Hae Kyung Im

29.7k total citations · 2 hit papers
80 papers, 4.2k citations indexed

About

Hae Kyung Im is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Hae Kyung Im has authored 80 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Molecular Biology, 41 papers in Genetics and 18 papers in Cancer Research. Recurrent topics in Hae Kyung Im's work include Genetic Associations and Epidemiology (33 papers), Bioinformatics and Genomic Networks (18 papers) and Genetic Mapping and Diversity in Plants and Animals (12 papers). Hae Kyung Im is often cited by papers focused on Genetic Associations and Epidemiology (33 papers), Bioinformatics and Genomic Networks (18 papers) and Genetic Mapping and Diversity in Plants and Animals (12 papers). Hae Kyung Im collaborates with scholars based in United States, United Kingdom and China. Hae Kyung Im's co-authors include Dan L. Nicolae, Eric R. Gamazon, Nancy J. Cox, Heather E. Wheeler, Alvaro Barbeira, Keston Aquino-Michaels, Kaanan P. Shah, Paul J. Rathouz, James D. Forester and Milton Pividori and has published in prestigious journals such as Science, Nature Communications and Nature Genetics.

In The Last Decade

Hae Kyung Im

78 papers receiving 4.1k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A gene-based association method for mapping traits using reference transcriptome data

2015 975 citations Eric R. Gamazon, Heather E. Wheeler et al. Nature Genetics profile →
Opportunities and challenges for transcriptome-wide association studies

2019 506 citations Michael Wainberg, Nasa Sinnott-Armstrong et al. Nature Genetics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hae Kyung Im United States	27	2.3k	1.9k	741	351	280	80	4.2k
Paul Shannon United States	23	3.0k 1.3×	1.6k 0.9×	508 0.7×	323 0.9×	244 0.9×	43	4.8k
Chad D. Huff United States	27	2.2k 0.9×	3.1k 1.7×	769 1.0×	365 1.0×	184 0.7×	66	4.9k
Abigail W. Bigham United States	27	2.6k 1.1×	3.6k 1.9×	1.0k 1.4×	493 1.4×	120 0.4×	61	6.2k
Samuel Deutsch United States	32	2.5k 1.1×	1.5k 0.8×	422 0.6×	143 0.4×	181 0.6×	63	4.1k
Eduardo Ruiz‐Pesini Spain	35	4.7k 2.0×	1.6k 0.9×	532 0.7×	506 1.4×	350 1.3×	128	6.8k
Xiaoming Liu China	36	3.3k 1.4×	2.7k 1.4×	988 1.3×	247 0.7×	225 0.8×	234	6.6k
Altuna Akalin Germany	30	3.4k 1.5×	746 0.4×	583 0.8×	213 0.6×	95 0.3×	61	4.4k
Min Zhao China	34	2.2k 0.9×	735 0.4×	847 1.1×	154 0.4×	296 1.1×	202	4.6k
Vardhman K. Rakyan United Kingdom	36	5.0k 2.1×	2.3k 1.2×	478 0.6×	371 1.1×	90 0.3×	60	6.4k
Eran Eden Israel	13	3.6k 1.5×	684 0.4×	522 0.7×	248 0.7×	125 0.4×	25	4.9k

Countries citing papers authored by Hae Kyung Im

Since Specialization

Citations

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

Fields of papers citing papers by Hae Kyung Im

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hae Kyung Im. 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 Hae Kyung Im. The network helps show where Hae Kyung Im may publish in the future.

Co-authorship network of co-authors of Hae Kyung Im

This figure shows the co-authorship network connecting the top 25 collaborators of Hae Kyung Im. A scholar is included among the top collaborators of Hae Kyung Im 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 Hae Kyung Im. Hae Kyung Im 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

Chiou, Joshua, Francesca Luca, Roger Piqué-Regi, et al.. (2025). Multi-INTACT: integrative analysis of the genome, transcriptome, and proteome identifies causal mechanisms of complex traits. Genome biology. 26(1). 19–19. 2 indexed citations

Ardlie, Kristin, Kent D. Taylor, Peter Durda, et al.. (2024). Transcriptome-wide association study of the plasma proteome reveals cis and trans regulatory mechanisms underlying complex traits. The American Journal of Human Genetics. 111(3). 445–455. 2 indexed citations

Aguet, François, Kaur Alasoo, Yang Li, et al.. (2023). Molecular quantitative trait loci. Nature Reviews Methods Primers. 3(1). 49 indexed citations

