Hyun‐Jong Jang

1.1k total citations
44 papers, 790 citations indexed

About

Hyun‐Jong Jang is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cognitive Neuroscience. According to data from OpenAlex, Hyun‐Jong Jang has authored 44 papers receiving a total of 790 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 15 papers in Cellular and Molecular Neuroscience and 12 papers in Cognitive Neuroscience. Recurrent topics in Hyun‐Jong Jang's work include Neuroscience and Neuropharmacology Research (15 papers), AI in cancer detection (10 papers) and Colorectal Cancer Screening and Detection (7 papers). Hyun‐Jong Jang is often cited by papers focused on Neuroscience and Neuropharmacology Research (15 papers), AI in cancer detection (10 papers) and Colorectal Cancer Screening and Detection (7 papers). Hyun‐Jong Jang collaborates with scholars based in South Korea, United States and Germany. Hyun‐Jong Jang's co-authors include Kyung‐Ok Cho, Sung Hak Lee, In Hye Song, Duck‐Joo Rhie, Myung-Jun Kim, Yang‐Hyeok Jo, Kwang‐Hyun Cho, Shin Hee Yoon, Sang June Hahn and Myung-Suk Kim and has published in prestigious journals such as Journal of Neuroscience, Cancer Research and Journal of Neurophysiology.

In The Last Decade

Hyun‐Jong Jang

42 papers receiving 777 citations

Peers

Countries citing papers authored by Hyun‐Jong Jang

Since Specialization

Citations

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

Fields of papers citing papers by Hyun‐Jong Jang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hyun‐Jong Jang

This figure shows the co-authorship network connecting the top 25 collaborators of Hyun‐Jong Jang. A scholar is included among the top collaborators of Hyun‐Jong Jang 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 Hyun‐Jong Jang. Hyun‐Jong Jang 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

