐Sik Choi may publish in the future.

Co-authorship network of co-authors of Jang‐Sik Choi

This figure shows the co-authorship network connecting the top 25 collaborators of Jang‐Sik Choi. A scholar is included among the top collaborators of Jang‐Sik Choi 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 Jang‐Sik Choi. Jang‐Sik Choi 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
1.
Choi, Jang‐Sik & Hyung‐Gi Byun. (2021). A case study to standardize odor metadata obtained from coffee aroma based on E-nose using ISO/IEC 23005 (MPEG-V) for olfactory-enhanced multimedia. Journal of Sensor Science and Technology. 30(4). 204–209. 1 indexed citations
2.
Federico, Antonio, Angela Serra, My Kieu Ha, et al.. (2020). Transcriptomics in Toxicogenomics, Part II: Preprocessing and Differential Expression Analysis for High Quality Data. Nanomaterials. 10(5). 903–903. 31 indexed citations
3.
Serra, Angela, Michele Fratello, Luca Cattelani, et al.. (2020). Transcriptomics in Toxicogenomics, Part III: Data Modelling for Risk Assessment. Nanomaterials. 10(4). 708–708. 42 indexed citations
4.
Kinaret, Pia, Angela Serra, Antonio Federico, et al.. (2020). Transcriptomics in Toxicogenomics, Part I: Experimental Design, Technologies, Publicly Available Data, and Regulatory Aspects. Nanomaterials. 10(4). 750–750. 46 indexed citations
5.
Choi, Jang‐Sik, My Kieu Ha, Tung X. Trinh, Tae Hyun Yoon, & Hyung‐Gi Byun. (2018). Towards a generalized toxicity prediction model for oxide nanomaterials using integrated data from different sources. Scientific Reports. 8(1). 6110–6110. 63 indexed citations
6.
7.
Choi, Jang‐Sik, et al.. (2016). Implementation of Elbow Method to improve the Gases Classification Performance based on the RBFN-NSG Algorithm. Journal of Sensor Science and Technology. 25(6). 431–434. 3 indexed citations
8.
Choi, Jang‐Sik, et al.. (2016). Investigation of Chemical Sensor Array Optimization Methods for DADSS. Journal of Sensor Science and Technology. 25(1). 13–19. 1 indexed citations
9.
Lee, Sang Jae, Jang‐Sik Choi, Hyoun Sook Kim, et al.. (2016). Crystal structures of spleen tyrosine kinase in complex with novel inhibitors: structural insights for design of anticancer drugs. FEBS Journal. 283(19). 3613–3625. 9 indexed citations
10.
Jeon, Woo Hyung, Hyunseok Kim, Jang‐Sik Choi, Kooyeon Lee, & Phil Ho Lee. (2015). Palladium‐catalyzed Intramolecular Coupling Reactions between Vinyl Bromides, Aryl and Vinyl Halides, and Aryl Iodides Mediated by Indium: Preparation of Five‐ to Eight‐membered Carbocycles and Heterocycles. Bulletin of the Korean Chemical Society. 36(2). 711–714.
11.
Choi, Jang‐Sik, Byung Il Lee, Ho‐Juhn Song, et al.. (2015). Highly potent and selective pyrazolylpyrimidines as Syk kinase inhibitors. Bioorganic & Medicinal Chemistry Letters. 25(20). 4441–4446. 14 indexed citations
12.
Choi, Jang‐Sik, et al.. (2015). Implementation of Context-Based Recommendation System to Verify Schema of MPEG-UD Standard. Journal of Sensor Science and Technology. 24(1). 62–68.
13.
Lee, In Yong, Dong Sik Jung, Sang Yeop Lee, et al.. (2014). G-749, a novel FLT3 kinase inhibitor, can overcome drug resistance for the treatment of acute myeloid leukemia. Blood. 123(14). 2209–2219. 47 indexed citations
14.
Byun, Hyung‐Gi & Jang‐Sik Choi. (2014). Real-Time Visualization Techniques for Sensor Array Patterns Using PCA and Sammon Mapping Analysis. Journal of Sensor Science and Technology. 23(2). 99–104. 2 indexed citations
15.
Lee, Sang Jae, et al.. (2013). Crystal Structure of Pim1 Kinase in Complex with a Pyrido[4,3-D]Pyrimidine Derivative Suggests a Unique Binding Mode. PLoS ONE. 8(7). e70358–e70358. 14 indexed citations
16.
Kang, Shin‐Geol, Jang‐Sik Choi, Kwanghee Nam, Hyungphil Chun, & Kimoon Kim. (2004). Synthesis and characterization of new adjacent-bridged tetraaza macrocyclic compounds with C-alkyl groups: crystal structure and spectral properties of a copper(II) complex. Inorganica Chimica Acta. 357(9). 2783–2790. 9 indexed citations
17.
Kang, Shin‐Geol, Mi-Seon Kim, Jang‐Sik Choi, Dongmok Whang, & Kimoon Kim. (1995). Synthesis and characterization of a di-N-hydroxyethylated tetraaza macrocycle and its nickel(II) and copper(II) complexes: crystal structure of the nickel(II) complex. Journal of the Chemical Society Dalton Transactions. 363–363. 47 indexed citations
18.
Kang, Shin‐Geol, et al.. (1995). Synthesis, characterization and properties of new fully n-alkylated 14-membered tetraaza macrocycles and their copper(II) complexes. Polyhedron. 14(6). 781–786. 14 indexed citations
19.
Kang, Shin‐Geol & Jang‐Sik Choi. (1994). Syntheses and Properties of New Nickel(II) Complexes of 14-Membered Pentaaza Macrocyclic Ligands with C-Nitro and N-Alkyl Pendant Arms. Bulletin of the Korean Chemical Society. 15(5). 374–378. 5 indexed citations
20.
Kang, Shin‐Geol, et al.. (1993). Effects of N-and C-Substituents on Protonation of 14-Membered Tetraaza Macrocycles and Formation of their Copper(II) and Nickel(II) Complexes. Bulletin of the Korean Chemical Society. 10(5). 75–79. 1 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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