Heejong Sung

614 total citations
21 papers, 310 citations indexed

About

Heejong Sung is a scholar working on Genetics, Molecular Biology and Cell Biology. According to data from OpenAlex, Heejong Sung has authored 21 papers receiving a total of 310 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Genetics, 6 papers in Molecular Biology and 3 papers in Cell Biology. Recurrent topics in Heejong Sung's work include Genetic Associations and Epidemiology (11 papers), Genetic and phenotypic traits in livestock (5 papers) and Genetic Mapping and Diversity in Plants and Animals (5 papers). Heejong Sung is often cited by papers focused on Genetic Associations and Epidemiology (11 papers), Genetic and phenotypic traits in livestock (5 papers) and Genetic Mapping and Diversity in Plants and Animals (5 papers). Heejong Sung collaborates with scholars based in United States, Canada and South Korea. Heejong Sung's co-authors include Nancy R. Mendell, Deborah L. Levy, Steven Matthysse, Fei Ji, Debra Titone, David M. Yousem, In Ho Lee, Elçin Zan, Michael J. Coleman and Alexander F. Wilson and has published in prestigious journals such as Scientific Reports, PLoS Genetics and American Journal of Roentgenology.

In The Last Decade

Heejong Sung

19 papers receiving 307 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Heejong Sung United States 9 67 61 56 56 46 21 310
Douglas J. Hyder United States 7 46 0.7× 31 0.5× 56 1.0× 18 0.3× 13 0.3× 9 397
Pen‐Jung Wang Taiwan 12 21 0.3× 75 1.2× 98 1.8× 96 1.7× 32 0.7× 51 399
A Martelli Italy 10 28 0.4× 24 0.4× 91 1.6× 44 0.8× 38 0.8× 21 357
Gemma García‐Fructuoso Spain 9 32 0.5× 120 2.0× 104 1.9× 67 1.2× 37 0.8× 15 408
G. Bensimon France 7 51 0.8× 113 1.9× 15 0.3× 28 0.5× 75 1.6× 8 468
Nancy J. Charest United States 8 103 1.5× 133 2.2× 215 3.8× 15 0.3× 51 1.1× 9 616
J. Tamraz France 10 13 0.2× 36 0.6× 59 1.1× 38 0.7× 42 0.9× 37 316
Shin Okazaki Japan 12 39 0.6× 160 2.6× 243 4.3× 148 2.6× 50 1.1× 79 620
A. R. Valentine United Kingdom 11 25 0.4× 73 1.2× 70 1.3× 25 0.4× 13 0.3× 25 546
Takayuki Kanai Japan 9 23 0.3× 57 0.9× 56 1.0× 47 0.8× 15 0.3× 17 519

Countries citing papers authored by Heejong Sung

Since Specialization
Citations

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

Fields of papers citing papers by Heejong Sung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Heejong Sung