Pharoah, Paul D.P., Simon A. Gayther, Ani Manichaikul, et al.. (2023). Predicted Proteome Association Studies of Breast, Prostate, Ovarian, and Endometrial Cancers Implicate Plasma Protein Regulation in Cancer Susceptibility. Cancer Epidemiology Biomarkers & Prevention. 32(9). 1198–1207. 4 indexed citations

Li, Yu, Xue Zhong, Kanix Wang, et al.. (2023). The high-dimensional space of human diseases built from diagnosis records and mapped to genetic loci. Nature Computational Science. 3(5). 403–417. 4 indexed citations

Mikhaylova, Anna V., Chris Gignoux, Kristin Ardlie, et al.. (2023). Multivariate adaptive shrinkage improves cross-population transcriptome prediction and association studies in underrepresented populations. Human Genetics and Genomics Advances. 4(4). 100216–100216. 5 indexed citations

Liang, Yanyu, François Aguet, Alvaro Barbeira, Kristin Ardlie, & Hae Kyung Im. (2021). A scalable unified framework of total and allele-specific counts for cis-QTL, fine-mapping, and prediction. Nature Communications. 12(1). 1424–1424. 14 indexed citations

Barbeira, Alvaro, Yanyu Liang, Rodrigo Bonazzola, et al.. (2020). Fine‐mapping and QTL tissue‐sharing information improves the reliability of causal gene identification. Genetic Epidemiology. 44(8). 854–867. 26 indexed citations

He, Yuan, Surya B. Chhetri, Marios Arvanitis, et al.. (2020). sn-spMF: matrix factorization informs tissue-specific genetic regulation of gene expression. Genome biology. 21(1). 235–235. 11 indexed citations

10.

Zhang, Yuhua, Corbin Quick, Ketian Yu, et al.. (2020). PTWAS: investigating tissue-relevant causal molecular mechanisms of complex traits using probabilistic TWAS analysis. Genome biology. 21(1). 232–232. 45 indexed citations

11.

Mohammadi, Pejman, Stephane E. Castel, Beryl B. Cummings, et al.. (2019). Genetic regulatory variation in populations informs transcriptome analysis in rare disease. Science. 366(6463). 351–356. 64 indexed citations

12.

Wainberg, Michael, Nasa Sinnott-Armstrong, Nicholas Mancuso, et al.. (2019). Opportunities and challenges for transcriptome-wide association studies. Nature Genetics. 51(4). 592–599. 506 indexed citations breakdown →

13.

Barbeira, Alvaro, Milton Pividori, Jiamao Zheng, et al.. (2019). Integrating predicted transcriptome from multiple tissues improves association detection. PLoS Genetics. 15(1). e1007889–e1007889. 169 indexed citations

14.

Li, Yang, David A. Knowles, Jack Humphrey, et al.. (2017). Annotation-free quantification of RNA splicing using LeafCutter. Nature Genetics. 50(1). 151–158. 358 indexed citations

15.

LaCroix, Bonnie, et al.. (2014). The impact of microRNA expression on cellular proliferation. Human Genetics. 133(7). 931–938. 44 indexed citations

16.

Wu, Kehua, Eric R. Gamazon, Hae Kyung Im, et al.. (2014). Genome-wide Interrogation of Longitudinal FEV1 in Children with Asthma. American Journal of Respiratory and Critical Care Medicine. 190(6). 619–627. 14 indexed citations

17.

Ziliak, Dana, Eric R. Gamazon, Bonnie LaCroix, et al.. (2012). Genetic Variation That Predicts Platinum Sensitivity Reveals the Role of miR-193b* in Chemotherapeutic Susceptibility. Molecular Cancer Therapeutics. 11(9). 2054–2061. 30 indexed citations

18.

Arowolo, Olukayode, Temidayo O. Ogundiran, Hae Kyung Im, et al.. (2012). Neoadjuvant capecitabine chemotherapy in women with newly diagnosed locally advanced breast cancer in a resource-poor setting (Nigeria): Efficacy and safety in a phase II feasibility study.. Journal of Clinical Oncology. 30(15_suppl). e11554–e11554. 1 indexed citations

19.

Gamazon, Eric R., Hae Kyung Im, Peter H. O’Donnell, et al.. (2011). Comprehensive Evaluation of the Contribution of X Chromosome Genes to Platinum Sensitivity. Molecular Cancer Therapeutics. 10(3). 472–480. 6 indexed citations

20.

Kenny, Hilary A., András Ladányi, S. Diane Yamada, et al.. (2010). Targeting the Urokinase Plasminogen Activator Receptor Inhibits Ovarian Cancer Metastasis. Clinical Cancer Research. 17(3). 459–471. 65 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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