#	Work	Indexed citations
1	Long-term tracking of neural and oligodendroglial development in large-scale human cerebral organoids by noninvasive volumetric imaging 2025 ·Scientific Reports ·Sangjun Park, (unknown), Eun‐Jin Choi, Jeong‐Sun Choi, Kyungjin Park, (unknown), Wonjun Choi, Hyun‐Jong Jang, Kyung‐Ok Cho, Moonseok Kim	2
2	Abstract 6175: Deep learning-based survival prediction for hepatocellular carcinoma using whole slide images 2024 ·Cancer Research ·Sung Hak Lee, Hyun‐Jong Jang	0
3	Recent application of artificial intelligence on histopathologic image-based prediction of gene mutation in solid cancers 2023 ·Briefings in Bioinformatics ·Rizwan Alam, Kyung Jin Seo, Jamshid Abdul‐Ghafar, Kwangil Yim, Sung Hak Lee, Hyun‐Jong Jang, Chan Kwon Jung, Yosep Chong	12
4	Deep Learning for the Pathologic Diagnosis of Hepatocellular Carcinoma, Cholangiocarcinoma, and Metastatic Colorectal Cancer 2023 ·Cancers ·Hyun‐Jong Jang, (unknown), Young-Hoon Kim, Sung Hak Lee	16
5	Deep learning-based prediction of molecular cancer biomarkers from tissue slides: A new tool for precision oncology 2022 ·Clinical and Molecular Hepatology ·Sung Hak Lee, Hyun‐Jong Jang	15
6	Prediction of clinically actionable genetic alterations from colorectal cancer histopathology images using deep learning 2020 ·World Journal of Gastroenterology ·Hyun‐Jong Jang, Ahwon Lee, (unknown), In Hye Song, Sung Hak Lee	56
7	Layer-specific involvement of endocannabinoid signaling in muscarinic-induced long-term depression in layer 2/3 pyramidal neurons of rat visual cortex 2019 ·Brain Research ·(unknown), Kwang‐Hyun Cho, (unknown), Hyun‐Jong Jang, Duck‐Joo Rhie	5
8	Applications of deep learning for the analysis of medical data 2019 ·Archives of Pharmacal Research ·Hyun‐Jong Jang, Kyung‐Ok Cho	67
9	Persistent Lin28 Expression Impairs Neurite Outgrowth and Cognitive Function in the Developing Mouse Neocortex 2018 ·Molecular Neurobiology ·Hyun‐Jong Jang, (unknown), Seong-Yun Kim, Kyung‐Ok Cho	8
10	Central Regulation of Micturition and Its Association With Epilepsy 2018 ·International Neurourology Journal ·Hyun‐Jong Jang, Min Kwon, Kyung‐Ok Cho	13
11	The level of nitric oxide regulates lipocalin-2 expression under inflammatory condition in RINm5F beta-cells 2016 ·Biochemical and Biophysical Research Communications ·(unknown), Dong‐Bin Kim, Seung‐Hyun Ko, Hyun‐Jong Jang, Yang‐Hyeok Jo, Myung-Jun Kim	11
12	Differential modulation of phasic and tonic inhibition underlies serotonergic suppression of long-term potentiation in the rat visual cortex 2015 ·Neuroscience ·Hyun‐Jong Jang, Kwang‐Hyun Cho, (unknown), (unknown), (unknown)	5
13	Layer- and cell-type-specific tonic GABAergic inhibition of pyramidal neurons in the rat visual cortex 2013 ·Pflügers Archiv - European Journal of Physiology ·Hyun‐Jong Jang, Kwang‐Hyun Cho, Myung-Jun Kim, Shin Hee Yoon, Duck‐Joo Rhie	8
14	Cholinergic Induction of Input-Specific Late-Phase LTP via Localized Ca²⁺Release in the Visual Cortex 2012 ·Journal of Neuroscience ·Kwang‐Hyun Cho, Hyun‐Jong Jang, Yang‐Hyeok Jo, Wolf Singer, Duck‐Joo Rhie	7
15	Developmental Switch of the Serotonergic Role in the Induction of Synaptic Long-term Potentiation in the Rat Visual Cortex 2012 ·Korean Journal of Physiology and Pharmacology ·Sung‐Won Park, Hyun‐Jong Jang, Kwang‐Hyun Cho, Myung-Jun Kim, Shin Hee Yoon, Duck‐Joo Rhie	17
16	Exendin-4 inhibits interleukin-1β-induced iNOS expression at the protein level, but not at the transcriptional and posttranscriptional levels, in RINm5F β-cells 2009 ·Journal of Endocrinology ·Jung‐Hoon Kang, (unknown), Hyun‐Jong Jang, Dong‐Bin Kim, Gyeong Ryul Ryu, Seung‐Hyun Ko, In‐Kyung Jeong, Yang‐Hyeok Jo, Myung-Jun Kim	27
17	Age-Dependent Decline in Supragranular Long-Term Synaptic Plasticity by Increased Inhibition During the Critical Period in the Rat Primary Visual Cortex 2008 ·Journal of Neurophysiology ·Hyun‐Jong Jang, Kwang‐Hyun Cho, (unknown), Sang June Hahn, Myung-Suk Kim, Duck‐Joo Rhie	19
18	Differential Cholinergic Modulation of Ca²⁺ Transients Evoked by Backpropagating Action Potentials in Apical and Basal Dendrites of Cortical Pyramidal Neurons 2008 ·Journal of Neurophysiology ·Kwang‐Hyun Cho, Hyun‐Jong Jang, Eun Hui Lee, Shin Hee Yoon, Sang June Hahn, Yang‐Hyeok Jo, Myung-Suk Kim, Duck‐Joo Rhie	13
19	Open channel block of Kv1.3 by rosiglitazone and troglitazone: Kv1.3 as the pharmacological target for rosiglitazone 2006 ·Naunyn-Schmiedeberg s Archives of Pharmacology ·Hye Sook Ahn, Sung Eun Kim, Hyun‐Jong Jang, Myung-Jun Kim, Duck‐Joo Rhie, (unknown), Yang‐Hyeok Jo, Myung-Suk Kim, Ki-Wug Sung, Seong-Yun Kim, Sang June Hahn	19
20	Serotonin inhibits the induction of NMDA receptor-dependent long-term potentiation in the rat primary visual cortex 2006 ·Brain Research ·(unknown), Hyun‐Jong Jang, Kwang‐Hyun Cho, Sang June Hahn, Myung-Jun Kim, Shin Hee Yoon, Yang‐Hyeok Jo, Myung-Suk Kim, Duck‐Joo Rhie	35

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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