This figure shows the co-authorship network connecting the top 25 collaborators of Heejong Sung. A scholar is included among the top collaborators of Heejong Sung 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 Heejong Sung. Heejong Sung 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.
Sung, Heejong, Layla Kassem, Nirmala Akula, et al.. (2024). Independent inheritance of cognition and bipolar disorder in a family sample. American Journal of Medical Genetics Part B Neuropsychiatric Genetics. 198(1). e33001–e33001.
2.
Song, Christopher, Heejong Sung, Mani Yavi, et al.. (2023). Exome-wide association study of treatment-resistant depression suggests novel treatment targets. Scientific Reports. 13(1). 12467–12467. 7 indexed citations
3.
Song, Christopher, Heejong Sung, Mani Yavi, et al.. (2022). EXOME-WIDE ASSOCIATION STUDY OF TREATMENT-RESISTANT DEPRESSION SUGGESTS NOVEL TREATMENT TARGETS. European Neuropsychopharmacology. 63. e268–e268. 2 indexed citations
4.
Sung, Heejong, Paula L. Hyland, Alexander Pemov, et al.. (2020). Genome‐wide association study of café‐au‐lait macule number in neurofibromatosis type 1. Molecular Genetics & Genomic Medicine. 8(10). e1400–e1400. 4 indexed citations
5.
Cropp, Cheryl D., et al.. (2018). ComPaSS‐GWAS: A method to reduce type I error in genome‐wide association studies when replication data are not available. Genetic Epidemiology. 43(1). 102–111. 7 indexed citations
6.
Székely, Eszter, Cristina M. Justice, Philip R. Jansen, et al.. (2018). Genetic associations with childhood brain growth, defined in two longitudinal cohorts. Genetic Epidemiology. 42(4). 405–414. 8 indexed citations
7.
Lyons, Jonathan J., Stephanie C. Stotz, Jack Chovanec, et al.. (2017). A common haplotype containing functional CACNA1H variants is frequently coinherited with increased TPSAB1 copy number. Genetics in Medicine. 20(5). 503–512. 21 indexed citations
8.
9.
10.
Lee, In Ho, Neil R. Miller, Elçin Zan, et al.. (2015). Visual Defects in Patients With Pituitary Adenomas: The Myth of Bitemporal Hemianopsia. American Journal of Roentgenology. 205(5). W512–W518. 44 indexed citations
11.
Pemov, Alexander, Heejong Sung, Paula L. Hyland, et al.. (2014). Genetic Modifiers of Neurofibromatosis Type 1-Associated Café-au-Lait Macule Count Identified Using Multi-platform Analysis. PLoS Genetics. 10(10). e1004575–e1004575. 24 indexed citations
12.
Miller, Nancy H., Cristina M. Justice, Beth Marosy, et al.. (2012). Intra-Familial Tests of Association between Familial Idiopathic Scoliosis and Linked Regions on 9q31.3–q34.3 and 16p12.3–q22.2. Human Heredity. 74(1). 36–44. 9 indexed citations
13.
Simpson, Claire L., Cristina M. Justice, Robert Wojciechowski, et al.. (2011). Old lessons learned anew: family-based methods for detecting genes responsible for quantitative and qualitative traits in the Genetic Analysis Workshop 17 mini-exome sequence data. BMC Proceedings. 5(S9). S83–S83. 9 indexed citations
14.
Sung, Heejong, Yoonhee Kim, Juanliang Cai, et al.. (2011). Comparison of results from tests of association in unrelated individuals with uncollapsed and collapsed sequence variants using tiled regression. BMC Proceedings. 5(S9). S15–S15. 7 indexed citations
15.
Kim, Yoonhee, Qing Li, Cheryl D. Cropp, et al.. (2011). Performance of random forests and logic regression methods using mini-exome sequence data. BMC Proceedings. 5(S9). S104–S104. 2 indexed citations
16.
17.
Kim, Yoonhee, Robert Wojciechowski, Heejong Sung, et al.. (2009). Evaluation of random forests performance for genome-wide association studies in the presence of interaction effects. BMC Proceedings. 3(S7). S64–S64. 20 indexed citations
18.
Levy, Deborah L., Michael J. Coleman, Heejong Sung, et al.. (2009). The genetic basis of thought disorder and language and communication disturbances in schizophrenia. Journal of Neurolinguistics. 23(3). 176–192. 74 indexed citations
19.
Sung, Heejong, Fei Ji, Deborah L. Levy, Steven Matthysse, & Nancy R. Mendell. (2008). The power of linkage analysis of a disease-related endophenotype using asymmetrically ascertained sib pairs. Computational Statistics & Data Analysis. 53(5). 1829–1842. 6 indexed citations
20.
Sung, Heejong, Stephen J. Finch, Kenny Ye, & Nancy R. Mendell. (2005). A gene-model-free method for linkage analysis of a disease-related-trait based on analysis of proband/sibling pairs. BMC Genetics. 6(S1). S47–S47. 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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