Julian Hecker

900 total citations
33 papers, 229 citations indexed

About

Julian Hecker is a scholar working on Genetics, Molecular Biology and Physiology. According to data from OpenAlex, Julian Hecker has authored 33 papers receiving a total of 229 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Genetics, 14 papers in Molecular Biology and 8 papers in Physiology. Recurrent topics in Julian Hecker's work include Genetic Associations and Epidemiology (19 papers), Genetic Mapping and Diversity in Plants and Animals (9 papers) and Bioinformatics and Genomic Networks (7 papers). Julian Hecker is often cited by papers focused on Genetic Associations and Epidemiology (19 papers), Genetic Mapping and Diversity in Plants and Animals (9 papers) and Bioinformatics and Genomic Networks (7 papers). Julian Hecker collaborates with scholars based in United States, South Korea and Germany. Julian Hecker's co-authors include Christoph Lange, Dmitry Prokopenko, Edwin K. Silverman, Dawn L. DeMeo, Heide Fier, Sharon M. Lutz, Michael H. Cho, Nan M. Laird, Kristina Mullin and Rudolph E. Tanzi and has published in prestigious journals such as Bioinformatics, American Journal of Respiratory and Critical Care Medicine and Scientific Reports.

In The Last Decade

Julian Hecker

30 papers receiving 227 citations

Peers

Julian Hecker

GENET

PRM

PHYSI

Yongqing Huang China

Jiahuan Xu China

Valérie Gagné‐Ouellet Canada

Kevin L. Keys United States

Kathy Pham United States

Daniel J. Panyard United States

Tatsuya Nogami Japan

N. Hashimoto Japan

Susan Hoonhorst Netherlands

Mathias Gorski Germany

Yongqing Huang China

Julian Hecker

88 ×1.0

46 ×0.7

GENET

60 ×1.0

PRM

72 ×1.3

PHYSI

14 ×0.9

Citations per year, relative to Julian Hecker Julian Hecker (= 1×) peers Yongqing Huang

Countries citing papers authored by Julian Hecker

Since Specialization

Citations

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

Fields of papers citing papers by Julian Hecker

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Julian Hecker

This figure shows the co-authorship network connecting the top 25 collaborators of Julian Hecker. A scholar is included among the top collaborators of Julian Hecker 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 Julian Hecker. Julian Hecker 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

Lee, Sanghun, Rachel S. Kelly, Kevin Mendez, et al.. (2025). On the analysis of metabolite quantitative trait loci: Impact of different data transformations and study designs. Science Advances. 11(15). eadp4532–eadp4532. 1 indexed citations

Liu, Tao, Julian Hecker, Siqi Liu, et al.. (2024). The Asthma Risk Gene, GSDMB, Promotes Mitochondrial DNA-induced ISGs Expression. PubMed. 1(1). 10005–10005. 7 indexed citations

Hahn, Georg, Dmitry Prokopenko, Julian Hecker, et al.. (2024). Polygenic hazard score models for the prediction of Alzheimer's free survival using the lasso for Cox's proportional hazards model. Genetic Epidemiology. 49(1). e22581–e22581. 2 indexed citations

Willett, Julian, Georg Hahn, Kristina Mullin, et al.. (2024). Assessing polyomic risk to predict Alzheimer's disease using a machine learning model. Alzheimer s & Dementia. 20(12). 8700–8714. 1 indexed citations

Hecker, Julian, et al.. (2023). Fallacies and Pitfalls in Genome-Wide Association Studies. 4(2). 1 indexed citations

Hecker, Julian, Sanghun Lee, Priyadarshini Kachroo, et al.. (2023). A consistent pattern of slide effects in Illumina DNA methylation BeadChip array data. Epigenetics. 18(1). 2257437–2257437.

Kachroo, Priyadarshini, Julian Hecker, Augusto A. Litonjua, et al.. (2023). DNA Methylation Predicting Lung Function Trajectories Across Life Course in Multi-ethnic Childhood Cohorts. A1160–A1160.

Wang, Xu‐Wen, Tong Wang, Can Chen, et al.. (2023). Benchmarking omics-based prediction of asthma development in children. Respiratory Research. 24(1). 63–63. 6 indexed citations

Prokopenko, Dmitry, Sanghun Lee, Julian Hecker, et al.. (2022). Region-based analysis of rare genomic variants in whole-genome sequencing datasets reveal two novel Alzheimer’s disease-associated genes: DTNB and DLG2. Molecular Psychiatry. 27(4). 1963–1969. 16 indexed citations

10.

Hecker, Julian, Dmitry Prokopenko, Matthew Moll, et al.. (2022). A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables. PLoS Genetics. 18(11). e1010464–e1010464. 3 indexed citations

11.

Lee, Sanghun, Georg Hahn, Julian Hecker, et al.. (2022). A comparison between similarity matrices for principal component analysis to assess population stratification in sequenced genetic data sets. Briefings in Bioinformatics. 24(1). 5 indexed citations

12.

Lee, Sanghun, Dmitry Prokopenko, Rachel S. Kelly, et al.. (2022). Zinc finger protein 33B demonstrates sex interaction with atopy-related markers in childhood asthma. European Respiratory Journal. 61(1). 2200479–2200479. 3 indexed citations

13.

Hahn, Georg, Sharon M. Lutz, Julian Hecker, et al.. (2020). locStra: Fast analysis of regional/global stratification in whole‐genome sequencing studies. Genetic Epidemiology. 45(1). 82–98. 4 indexed citations

14.

Lee, Sanghun, Jessica Lasky‐Su, Christoph Lange, et al.. (2020). A novel locus for exertional dyspnoea in childhood asthma. European Respiratory Journal. 57(2). 2001224–2001224. 6 indexed citations

15.

Hecker, Julian, F. William Townes, Priyadarshini Kachroo, et al.. (2020). A unifying framework for rare variant association testing in family-based designs, including higher criticism approaches, SKATs, and burden tests. Bioinformatics. 36(22-23). 5432–5438. 5 indexed citations

16.

Won, Sungho, et al.. (2019). Effect of population stratification on SNP‐by‐environment interaction. Genetic Epidemiology. 43(8). 1046–1055. 6 indexed citations

17.

Hecker, Julian, Nan M. Laird, & Christoph Lange. (2019). A comparison of popular TDT‐generalizations for family‐based association analysis. Genetic Epidemiology. 43(3). 300–317. 3 indexed citations

18.

Hecker, Julian, Ingo Ruczinski, Michael H. Cho, et al.. (2019). A flexible and nearly optimal sequential testing approach to randomized testing: QUICK‐STOP. Genetic Epidemiology. 44(2). 139–147. 2 indexed citations

19.

Ragland, M.F., Christopher J. Benway, Sharon M. Lutz, et al.. (2019). Genetic Advances in Chronic Obstructive Pulmonary Disease. Insights from COPDGene. American Journal of Respiratory and Critical Care Medicine. 200(6). 677–690. 60 indexed citations

20.

Hecker, Julian, Xin Xu, F. William Townes, et al.. (2017). Family‐based tests for associating haplotypes with general phenotype data. Genetic Epidemiology. 42(1). 123–126. 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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